Impact of Postpartum Diseases and Reproductive Programs on Fertility of Grazing Dairy Cows

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Title:
Impact of Postpartum Diseases and Reproductive Programs on Fertility of Grazing Dairy Cows
Physical Description:
1 online resource (232 p.)
Language:
english
Creator:
Ribeiro,Eduardo De Souza
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
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Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Animal Sciences
Committee Chair:
Santos, Jose
Committee Members:
Thatcher, William W
Hansen, Peter J

Subjects

Subjects / Keywords:
breeding -- cow -- dairy -- grazing -- health -- insemination -- reproduction -- season -- synchronization -- timed
Animal Sciences -- Dissertations, Academic -- UF
Genre:
Animal Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
The objectives of this thesis were to identify factors affecting reproductive efficiency of grazing dairy cows, and to develop suitable reproductive programs for seasonal calving grazing dairy cows. Experiments were conducted focusing on characterizing the epidemiology of diseases and their impact on fertility of dairy cows, and on establishing timed artificial insemination (AI) programs to maximize pregnancy per AI (P/AI) at the beginning as well as throughout the breeding season. In the first study, 957 lactating grazing cows were evaluated and health problems diagnosed from calving until 30 days after first AI. Clinical diseases were characterized as calving problems, metritis, endometritis, mastitis, lameness, digestive and respiratory problems. On d 7 and 14 postpartum, blood was sampled and analyzed for concentrations of calcium (Ca), nonesterified fatty acids, and ?-hydroxybutyrate to identify subclinical diseases such as hypocalcemia, severe negative energy balance and ketosis. Incidence of postpartum clinical and subclinical diseases in grazing dairy cows in the two herds studied were high and associated with resumption of estrous cyclicity, pregnancy per AI (P/AI), and pregnancy loss. In general, diseases reduced the prevalence of estrous cyclic cows at 49 d postpartum, reduced P/AI on d 30 and 65 after the first insemination, and increased the risk of pregnancy loss. Results demonstrated that management of grazing cows should focus on reducing periparturient diseases and lipid mobilization and improving Ca homeostasis in order to optimize fertility of grazing cows. In the second study, objectives were to compare P/AI of dairy cows subjected to the 5-d timed AI protocol either presynchronized or supplemented with progesterone during the protocol, and using twice the luteolytic dose of PGF2? administered either as single or split injections. Lactating dairy cows were randomly assigned to 1 of 4 treatments arranged as a 2 x 2 factorial, with two synchronization and two luteolytic treatments. Half of the cows had their estrous cycles presynchronized with the G6G protocol before the 5-d timed AI protocol using 1 mg of cloprostenol either as a single injection (G6G-SinglePG) or split into two injections in two consecutive days (G6G-SplitPG). The other half of the cows were not presynchronized, but received a controlled internal drug-release (CIDR) containing progesterone between the GnRH and the first PGF2alpha injection of the protocol, and 1 mg of cloprostenol either as a single (CIDR-SinglePG) or split into two injections (CIDR-SplitPG). Presynchronization increased the proportion of cows with a corpus luteum (CL) on the first GnRH of the 5-d timed AI protocol (80.6 vs. 58.8%), ovulation to the first GnRH of the protocol (64.2 vs. 50.2%), and presence (95.6 vs. 88.4%) and number (1.79 vs. 1.30) of CL at PGF2alpha. Luteolysis was greater for the split injection of PGF2alpha (95.9 vs. 72.2%), especially for presynchronized cows (96.2 vs. 61.7%). An interaction was observed for P/AI on d 35. For cows not presynchronized, method of PGF2alpha administration had no effect on P/AI (CIDR-SinglePG = 30.2 vs. CIDR-SplitPG = 34.3%), whereas for presynchronized cows, splitting the dose into two injections improved P/AI (G6G-SinglePG = 28.7 vs. G6G-SplitPG = 45.4%). In conclusion, presynchronization and splitting the dose of PGF2alpha into two injections increased P/AI in grazing dairy cows subjected to the 5-d timed AI protocol. Objectives of the third study were to compare the impact of presynchronization and resynchronization methods on fertility responses of grazing dairy cows at first and second AI and pregnancy rate during the entire breeding season. Lactating dairy cows (n = 1,263) were randomly assigned to 1 of 4 treatments arranged as a 2 x 2 factorial with two presynchronization and two resynchronization treatments. Cows had their estrous cycles presynchronized with either a PGF2alpha-based program (Presynch) or with a PGF2alpha-GnRH-based program (G6G). The 5-d timed AI protocol was used for all cows. On d 12, cows in each presynchronization treatment remained either as untreated controls (RCON) or received a CIDR insert containing progesterone for 7 d (RCIDR). Estrus was observed daily starting on d 19 after AI and cows in estrus were inseminated on the same day. On d 35 bulls were placed with the cows for additional 65 d, completing a 100-d breeding season. A greater proportion of G6G cows had progesterone ? 1 ng/mL at the first GnRH of timed AI protocol compared with Presynch cows (82.0 vs. 74.3%). Presynchronization treatment did not influence P/AI, but cows in G6G had increased risk of pregnancy loss between d 30 and 65 after the first AI (12.9 vs. 8.1%). Nevertheless, an interaction between presynchronization and ovarian status was observed, and cows initiating the timed AI with progesterone ? 1 ng/mL had greater P/AI when previously treated with Presynch than G6G. Conversely, G6G benefited P/AI of cows initiating the timed AI with progesterone < 1 ng/mL. Resynchronization with RCIDR altered the pattern of return to estrus, but it did not increase the rate of re-insemination and decreased the proportion of pregnant cows at the end of the 100-d breeding period (80.6 vs. 84.4%). In addition, breed of the cow, body condition, days in milk, and plasma progesterone concentration at the first GnRH of the timed AI protocol had marked effects on fertility and were identified as important factors affecting the reproductive performance of lactating grazing dairy cows. The fourth experiment compared the effects of two methods of presynchronization of the estrous cycle and two lengths of proestrus on fertility of grazing dairy cows subjected to the 5-d timed AI protocol. Lactating grazing dairy cows (n = 1,754) were assigned to 1 of 4 treatments in a 2 x 2 factorial arrangement, with two methods of presynchronization and two lengths of proestrus. Presynchronization treatments were either a PGF2alpha-based program (Presynch) or PGF2alpha-GnRH-based program double Ovsynch (DO). The two lengths of proestrus were either 58 h (COS58) or 72 h (COS72) after the first PGF2alpha injection of the 5-d timed AI protocol. Presynchronization did not affect the concentration of estradiol at AI (DO = 6.4 vs. Presynch = 5.8 pg/mL), detection of estrus at AI (20.8 vs. 25.9%), or P/AI on d 30 (56.8 vs. 59.1%) and 65 (52.5 vs. 52.4%) after first insemination. Cows receiving COS72 had increased concentration of estradiol (6.6 vs.5.5 pg/mL) and detection of estrus at AI (28.5 vs. 10.8%) compared with cows receiving COS58. Length of proestrus did not affect P/AI on d 30 (58.7 vs. 56.1%) but, in Presynch cows, COS58 was detrimental to fertility on d 65 (54.9 vs. 46.5%). Pregnancy loss was greater for Presynch than DO (7.6 vs. 11.3%), but length of proestrus had no impact on losses of pregnancy in the first 65 d of gestation. Estrous cyclic cows had greater P/AI than anovular cows on d 30 (61.7 vs. 35.1%) and 65 (56.1 vs. 30.7%), but no interaction between estrous cyclic status and treatments were detected. Presynch and DO resulted in similar fertility, but limiting the length of proestrus to 58 h reduced P/AI in the 5-d timed AI protocol when cows had their estrous cycle presynchronized with the Presynch, but not the DO.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Eduardo De Souza Ribeiro.
Thesis:
Thesis (M.S.)--University of Florida, 2011.
Local:
Adviser: Santos, Jose.

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Applicable rights reserved.
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UFE0043474:00001


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1 I MPACT OF POSTPARTUM DISEASES AND REPRODU CTIVE PROGRAMS ON FERTILITY OF GRAZ ING DAIRY COWS By EDUARDO DE SOUZA RIBEIRO A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE R EQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2011

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2 2011 Eduardo de Souza Ribeiro

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3 To my parents for their love and endless support

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4 ACKNOWLEDGMENTS First and foremost I would like to thank God for everything in m y life and for making it all possible. I would like to express my sincere gratitude to my advisor Dr. Jos Eduardo Portela Santos, for the opportunity of pursuing my Master of Science degree at the University of Florida, for his continuous support, encour agement and enthusiasm during my scientific learning. I have a profound admiration for his vast knowledge and for his commitment and passion for research, which certainly motivated me and all his students to develop as scientists. I extend my appreciation to my committee members, Dr. William W. Thatcher and Dr. Peter J. Hansen, for all their insightful contribution throughout the last two years in my development as a young scientist. It is an honor for me to have in my committee two of most respected reprod uctive biologists. I was exposed to their scientific work when I started my veterinary studies in Brazil, and it certainly contributed to magnify my passion for the biology of reproduction and the desire to pursue an academic career, which has been reinfor ced by our relationship during these two years. I owe special thanks to my mentors during my studies in Veterinary Medicine in Brazil, Dr. Marcelo Bertolini and Dr. Alceu Mezzalira, for helping me to initiate my career as a researcher. I feel fortunate to have worked with mentors that encouraged me to develop critical thinking, initiative and independent spirit. I specially thank Dr. Bertolini for making the initial contact with Dr. Santos to extend my experience abroad, which was very important for my prof essional and personal development and made all the remaining possible.

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5 like to thank t he staff and faculty of the Department of Animal Sciences, especially Dr. Alan Ealy, Dr. Charles Staples, Dr. Joel Yelich, and Mr. Sergji Sennikov for sharing their laboratories and for their assistance with sample processing and general lab procedures; an d also Debra Sykes, Joann Fischer and Sabrina Robinson for all their help with clerical work. I also would like to thank Dr. Carlos Risco and Dr. Fiona Maunsell at the College of Veterinary Medicine at the University of Florida, for sharing their laborator y and for their assistance with lab procedures. I am very grateful to Dr. Flvio Silvestre and Dr. Ronaldo Cerri for their assistance during the experiments and for sharing their experience and knowledge. I would like to express my profound appreciation t o my labmates Fbio Lima, Leandro Greco, Rafael Bisinotto and Natalia Martinez; and visiting students Maurcio Favoreto, Ana Paula Monteiro, Henderson Ayres, Leonardo Tondello, Rafael Marsola, Mariana Carvalho and Ana Lcia Sevarolli. Without their valuabl e help, none of the work presented here would have been possible. I extend my appreciation to the Animal Sciences graduate students Izabella Thompson, Guilherme Marquezini, Dan Wang, Miriam Garcia, and Milerky Perdomo for their valuable help with the exper iments and for sharing the responsibilities of our laboratory. I am not going to list all of them, but I thank all the friends I made during the last two years in Gainesville for all the fun that helped me overcome the distance from home. I especially tha nk Fbio Lima, Leandro Greco, and Rafael Bisinotto whom, in addition to the countless long days of help with the design and conduction of all

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6 US. I really appreciate their friendship. I extend very special thanks to my girlfriend Ana Paula Monteiro for her tremendous help with the experiments, her love, support, complicity, and patience during all these years. I am very grateful to the owner of Alliance Dairies, Ronald St. John, and staff for use of their cows and facilities. Special thanks to Pat Cilo Cilo, Cliff Reindl, Nilo Francisco, Pete Hetherington, Hildelberto, Antonio and Franklin for assistance with the experiments. Last but not least, I want to thank my entire fam ily and friends in Brazil for all their support, motivation, and encouragement. To be away from home was not an easy thing for me who has always been very close to the entire family and friends. Nonetheless, they made me feel spiritually close to them and motivated me to always move forward. I especially thank my aunts, Inez and Niralba, and my grandmothers, Benilde and Izabel, for all their prayers. Although they are not here among us anymore, I also would like to thank my grandfathers, Belarmindo and Jalb as, for having always motivated me to be a good person and to pursue Veterinary Medicine as a career. From where they are now, I am sure that they are very happy and proud of me. I express my deepest appreciation to my parents, Dejalmo Pereira Ribeiro and Liberaci de Souza Ribeiro, and to my brother and best friend Dejalmo Jnior. There are no words to express my love and gratitude to them. I am fortunate and very proud to have them as family and I thank God every day for this blessing of have them in my li fe. They are fantastic people who will be always by my side and who mean the most for me.

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7 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 12 L IST OF ABBREVIATIONS ................................ ................................ ........................... 13 ABSTRACT ................................ ................................ ................................ ................... 16 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 21 2 LITERATURE REVIEW ................................ ................................ .......................... 27 The Transition Period ................................ ................................ .............................. 27 Periparturient Diseases and Disorders ................................ ................................ ... 32 Postpartum Anovulation and Resumption of Estrous Cyclicity ................................ 39 Oocyte and Follicle Development: From Primordial Germ Cell to Antral Follicles ... 43 Estrous Cycle and Antral Follicle Development ................................ ...................... 48 Corpus Luteum Formation, Function and Regression ................................ ............. 58 Abrogation of Luteolysis and Maternal Recognition of Pregnancy .......................... 65 Reproductive Efficiency and Development of Timed Artificial Insemination Protocols ................................ ................................ ................................ .............. 68 General Features and Reproductive Managemen t in Seasonal Grazing Dairy Farms ................................ ................................ ................................ .................. 77 3 EPIDEMIOLOGY OF PERIPARTURIENT DISEASES AND THEIR IMPACTS ON FERTILITY OF DAIRY COWS IN SEASO NAL GRAZING FARMS .................. 87 Introductory Remarks ................................ ................................ .............................. 88 Materials and Methods ................................ ................................ ............................ 90 Cows, Pastures and Management ................................ ................................ ... 90 Characterization and Di agnosis of Health Problems ................................ ........ 91 Reproductive Management ................................ ................................ .............. 93 Determination of Estrous Cyclicity, Pregnancy Diagnoses and Body Condition Scoring ................................ ................................ .......................... 94 Statistical Analyses ................................ ................................ .......................... 95 Results ................................ ................................ ................................ .................... 96 Estrous Cyclicity ................................ ................................ ............................... 98 Pregnancy per AI and Pregnancy Loss ................................ ............................ 99 Uterine Diseases and Fertility ................................ ................................ ......... 100 Concentrations of NEFA, BHBA, and Ca in Serum of Grazing Cows ............. 100

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8 Discussion ................................ ................................ ................................ ............ 101 Summary ................................ ................................ ................................ .............. 107 4 PREGNANCY PER ARTIFICIAL INSEMINATION OF DAIRY COWS FOLLOWING PRESYNCHRONIZATION AND SPLITTING PROSTAGLANDIN F INJECTION IN THE 5 D TIMED ARTIFICIAL INSEMINATION PROTOCOL 118 Introductory Remarks ................................ ................................ ............................ 119 Mater ials and Methods ................................ ................................ .......................... 121 Experiment 1 ................................ ................................ ................................ .. 121 Cows, pastures and management ................................ ........................... 121 Experimental design and randomization ................................ .................. 122 Synchronization and luteolytic treatments ................................ ................ 122 Ovarian ultrasonography and ovulatory responses ................................ .. 123 Progesterone analysis and luteolysis ................................ ....................... 123 Detection of estrus, body condition score and days in milk ...................... 124 Pregnancy diagnoses and pregnancy losses ................................ ........... 125 Experiment 2 ................................ ................................ ................................ .. 125 Cows, housing and diets ................................ ................................ .......... 125 Experimental design and randomization ................................ .................. 126 Synchronization protocol and luteolytic treatments ................................ .. 126 Pre gnancy diagnoses, milk yield and body condition score ..................... 126 Statistical Analyses ................................ ................................ ........................ 126 Experiment 1 ................................ ................................ ............................ 126 Experiment 2 ................................ ................................ ............................ 127 Results ................................ ................................ ................................ .................. 128 Experimen t 1 ................................ ................................ ................................ .. 128 Experiment 2 ................................ ................................ ................................ .. 131 Discussion ................................ ................................ ................................ ............ 131 Summary ................................ ................................ ................................ .............. 136 5 REPRODUCTIVE PERFORMANCE OF GRAZING DAIRY COW S FOLLOWING PRESYNCHRONIZATION AND RESYNCHRONIZATION PROTOCOLS ................................ ................................ ................................ ....... 144 Introductory Remarks ................................ ................................ ............................ 145 Materials and Methods ................................ ................................ .......................... 148 Cows, Pastures and Management ................................ ................................ 148 Reproductive Management ................................ ................................ ............ 149 Experimental Design and Randomization ................................ ....................... 149 Presynchronization Treatments and Timed AI Protocol ................................ 149 Resynchronization Treatments and Natural Service ................................ ...... 150 Blood Samples, Progesterone Analysis and Characterization of Ovarian Status ................................ ................................ ................................ .......... 151 Body Condition Score, Days in Milk and Milk Yield ................................ ........ 152 Pregnancy Diagnoses and Calculation of Reproductive Responses .............. 152 Statistical Analyses ................................ ................................ ........................ 153

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9 Results ................................ ................................ ................................ .................. 154 Presynchr onization Treatments ................................ ................................ ...... 155 Resynchronization Treatments ................................ ................................ ....... 156 Effects of Breed ................................ ................................ .............................. 157 Ovarian Status at First GnRH on Study Day 8 ................................ .............. 15 7 Body Cond ition Score and Days in Milk at First AI ................................ ......... 158 Discussion ................................ ................................ ................................ ............ 159 Summary ................................ ................................ ................................ .............. 164 6 EFFECTS OF PRESYNCHRONIZATION AND LENGTH OF PROESTRUS ON PREGNANCY PER ARTIFICIAL INSEMINATION OF GRAZING DAIRY COWS SUBJECTED TO THE 5 D TIMED ARTIFICIAL INSEMINATION PROTOCOL ... 174 Introductory Remarks ................................ ................................ ............................ 175 Materials and Methods ................................ ................................ .......................... 177 Cows, Pastures and Management ................................ ................................ 177 Experimental Design and Treatments ................................ ............................ 178 Ovarian Ultrasonography and Determination of Estrous Cyclicity .................. 179 Blood Samples and Estradiol Analysis ................................ ........................... 179 Detection of Estrus, Body Condition Score and Days in Milk ......................... 180 Remaining Breeding Season ................................ ................................ .......... 181 Pregnancy Diagnoses and Calculation of Reproductive Responses .............. 181 Statistical Analyses ................................ ................................ ........................ 182 Results ................................ ................................ ................................ .................. 184 Estrus at AI and Estradiol Concentrations ................................ ...................... 185 Pregnancy per AI and Pregnancy Loss ................................ .......................... 185 Reproduction in the Entire Breeding Season in Farm A ................................ 186 Discussion ................................ ................................ ................................ ............ 187 Summary ................................ ................................ ................................ .............. 192 7 GENERAL DISCUSSION, CONCLUSIONS AND IMPLICATIONS ...................... 199 LIST OF REFERENCES ................................ ................................ ............................. 208 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 232

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10 LIST OF TABLES Tabl e page 3 1 Incidence of clinical and subclinical diseases in early postpartum grazing dairy cows ................................ ................................ ................................ ......... 108 3 2 Impact of clinical and/or subclinical diseases on es trous cyclicity on d 49 postpartum and pregnancy per artificial insemination (AI) on d 30 and 65 after AI ................................ ................................ ................................ .............. 109 3 3 Impact of postpartum diseases on resumption of estrous cyclicity by d 49 postpartum ................................ ................................ ................................ ........ 110 3 4 Impact of postpartum diseases on pregnancy per AI on d 30 after first insemination ................................ ................................ ................................ ..... 111 3 5 Impact of postpartum diseases on pregnancy per AI on d 65 after first insemination ................................ ................................ ................................ ..... 112 3 6 Impact of po stpartum diseases on pregnancy loss between gestational days 30 and 65 ................................ ................................ ................................ ......... 113 3 7 Impact of clinical uterine diseases on pregnancy per AI on d 30 and 65 after insemination and on pregnancy loss between gestational days 30 and 65 ...... 114 3 8 Serum concentrations of Ca and nonesterified fatty acids (NEFA) on d 7 3 hydroxybutyrate (BHBA) on d 14 3 according to incidence of postpartum diseases ................................ ................................ ........................ 115 3 9 Correlation coefficients (r) among serum concentrations of metabolites and body condition score ................................ ................................ ......................... 116 3 10 Serum concentrations of Ca and nonesterified fatty acids (NEFA) on d 7 3 hydroxybutyrate (BHBA) on d 14 3 according to fertility response ...... 117 4 1 Effects of synchronization and luteolytic treatments on reproductive responses of grazing dairy cows Experiment 1 ................................ ............. 137 4 2 Effect of breed on reproductive responses of grazing dairy cows Experiment 1 ................................ ................................ ................................ ....................... 138 5 1 Effect of presynchronization treatments on reproductive outcomes of grazing dairy cows ................................ ................................ ................................ ......... 166 5 2 cows ................................ ................................ ................................ ................. 167

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11 5 3 Effect of resynchronization treatment on reproductive responses of grazing dairy cows ................................ ................................ ................................ ......... 168 5 4 Effect of breed on reproductive responses of grazing dairy cows ..................... 169 6 1 Effects of presynchronization and length of proestrus on reproductive outcomes of lactating grazing dairy cows after first insemination ..................... 193 6 2 Effects of method of presynchronization and estrous cyclic status on reproductive responses of grazing dairy cows ................................ .................. 194 6 3 Effects of presynchronization on reproductive responses of the remaining breeding season of farm A ................................ ................................ ............... 195 6 4 farm A ................................ ................................ ................................ ............... 196

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1 2 LIST OF FIGURES Figure page 4 1 Diagram of activities for Experiment 1. ................................ ............................ 139 4 2 Diagram of activities for Experiment 2. ................................ ............................ 140 4 3 Probability of CL at first GnRH of timed AI protocol (study d 8) accor ding to treatment and days postpartum (Panel A) or body condition score (Panel B). 141 4 4 Pregnancy per AI on d 35 and 64 after timed insemination and pregnancy loss for cows with or without ideal progesterone profiles on study d 3 and 0. 142 4 5 Pregnancy per AI on d 35 and 64 after timed insemination and pregnancy loss in lactating dairy cows subjected to 5 d timed AI protocol and receiving 50 m g of dinoprost administered either as a single injection on study d 3 or split into two injections administered on study d 3 and 2 (Experiment 2). ...... 143 5 1 Diagram of activities for the presynchronization treatments and timed artificial insemination program. ................................ ................................ ...................... 170 5 2 Diagram of activities during the resynchronization and natural service periods. ................................ ................................ ................................ ............. 171 5 3 Pregnancy on d 30 (A) and 65 (B) after the first AI according to presynchronization treatment and categor y of progesterone concentration in plasma at first GnRH of timed AI protocol. ................................ ....................... 172 5 4 Survival curves for interval to pregnancy according to breed (panel A) and progesterone category at the first GnRH of the timed AI (panel B). .................. 173 6 1 Diagram of activities in the study. ................................ ................................ .... 197 6 2 Fertility responses of grazing dairy cows at first insemination according breeds and presynchronization treatments in three seasonal grazing farms. ... 198

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13 LIST OF ABBREVIATION S HSD 3 beta 5 4 isomerase AI artificial insemination AMH anti Mullerian hormone ANOVA analysis of variance AHR adjusted hazard ratio AOR adjusted odds ratio ATP adenosil tri phosphate BCS body condition score BHBA hydroxybut y rate BMP bone morphogen et ic protein Ca calcium CARTPT cocaine and amphetamine regulated transcript cAMP cyclic adenosine monophosphate CI confidence interval CIDR controlled internal drug release CL corpus luteum COS58 cosynch timed artificial insemination protocol with 58h of proestrus COS72 cosynch timed artificial in semination protocol with 72h of proestrus CV coefficient of variation DAG 1,2 diacylglycerol DIM days in milk DMI dry matter intake DO double Ovsynch program of presynchronization and synchronization of the estrous cycle EDTA ethylenediaminetetraacetic acid

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14 FG F fibroblast growth factor FSH follicle stimulating hormone G6G PGF GnRH based protocol of presynchronization of the estrous cycle GDF growth differentiating factor GH growth hormone GnRH gonadotropin releasing hormone HDL high density lipoprotein IGF insuli n like growth factor IGFBP insulin like growth factor binding proteins IFNT interferon ISG interferon stimulate d genes LH luteinizing hormone MPF maturation promot ing factor mRNA messenger ribonucleic acid NEB negative energy balance NEFA nonesterified f atty acid NEL net energy of lactation OR odds ratio P/AI pregnancy per artificial insemination PAPP A plasma associated pregnancy protein A PG prostaglandin PGCs primordial germ cells PKA2 protein kinase A 2 PKC protein kinase C PLC phospholipase C

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15 PRESYN CH PGF 2 based protocol of presynchronization of the estrous cycle PVD purulent vaginal discharge RIA radioimmunoassay RCON group control of resynchronization treatment RCIDR resynchronization treatment using intravaginal inserts of progesterone ROC receiver operatin g characteristic SD standard deviation SNEB severe negative energy balance StAR steroidogenic acute regulatory protein TGF transforming growth factor TMR total mixed ration US United States VEGF vascular endothelial growth factor VLDL very low density prot ein

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16 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science IMPACT OF POSTPARTUM DISEASES AND REPRODU CTIVE PROGRAMS O N FERTILITY OF GRAZI NG DAIRY COWS By Eduardo de Souza Ribeiro August 2011 Chair: Jos Eduardo Portela Santos Major: Animal Sciences The o bjectives of this thesis were to identify factors affecting reproductive efficiency of grazing dairy cows, and to de velop suitable reproductive programs for seasonal calving grazing dairy cows Experiments were conducted focusing on characteriz ing the epidemiology of diseases and their impact on fertility of dairy cows and on establish ing timed artificial insemination (AI) programs to maximiz e pregnancy per AI (P/AI) at the beginning as well as throughout the breeding season. In the first study, 957 lactating grazing cows were evaluated and health problems diagnosed f rom calving until 30 days after first AI C linical di seases were characterized as calving problems, metritis, endometritis, mastitis, lameness, digestive and respiratory problems. On d 7 3 and 14 3 postpartum, blood was sampled and analyzed for concentrations of calcium (Ca) non esterified fatty acid s, a hydroxybuty rate to identify subclinical diseases such as hypocalcemia, severe negative energy balance and ketosis. I ncidence of postpartum clinical and subclinical diseases in grazing dairy cows in the two herds studied were high and associated with r esumption of estrous cyclicity, pregnancy per AI (P/AI) and pregnancy loss. In general, diseases reduced the prevalence of estrous cyclic cows at 49 d postpartum, reduced P/AI on d 30 and 65

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17 after the first insemination, and increased the risk of pregnanc y loss. Results demonstrated that management of grazing cows should focus on reducing periparturient diseases and lipid mobilization and improving Ca homeostasis in order to optimize fertility of grazing cows. In the second study, objectives were to compar e P/AI of dairy cows subjected to the 5 d timed AI protocol either presynchronized or supplement ed with progesterone during the protocol, and using twice the luteolytic dose of PGF administered either as single or split injections. Lactating dairy cows w ere randomly assigned to 1 of 4 treatments arranged as a 2 x 2 factorial, with two synchronization and two luteolytic treatments Half of the cows had their estrous cycles presynchronized with the G6G protocol before the 5 d timed AI protocol using 1 mg of cloprostenol either as a single injection (G6G SinglePG) or split into two injections in two consecutive days (G6G SplitPG). The other half of the cows were not presynchronized, but received a controlled internal drug release (CIDR) containing progesteron e between the GnRH and the first PGF injection of the protocol and 1 mg of cloprostenol either as a single (CIDR SinglePG) or split into two injections (CIDR SplitPG). Presynchronization increased the proportion of cows with a corpus luteum (CL) on the first GnRH of the 5 d timed AI protocol (80.6 vs. 58.8%), ovulation to the first GnRH of the protocol (64.2 vs. 50.2%), and presence (95.6 vs. 88.4%) and number (1.79 vs. 1.30) of CL at PGF Luteolysis was greater for the split injection of PGF (95.9 v s. 72.2%), especially for presynchronized cows (96.2 vs. 61.7%). An interaction was observed for P/AI on d 35. For cows not presynchronized, method of PGF administration had no effect on P/AI (CIDR SinglePG = 30.2 vs. CIDR SplitPG = 34.3%), whereas for p resynchronized cows,

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18 splitting the dose into two injections improved P/AI (G6G SinglePG = 28.7 vs. G6G SplitPG = 45.4%). In c onclu sion presynchronization and splitting the dose of PGF into two injections increased P/AI in grazing dairy cows subjected to the 5 d timed AI protocol. Objectives of the third study were to compare the impact of presynchronization and resynchronization methods on fertility responses of grazing dairy cows at first and second AI and pregnancy rate during the entire breeding seaso n. Lactating dairy cows (n = 1,263) were randomly assigned to 1 of 4 treatments arranged as a 2 x 2 factorial with two presynchronization and two resynchronization treatments. Cows had their estrous cycles presynchronized with either a PGF based program (Presynch) or with a PGF GnRH based program (G6G). The 5 d timed AI protocol was used for all cows. On d 12, cows in each presynchronization treatment remained either as untreated controls (RCON) or received a CIDR insert containing prog esterone for 7 d (RCIDR). Estrus was observed daily starting on d 19 after AI and cows in estrus were inseminated on the same day. On d 35 bulls were placed with the cows for additional 65 d, completing a 100 d breeding season A greater proportion of G6G cows had ng/mL at the first GnRH of timed AI protocol compared with Presynch cows (82.0 vs. 74.3%). Presynchronization treatment did not influence P/AI, but cows in G6G had increased risk of pregnancy loss between d 30 and 65 after the fir st AI (12.9 vs. 8.1%). Nevertheless, an interaction between presynchronization and ovarian status P/AI when previously treated with Presynch than G6G. Conversely G6G be nefited P/AI of cows initiating the timed AI with progesterone < 1 ng/mL. Resynchronization with

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19 RCIDR altered the pattern of return to estrus, but it did not increase the rate of re insemination and decreased the proportion of pregnant cows at the end of the 100 d breeding period (80.6 vs. 84.4%). In addition, breed of the cow, body condition, days in milk and plasma progesterone concentration at the first GnRH of the timed AI protocol had marked effects on fertility and were identif ied as important facto rs affecting the reproductive performance of lactating grazing dairy cows. The fourth experiment compared the effects of two methods of presynchronization of the estrous cycle and two lengths of proestrus on fertility of grazing dairy cows subjected to th e 5 d timed AI protocol. Lactating grazing dairy cows (n = 1,754) were assigned to 1 of 4 treatments in a 2 x 2 factorial arrangement, with two methods of presynchronization and two lengths of proestrus. Presynchronization treatments were either a PGF based program (Presynch) or PGF GnRH based program d ouble Ovsynch (DO). The two lengths of proestrus were either 58 h (COS58) or 72 h (COS72) after the first PGF injection of the 5 d timed AI protocol. Presynchronization did not affect the concentra tion of estradiol at AI (DO = 6.4 vs. Presynch = 5.8 pg/mL), detection of estrus at AI (20.8 vs. 25.9%), or P/AI on d 30 (56.8 vs. 59.1%) and 65 (52.5 vs. 52.4%) after first insemination. Cows receiving COS72 had increased concentration of estradiol (6.6 v s.5.5 pg/mL) and detection of estrus at AI (28.5 vs. 10.8%) compared with cows receiving COS58. Length of proestrus did not affect P/AI on d 30 (58.7 vs. 56.1%) but, in Presynch cows, COS58 was detrimental to fertility on d 65 (54.9 vs. 46.5%). Pregnancy l oss was greater for Presynch than DO (7.6 vs. 11.3%), but length of proestrus had no impact on losses of pregnancy in the first 65 d of gestation. Estrous cyclic cows had greater P/AI than anovular cows on d 30 (61.7 vs. 35.1%) and 65 (56.1

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20 vs. 30.7%), but no interaction between estrous cyclic status and treatments were detected. Presynch and DO resulted in similar fertility, but limiting the length of proestrus to 58 h reduced P/AI in the 5 d timed AI protocol when cows had their estrous cycle presynchroni zed with the Presynch, but not the DO.

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21 CHAPTER 1 INTRODUCTION Economics of the dairy industry in United States (US) has encouraged some producers to pursue methods of production that incur in low costs and inputs, which has generated a renewed interest i n pasture based systems. Seasonal production is a strategy often used in grazing farms to simplify management and to match calving and breeding periods to better climatic conditions and forage quality and availability. For seasonal dairy production, a conc entrate d calving pattern on a yearly basis is required and, therefore, reproductive efficiency becomes extremely important. As oppose d to high producing cows in confinement, prolonged breeding period is not feasible as production in grazing cows is less an d lactation persistence is not sufficient to keep them productive with advanced lactation. Furthermore, in many cases in seasonal grazing, cows have a pre defined dry date that is not always based on stage of gestation, but on calendar da te Therefore ina bility to become pregnant i n a timely manner markedly compromises production because lactation is interrupted early (McDougall, 2006). As in high producing cows those that do not become pregnant have increased risk of culling late in lactation, which nega tively impacts profitability. Moreover, a cow that become s pregnant at the end of the breeding season consequently calve late in the following calving season, which limits the interval to reestablish energy balance and estrous cyclicity, thus compromising reproduction in the subsequent breeding season (McDougall and Compton, 2006). In order to achieve adequate reproductive performance in grazing dairy cows a high submission rate and pregnancy per artificial insemination (P/AI) are essential (Morton, 2010). Although estrous detection is typically high for grazing dairy cows,

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22 approximately 20% (13 to 48%) remain anovular at the beginning of the breeding season, limiting submission to AI and compromising fertility of those inseminated (Rhodes et al., 2003). Ti med AI programs are, therefore, a reasonable technology to increase insemination early in the breeding period, which should favor pregnancy when it is more profitable for seasonally calving herds. Also, timed AI programs often incorporate the use of gonado tropin releasing hormone (GnRH), which is known to induce ovulation in a high percentage of anovular cows (Gmen et al., 2003), thereby restricting the length of the anovular period in dairy cows. These programs have been used more extensively for first po stpartum insemination of cows not detected in spontaneous estrus before the planned starting of breeding (McDougall and Compton, 2006; McDougall, 2010). Synchronizing estrus (McDougall and Compton, 2006) or ovulation (McDougall, 2010) in these cows results in improvements in reproductive efficiency, and these benefits translate in economic advantages to the producer regardless of estrous cyclic status of the cows (McDougall, 2010). Therefore, ensuring that all cows are inseminated early in the breeding seas on and with high fertility at that insemination is critical to success ful reproductive management of grazing dairy cows with seasonal calving. Although the use of timed AI programs benefits anovular cows by maximizing insemination rates, these cows still h ave smaller P/AI, greater risk of pregnancy loss, slower pregnancy rate, longer interval to pregnancy, and greater risk of culling compared with their cyclic counterparts (Rhodes et al., 2003; McNaughton et al., 2007). Thus, development of timed AI protoco ls that not only secure insemination, but also improve fertility is expected to benefit profitability in grazing farms The low

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23 concentrations of progesterone during the development of the ovulatory follicle in anovular cows seem to be a major reason for t he depression in fertility (Bisinotto et al., 2010). Low endogenous concentrations of progesterone allow greater luteinizing hormone (LH) pulsatility, which might compromise oocyte maturation by altering the composition of the follicular fluid (Cerri et al ., 2011), and advancing oocyte maturation by inducing premature resumption of the second meiotic division (Revah and Butler, 1996). Additionally, cows that develop the ovulatory follicle under low concentrations of progesterone have increased uterine prost aglandin (PG) release in the next estrous cycle (Shaham Albalancy et al., 2001; Cerri et al., 2011) by altering endometrial luteolytic signals, which increases the frequency of short luteal phases (Cerri et al., 2011) and short inter AI intervals (Bisinot to et al. 2010a). Programs that induce cows to ovulate a nd be in early diestrus at enro l l ment in timed AI protocols promote greater incidence of follicle turnover when GnRH is administered at the beginning of the timed AI, induce the ovulatory follicle to develop under high concentrations of progesterone, and prevent premature luteolysis before planned insemination (Moreira et al., 2001; Galvo et al., 2007). Inclusion of GnRH in presynchronization programs might benefit preferentially anovular cows as it i nduces ovulation in more than 80% of the anovular cows (Gmen et al., 2003) and cows without a corpus luteum ( CL ; Galvo et al., 2007). Presynchronization with PGF improves fertility of dairy cows (Moreira et al., 2001; El Zarkouny et al., 2004; Navanukr aw et al., 2004), particularly estrous cyclic cows, but no program has been developed and clearly demonstrated to differentially influence fertility of anovular cows.

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24 Timed AI programs that achieve high P/AI associated with maximized service rates are lik ely to improve profitability in seasonal grazing farms The 5 d timed AI program has been designed to reduce the period of follicle dominance and improve P/AI in dairy heifers (Rabaglino et al., 2010), dairy cows (Santos et al., 2010a), and beef cows (Brid ges et al., 2008) compared with programs of 7 d between follicle recruitment and induction of luteolysis. Although this program requires handling of cows o n more days of the week, it improves P/AI in dairy cows (Santos et al., 2010a), and might be a very a ttractive alternative to maximize fertility in dairy production systems in which cows are inseminated only once or twice such as when a breeding season is implemented. The response to this program might vary with different types of presynchronization schem es, supplementation of progesterone, or alternative strategies to induce luteol ysis of an early CL. Improvements in nutrition, health, genetic selection, and increased consciousness of the producers on how to manage dairy cows constitute important pillars for success of a reproductive program (Norman et al., 2009). Cows experiencing extensive loss of body condition (BCS, body condition score), diseases or metabolic problems in early lactation are more likely to have extended periods of anovulation and impa ired reproduction (Rhodes et al., 2003; Chagas et al., 2007; Santos et al., 2009; Santos et al., 2010b). These events are all associated with negative nutrient balance, often expressed as negative energy balance (NEB). Energy balance is determined primaril y by energy intake (Santos et al., 2010b) and, therefore, constitutes a greater challenge in grazing farms with limited feed availability and nutrient supply, especially when the

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25 genetics of the cow favor increased partition of nutrients for production at the cost of body reserves (Bauman and Currie, 1980). confinement, and intensive postpartum health programs are not common in grazing farms Nonetheless, little is known of the epi demiology of periparturient and metabolic disorders in US grazing farms. Likely, the lower production of these cows, the perception of cows being healthier and the use of less intensive production practices in grazing farms preclude full characterization of the epidemiology of diseases because of lack of diagnosis. Nevertheless, incidence of diseases in grazing dairy farms is known to compromise fertility and production, which negatively affects profitability (McDougall et al., 2001a, 2001b). Therefore, th ere is a need to further characterize health and metabolic status of postpartum dairy cows in under seasonal grazing and their impact on reproductive performance in US dairy farms. C hapter 2 reviews important physiological events and health disorders occu rring during the transition period, the reproductive physiology of dairy cows, and important features of dairy production under seasonal grazing with emphasis on the reproductive management. Chapters 3 to 6 refers to original research developed for this Ma ster of Science program. Chapter 3 describes the incidence of postpartum diseases and their impact on reproduction on seasonal grazing farms. In Chapter 4, a study was designed to compare the efficacy of presynchronization against supplementation of proges terone during the 5 d timed AI protocol, as well as two luteolytic strategies for these programs. The study in Chapter 5 was designed to compare two methods of presynchronization and two of resynchronization of return to estrus on reproductive performance of grazing

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26 dairy cows during a 100 d breeding season. The study in Chapter 6 evaluated two methods of presynchronization of the estrous cycle associated with changes in the length of proestrus on fertility of grazing dairy cows inseminated following the 5 d timed AI protocol. F inally, Chapter 7 addresses general conclusions and implications from the research developed.

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27 CHAPTER 2 LITERATURE REVIEW The Transition Period The transition period from a pregnant nonlactating to a nonpregnant lactating animal typ ically comprises the interval between 3 weeks before to 3 weeks after calving (Grummer, 1995), when the cow is most susceptible to diseases (Drackley, 1999). The rapid fetal growth in the last weeks of gestation associated with the onset of colostrogenesis prepartum and of lactation postpartum dramaticall y increase the nutrient needs of t he cow (Bell, 1995). Conversely feed intake is reduced in the last two weeks of gestation likely because of endocrine, metabolic and behavioral reasons (Bell, 1995) Altho ugh the requirement for nutrients at the end of gestation is approximately 75% greater than that of a nonlactating nonpregnant cow, it increases 4 fold with the onset of lactation posing challenges for metabolic regulation to cope with drastic increases i n nutrient demands (Bauman and Currie, 1980; Grummer, 1995). Although feed intake is normally ascending after parturition (Bauman and Currie, 1980; Bell, 1995; Grummer, 1995). Additionally, following homeostatic and h omeorrhetic regulations for sustainability of essential physiological processes, glucose in dairy cows is preserved to be preferentially used by the mammary gland to synthesize lactose that drives milk production. It is estimated that glucose uptake by the mammary gland can account for up to 85% of glucose entering in blood circulation of a high producing dairy cow (Zhao and Keating, 2007). This homeorrhetic regulation prioritize nutrient partition to support lactation at the expense of body reserves (Bauma n and Currie, 1980). Genetic selection for productive traits over the years further developed this evolutionary mechanism of nutrient partition ing in dairy

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28 cows (Bonczek et al., 1988). Data presented by Bell (1995) and discussed by Drackley (1999) shows th at the requirements for calories as net energy of lactation (NE L ) and metabolizable protein of a lactating cow at 4 days postpartum exceed s intake by 26 and 25% respectively, and that utilization by the mammary gland represents 97 and 83% of the intake res pectively. As a consequence of these events, most dairy cows during the transition period experience NEB, negative net metabolizable protein balance, mobilization of body reserves and loss of BCS, which occur concurrent with metabolic and hormonal adaptati ons coordinated by tissue specific responses. Homeorrhetic controls induce metabolic changes that include decreased glycogenesis and increased gluconeogenesis and glycogenolysis in the liver; decreased lipogenesis and increased lipolysis in adipose tissue ; and increased mobilization of protein reserves from muscle tissue (Bauman and Currie, 1980). Reductions in DMI result in a decrease of blood glucose concentrations and, consequently, hypoinsulinaemia, which associated with high systemic concentrations of catecholamines and glucocorticoids present during transition period, stimulate hormone sensitive lipases in adipose tissue to mobilize fatty acids (Drackley, 1999; Fukao et al., 2004). This process results in the release of nonesterified fatty acids (NEFA ) in blood circulation, which are mainly taken up by the mammary gland However, the liver also uses NEFA for its own energetic needs by oxidizing them for synthesis of adenosi ne tri phosphate (ATP ). Nonetheless, w hen excessive amounts are taken up by the hepatocytes, a portion of these fatty are then esterified and stored as triacylglycerol, or hydroxybutyrate (BHBA) to be

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29 use d by peripheral tissues as an alternative energy source (Drackley, 1999; F ukao et al., 2004). Oxidation of fatty acids occurs in the m itochondria, but when excess fatty acids oxidation takes on an increased role to dispose of the excess of carbon entering the liver. Therefore, peroxissomes become an important organelle for NEFA metabolism in the liver, working especially as an controlled by the energy needs of the cell as in mitochondria (Drackley, 1999 ). It also is important to mention that ruminants are not efficient in export ing fatty acids from the liver as triacylglycerols in very low density lipo protein (VLDL ). This is likely due to the liver not being a lipogenic tissue in ruminants and possibly b ecause of inability to synthesize large amounts of apolipoprotein B for synthesis of VLDL (Gruffat et al., 1997). Glucose is the sole precursor for lactose synthesis in the mammary epithelial cells (Zhao and Keating, 2007). Thus, in order to synthesize mi lk during NEB, most cows experience uncoupling of the somatotrophic axis and insulin resistance. The concentration of growth hormone (GH) in plasma increases during the periparturient period (Bell, 1995). However, probably as result of low insulin concentr ations, the hepatocytes express little GH receptor 1A at this period, decreasing secretion of insulin like growth factor 1 (IGF 1), thereby breaking the feedback loop for GH secretion (Lucy et al., 2001). These processes further stimulate lipolysis to supp ort the demands of the mammary gland for fatty acids for milk synthesis. The high plasma concentrations of NEFA and GH induce a state of insulin resistance in insulin dependent tissues such as

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30 the adipose tissue (Lucy et al., 2001; Hayirli, 2006) which as sociated with the low concentrations of insulin and IGF 1 further decrease glucose uptake by non mammary cells. This mechanism supplies precursors for gluconeogenesis and secures glucose for milk synthesis in the mammary gland, a tissue known to utilize g lucose by non insulin dependent manners (Zhao and Keating, 2007). Although the state of NEB is more pronounced in the first two weeks postpartum, it may last several weeks and mainly depend s on the ability of the cow to restore adequate DMI (Santos et al., 2010b). Maximizing nutrient intake postpartum through adequate nutritional management is essential for dairy cows to minimize the degree and duration of NEB. Diets with high caloric density and those so called glucogenic diets can be used as an alternativ e to maximize caloric intake and stimulate gluconeogenesis during periods of NEB. However, diets with excessive concentrations of ruminally fermentable carbohydrate can also inhibit feed intake, especially by affecting satiety of cows (Allen et al., 2009). According to the hepatic oxidation theory, those diets may result in increased flux of propionate though the hepatic portal blood system that increases oxidation and ATP formation in hepatocytes. These events are supposed to decrease the firing rate of th e vagal afferent nerve fibers signaling the hypothalamic feeding centers to reach satiety and end a meal. It has been suggested that such mechanism s may be potentiated by fatty acid oxidation in the liver, in which propionate may enhance complete oxidation of acetyl CoA rather than exporting as ketones, further increasing the production of ATP and inhibiting intake (Allen et al., 2009). Feeding nutrient dense prepartum diets normally increases prepartum DMI, but it can also induce greater declines in intak e immediately prepartum, thereby enhancing fat

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31 mobilization and NEFA concentrations in blood in the week before and after calving (Dann et al., 2006). On the other hand, cows fed low energy, high fiber diets have increased rumen fill and limited intake pre partum, which minimizes the drop in DMI immediately before calving. This is thought to reduce the supply of NEFA for hepatic oxidation, which might potentially have benefits to cow health (Allen et al., 2009; Janovick and Drackley, 2010). Nevertheless, pre partum diets that restrict nutrient intake such as those high in fiber often compromise milk production in early lactation (Janovick and Drackley, 2010; Silva del Rio et al., 2010). Therefore, diet formulation prepartum requires a balance between optimizin g early lactation milk production and minimizing excessive mobilization of body reserves that predispose cows to ketosis and fatty liver. Monitoring BCS is an important tool for diet formulation and management of dairy cows. Overconditioned cows usually ha ve exacerbated reduction in DMI prepartum, increased fat mobilization and loss of BCS postpartum, and increased risk of periparturient diseases. These events have profound negative impacts on future reproductive performance as exacerbated mobilization of b ody reserves postpartum result in delayed resumption of estrous cyclicity smaller P/AI and greater incidence pregnancy losses (Chagas et al., 2007; Santos et al., 2009). Although the mentality has been changed in the last years (LeBlanc et al., 2006), man y producers still neglect the importance of management and comfort of dry cows, dealing with postpartum problems as unavoidable situations. Although not always documented, common sense tells that proper management during transition period minimizes metabol ic and health problems and is essential to maximize production and profitability. In addition to poorer reproductive performance, cows failing to adapt to these metabolic challenges do not

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32 achieve their potential for peak milk production, which normally co mpromise production in the entire lactation (Drackley, 1999). In addition to the dramatic increase in caloric requirements, colostrum and milk syntheses substantially increase the needs for Ca. Colostrum synthesis results in a drain of Ca that might repres ent 8 to 10 times the total blood pool in a dairy cow (Horst et al., 1997). Therefore, mobilization of Ca from bones, which is the major reservoir of Ca in the body is extremely important to maintain the Ca homeostasis peripartum. To maintain Ca homeostasi s, diets prepartum are manipulated to result in a negative cation anion difference. These diets induce a mild metabolic acidosis that enhance bone remodeling and Ca mobilization (Charbonneau et al., 2006). It is thought that mild metabolic acidosis enhance s the affinity of the parathyroid hormone to its receptor in target tissues, thereby improving Ca resorption from bones and intestinal absorption of dietary Ca (Goff et al., 1991; Charbonneau et al., 2006). These diets are effective in preventing clinical and subclinical hypocalcemia, but often are not indicated for primigravid cows because of further depression in DMI (Moore et al., 2000). Others macrominerals such as P and Mg are also important for Ca homeostasis as they participate in the transduction si gnaling of parathyroid hormone (Mg), or in the synthesis of active vitamin D (P) (Goff, 2004). Periparturient Diseases and Disorders It is unquestionable that the transition period is critical for health and survival of dairy cows. Of all the cows that lea ve a dairy farm because of culling or death, almost 12% do so in the first 3 weeks postpartum, and 24% in the first 2 months of lactation (Godden et al., 2003). These cows represent a major economic loss to the producer as culling and death in early lactat ion compromises lifetime milk production of a cow.

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33 Delivery of a calf with consequent risks for dystocia and uterine diseases, peripartum immune suppression, changes in DMI, nutrient imbalance, inability to cope with stressors around parturition, and conta minated environment are major risk factors leading to the occurrence of health problems in this period, which in their totality have a multifactorial nature. The most common problems include uterine diseases such as retained fetal membranes, metritis and e ndometritis, disorders of mine ral metabolism such as hypocalc emia, hypomagnesemia and hypophosphatemia, disorders of the intermediary metabolism such as ketosis and hepatic lipidosis, digestive and respiratory problems, and lameness. The severity of these diseases varies, but they further exacerbate reduction in appetite, thereby further compromising the state of NEB. The opposite is also true as NEB exacerbates, the susceptibility to diseases increase. Taken together, they constitute a vicious cycle that c ompromises lactation and reproductive performance, increase veterinary costs, and reduce profitability (Drackley, 1999; Santos et al., 2010b). The liver has a fundamental role for all physiological adaptations occurring during the transition period. Nonet heless, excessive fat mobilization may result in excessive triglyceride accumulation in the liver and d evelopment of hepatic lipidosis, which compromises hepatocyte function, decreas ing ureagenesis and gluconeogenesis. As the capacity of triglyceride stora ge is exceeded and NEFA oxidation is compromised, incomplete oxidation of NEFA increases and consequently ketone bodies are accumulated in plasma circulation characterizing ketosis (Grummer, 1995; Drackley, 1999). In principle, ketone formation is an impor tant metabolic adaptation to supply energy substrates for the mammary gland and non mammary tissues, especially

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34 essential organs such as brain and hearth. However, excessive concentrations of ketones can induce keto acidosis and compromise health. The cl inical presentation of ketosis are signs of systemic illness, with hypoglycemia, no appetite and neurological symptoms resulting from low glucose flux to neurons in the brain. On the other hand, the subclinical disease is characterized by high concentratio but with associated reductions in production and reproduction. It is estimate d that 50% of all dairy cows experience a temporary period of subclinical ketosis within the first month postpartum (Wathes et al., 2007). Subclinical ketosis in either the first or second week postpartum was associated with a reduction in the probability of pregnancy by 20% after first service, and with reduced pregnancy rate throughout the lactation (Walsh et al., 2007a). Calcium in its ionized form is part of many cell signaling pathways, required for normal muscle contraction, neuronal communication, and immune function (Kimura et al., 2006; Goff, 2008). Inability to maintain Ca homeostasis immediate post partum may cause cl inical and subclinical hypocalc emia. Clinical hypocalcemia or milk fever results in inability to sustain muscle tone which induces downer cows and is a major risk for death because of cardiac arrest if not promptly treated (Goff, 2004). Clinical signs are normally observed when Ca concentrations are less than 5.0 mg/dL. Normal Ca concentrations range between 8.5 and 10.0 mg/dL, whereas concentrations between 5.5 and 8.0 mg/dL ch aracterize subclinical hypocalc emia (Goff, 2008). Reinhardt e t al. (2010) reported that the incidence of cl inical and subclinical hypocalc emia was 6.2% and 47% for multiparous cows and 1% and 25% for primiparous cows, respectively.

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35 Interesting, in the same study authors reported higher NEFA concen trations for cows w ith hypocalc emia than those normocalcemic, suggesting a relationship between Ca homeostasis and energy balance. The s ubclinical disease is also associated with reduced feed intake, poor rumen and intestin al motility, poor productivity, and increases suscep tibility to dystocia, retained fetal membranes and metritis, displacement of the abomasum, and mastitis (Goff, 2008). The immune suppression observed during the periparturient period (Kehrli et al., 1989) is not completely understood, but recent studies h ave drawn attention to new insights regarding the relationships between immune cell function and periparturient metabolic adaptations and diseases. Studies have demonstrated that cows developing metritis have greater concentrations of NEFA and BHBA in plas ma before calving, and these metabolites have been associated with decreased neutrophil activity (Grinberg et al., 2006; Hammon et al., 2006). Because immune cell s also require ATP NEB could compromise their activity by limiting nutrient uptake In fact, Galvo and co authors (2010) demonstrated that blood neutrophils from cows developing metritis and subclinical endometritis had less glycogen content than those from healthy cows. Additionally, Kimura et al. (2006) demonstrated that the store of intracellu lar Ca +2 and activation of peripheral mononuclear cells decreased in periparturient cows developing clinical hypocalcemia Collectively, these findings suggest that low Ca concentrations in serum during the peripartum may also contribute to immune suppress ion. Interestingly, cows with low serum Ca concentrations had reduced neutrophil oxidative burst and increased risk of metritis than cows that were able to maintain serum Ca concentrations > 8.5 9 mg/dL during the first week postpartum (Martinez et al., 201 1 ). Therefore,

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36 inability to cope with caloric and macromineral needs in late gestation and early lactation might negatively affect immune cell function, thereby predisposing cows to metabolic and infectious diseases. One cannot neglect that flux of immune cells and immunoglobulins to the mammary gland and uterus immediately after calving is very high, which might contribute to the state of immune suppression of postpartum dairy cows. The uterus during gestation is considered sterile, unless viral or hematog enous bacterial infections occur. Upon parturition however, the cervix opens and allows contamination from the vagina to enter the uterus, which affects almost all cows (Griffin et al., 1974). Large uterus, presence of lochia and remnants of fetal membran es, and necrotic material favor bacterial proliferation. Thus, besides proper physical clearance of the uterus by uterine contractions, t he development of uterine diseases depends o n the ability of the local immune system to control bacterial growth. Metri tis affects up to 40% of the cows and occurs in the first 21 days postpartum, but it is more common within 10 days postpartum ( Sheldon et al., 2009). It is characterized by an enlarged uterus with watery brow red vaginal discharge of fetid odor ( Sheldon et al., 2006). Fever and anorexia are also present in approximately half of cows affected. Calving problems such as dystocia, retention of fetal membranes, abortion, stillbirth, and twins are key predisposing factors, but also low prepartum DMI, NEB, and inc reased acute phase response have all been associated with increased risk of metritis (Correa et al., 1993; Kaneene and Miller, 1995; Huzzey et al., 2007; Dubuc et al., 2010a). It is estimated that milk production is reduce d 259 kg per lactation in multipar ous cows affected by metritis

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37 (Dubuc et al., 2011), and the annual cost as result of the disease would be approximately $650 million only in the US ( Sheldon et al., 2009). Clinical endometritis is characterized by mucopurulent or purulent vaginal discharg e after 21 days postpartum ( Sheldon et al., 2006). Recently, Dubuc et al. (2010b) suggested a different nomenclature for this presentation, suggesting purulent vaginal discharge (PVD) because a large portion of the cows with this clinical sign did not pres ent cytological inflammation of uterus. The presence of inflammatory cells in endometrial cytology, usually greater than 5 to 10% neutrophils of all cells in the smear, and absence of clinical signs characterizes subclinical endometritis ( Sheldon et al., 2 006). According to Dubuc et al. (2010a), the risk factors for PVD include twinning, dystocia, metritis, and increased haptoglobin concentrations in the first week postpartum, whereas for subclinical endometritis low BCS at calving ketosis and haptoglobin were identified. Effects of endometritis are localized to the reproductive tract and do not affect milk production (Dubuc et al., 2010b). Nonetheless, both PVD and subclinical endometritis reduce reproductive performance, having additive detrimental impact s on reproduction (Dubuc et al., 2010b). Moreover, endometritis has been associated with disturbed luteolysis and with reduction of steroidogenic capacity of follicular and luteal cells, resulting in reduced concentrations of estradiol during the follicula r phase and of progesterone during the luteal phase of the estrous cycle (Sheldon et al., 2009). The postpartum period also involves drastic changes in the uterine morphology and physiology. Uterine involution, including return to size, tone and position of a nonpregnant uterus elimination of bacterial infections, vascular remodeling, and

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38 restoration of epithelium and physiological activity of the endometrium are major events needed before a new pregnancy can occur (Archbald et al., 1972; Kiracofe, 1980; Gray et al., 2003; Wathes et al., 2007, 2011). Involution combine s a series of degenerative and regenerative events in which uterine health is extremely important. Additionally, cows undergoing severe NEB have increased inflammatory response of the endomet rium by the second week postpartum and differential gene expression, which has been suggested as indicative of compromised tissue remodeling and immune response (Wathes et al., 2007, 2011). Steroid hormones, somatotropin and local regulatory proteins seem to regulate endometrial immunity postpartum ( Sheldon et al., 2009). As discussed before, energy and macromineral imbalance may also affect immune function and increase susceptibility to uterine diseases. However, it is important to rem ember that whole anim al studies that present an evidence for links between immune cell function and uterine disease used circulating blood cells, which differ from the population of immune cells present in the uterus during pregnancy (Oliveira et al 2010). Nonetheless, those experiments are supported by strong epidemiological evidence of links between immune status and diseases, making it plausible to suggest that reductions in function of circulating blood cells around parturition likely represent similar reductions of local ized cells in the uterus responsible for the local defense mechanisms. In high producing dairy cows, incidence of periparturient diseases have been linked with depression in reproduction (Santos et al., 2010b). Epidemiology of diseases from 5,719 cows in 7 dairy farms in the US resulted in 14.6% of the cows diagnosed with calving problems, 16.1% with metritis, 20.8% with clinical endometritis, 21.0% with

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39 fever, 12.2% with mastitis, 10.4% with clinical ketosis, 6.8% with lameness, 2.87% with digestive proble ms, and 2.0% with pneumonia in the first 60 days postpartum. Of all cows, morbidity was 44.2%, and 27.0% presented a single clinical case, whereas 17.2% had two or more cases of disease. The incidence of diseases did not affect milk production for the enti re lactation (~11,000kg). However, estrous cyclicity at 65 d postpartum, P/AI, and pregnancy loss were all affected by diseases. Resumption of estrous cyclicity was mostly affected by uterine diseases, whereas P/AI and pregnancy loss suffered negative effe cts from almost all diseases evaluated. These data clearly demonstrate the importance of postpartum health for reproductive performance of high producing dairy cows. Postpartum Anovulation and Resumption of Estrous Cyclicity Estrous cyclicity is interrupte d with the establishment of pregnancy, although growth of follicle s in a wave like pattern is still present in the ovaries throughout gestation. Nevertheless, elevated concentrations of estradiol during the last months of gestation cause a strong negative feedback on the hypothalamus and it result in minimal secretion of follicle stimulating hormone (FSH) and follicle development at the end of gestation (Ginther et al., 1996a). After parturition however, steroid hormone concentrations sharply decline and mo st cows exhibit FSH pulsatility around day 4 (2 to 7) postpartum followed by the development of the first wave if follicle development (Ginther et al., 1996a). However, only approximately 45% of the cows ovulate the follicle of the first wave, which occurs around day 20 postpartum (Beam and Butler, 1997). The remaining cows fail to ovulate and are classified as anovular cows, with two possible fates: approximately 35% regress the dominant follicle and develop a new follicle wave that may or may not ovulate; and 20% develop a first dominant follicle of large size that

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40 do not ovulate and stay on the ovary for undetermined time and are classified as cystic cows (Beam and Butler, 1997). A third outcome was described (Wiltbank et al., 2002) for cows in extreme un dernutrition where growth of follicles is limited to sizes smaller than the deviation size, also called inactive ovaries. In most postpartum dairy cows, the anovulatory state is characterized by development of follicles past the deviation stage with diamet ers of 15 to 24 mm (Gumen et al., 2003). These cows developing multiple anovulatory follicular waves with dominant follicles with reduced steroidogenic capacity that are unable to trigger a GnRH and LH surge to induce ovulation (Beam and Butler, 1997). Thi s condition is directly associated with energy balance and uncoupling of the somatotrophic axis during peripartum (Beam and Buttler, 1999; Butler, 2003). Impaired follicular steroidogenesis during periods of NEB seems to be caused by low concentrations of insulin and IGF 1 postpartum (Butler et al., 2004). When cows in NEB were exposed to an euglycemic/hyperinsulinemic clamp, hepatic expression of GH receptor 1A and IGF 1 increased, which resulted in greater concentrations of plasma IGF 1 suggesting recoupl ing of somatotrophic axis (Butler et al., 2003; Butler et al., 2004; Rhoads et al., 2004). In fact, these cows had increased concentrations of estradiol after supplementation with insulin (Butler et al. 2004). These beneficial changes do not seem to be as sociated with changes in GnRH/LH release (Gong et al., 2002; Butler et al., 2004) and are not likely mediated by uptake of glucose as the main glucose transporters on follicular cells are insulin independent (Nishimoto et al., 2006). Indeed, IGF 1 seems to be essential for adequate expression of steroidogenic enzymes and estradiol production by granulosa cells and, therefore, the benefits seem to be localized in the follicle with increased steroidogenesis (Diskin et al., 2003; Butler et al.,

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41 2004). Addition ally, insulin and IGF 1 induce cell proliferation and expression of LH receptors, and improve responsiveness to LH, which are essential for follicle development, transition from FSH dependent to LH dependent, and oocyte maturation (Lucy, 2000; Webb et al., 2004). Energy balance may also control resumption of estrous cyclicity by directly affecting the secretion of GnRH by the hypothalamus. Central neurological control of reproduction and feed intake shares metabolic sensory stimuli, hormonal mediators and modulators (Schneider, 2004). Both centers respond according to availability of oxidizable metabolic fuels and the main effect on reproduction would be through the pulsatile secretion pattern of GnRH release. Oftentimes they have opposite effects, in which neuropeptides that stimulate feed intake inhibit reproduction and vice versa. Thus, deficit of oxidizable metabolic fuels would inhibit the hypothalamic GnRH pulse generator and, consequently, pituitary gonadotropin secretion and follicle development an/o r ovulation (Schneider, 2004). In fact, undernutrition has been linked to inability of the hypothalamus to sustain high frequency of LH pulses (Schillo, 1992), and anestrus can be induced in pubertal heifers by imposing loss of 22 24% of their initial body weight (Diskin et al., 2003). Peripheral tissues also participate in the control of reproduction by signaling the brain about availability of nutrients trough metabolic and hormonal cues. For instance, influx of fuels stimulate secretion of insulin, lept in and cholecystokinin, by the pancreas, adipose tissue and intestine, respectively; or inhibit ghrelin secretion by the gut, and all these hormonal changes are involved in the hormonal control of hypothalamic secretion of GnRH (Schneider, 2004). In cattle opioid peptides, neuropeptide Y and glucose have

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42 been described as regulators of GnRH release (Diskin et al., 2003). From an evolutionary perspective, it might be a mechanism to ensure survival under nutritionally challenging conditions, at the same time that it might optimize reproductive success under nutrient abundance (Schneider, 2004). Animals have the ability to partition available metabolic fuels according to priorities, in which individual survival is paramount, and reproduction as well as fat sto rage is considered as expendable processes, at the bottom of the priority scale under nutritionally challenging times (Wade and Jones, 2004). In general, prioritization is given to physiological processes that are essential to survival and cannot be compr omised, such as cell maintenance, circulation, neural activity, followed by reducible processes such as thermoregulation, growth, lactation (Wade and Jones, 2004). Thus, especially for postpartum females, reproduction receives a very low priority for nutri ent utilization, and adaptive mechanism secure well being and survival of the dam and her born offspring. Under these premises, a new attempt to reproduce will only be successful when the animal has sufficient oxidizable fuels above and beyond the needs fo r essential and reducible processes. Because of the priorities for nutrient partition, resumption of ovulation var ies among individual cows and it is directly associated with energy status, and reestablishment of ovulatory cycles normally occurs after the nadir of NEB (Butler, 2003). It is important to mention that prevalence of anovular cows is not associated with milk production (Santos et al., 2009), which is basically explained by the fact that energy balance is more influenced by energy intake (r 2 = 0 .57) than by energy secreted in milk (r 2 = 0.07; Santos et al., 2010b). Comparisons among different herds may even find a

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43 positive association between production and resumption of ovulation postpartum, in which herds that produce more milk might have bett er management that minimize the degree of NEB in postpartum cows. This evidence reinforces the importance of adequate management during the transition period to maximiz e DMI and minimize the risk of diseases. Early resumption of estrous cyclicity is desira ble because it improves fertility (Thatcher and Wilcox, 1973; Butler, 2003) and anovulation at the end of the voluntary waiting period decrease s P/AI (Santos et al., 2009) and increase s the risk of pregnancy loss (Santos et al., 2004), thereby extending th e interval to pregnancy (Walsh et al., 2007b). Oocyte and Follicle Development: From Primordial Germ Cell to Antral Follicles Primordial germ cells (PGCs) are the founder cells for the germline in animals (Seydoux and Braun, 2006). Mammalian germline speci fication occurs through inductive signaling from extraembryonic ectoderm during gastrulation, in which primordial germ cells arise from the epiblast (Seydoux and Braun, 2006; Nicholas et al., 2009). The PGCs migrate by amoeboid movement via the dorsal mese ntery of the hindgut to the gonadal ridge (Nicholas et al., 2009). The g onadal ridge is formed by proliferation of celomic epithelium and condensation of surrounding mesenchymal cells around days 28 to 32 of gestation in the bovine (Aerts and Bols, 2010). The migration of PGCs usually occurs between days 30 and 64 of gestation in cattle (Erickson, 1966; Aerts and Bols, 2010). Chemotaxis signaling produced by gonadal ridge including kit ligan d and integrins, and growth factors produced by germ cells, especia lly those of the BMP family seem to coordinate the migration process (Dudley et al., 2007). During migration and upon arriving on the gonadal ridge, PGCs underwent limit number of mitotic divisions, which are ceased after internalization to the gonadal rid ge (Adams et al., 2008). Upon

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44 colonization of the gonadal ridge, PGCs undergo remarkable changes in genome methylation and chromatin structure, which is considered the most widespread and complete demethylation process in mammalian development (Bowles and Koopman, 2010). Additionally, they interact with gonadal somatic cells that determine their sex specific commitment based on gonadal environment (Bowles and Koopman, 2010). Retinoic acid is a meiotic induction signal secreted by neighboring somatic cells i n both sex, which in the case of the fetal ovary it is able to induce the expression of Stra 8 and subsequent meiotic entry by the PGC and, consequently the oocyte fate. In contrast in the case of the fetal testis, secretion of additional factors such as CYP26 inhibit the expression of Stra 8 and the entry in meiosis division, arresting PGC in mitosis, G0/G1 stage of cell cycle and determining the sperm fate. Germ cells committed to the oocyte fate in the fetal ovary are termed oogonia, and are primarily located in germ cell cords composed by epithelial cells, delineated by basal membrane and surrounded by mesenchymal cells (Adams et al., 2008). Cluster of oogonia are formed at this time and are surrounded by pre granulosa cells, wh ose differentiation from somatic cells seems to be induced by the presence of the oogonia (Trombly et al., 2009). Mitotic divisions within clusters occur synchronously, but with incomplete cytoplasmic division, resulting in formation of interconnection bridges among the now calle d secondary oogonias (Aerts and Bols, 2010). After successive mitotic divisions, secondary oogonias enter meiotic division, progressing until diplotene stage of meiotic prophase I and forming the primary oocytes, which are arrested at this stage of the cel l cycle until few hours before ovulation, when then the cell cycle is resumed. Chromosomes during this time are decondensed and contained within the germinal

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45 vesicle. Nevertheless, development of primordial follicles seems to be required for progression of the first meiotic prophase until diplotene stage (Yang and Fortune, 2008). Oogonia l cluster breakdown allow infiltration of granulosa cells and formation of primordial follicles. Breakdown occurs around day 90 of gestation in the bovine and seems to be as sociated with a decrease in estradiol production by the fetal ovary between gestation days 80 to 100 (Fortune et al., 2010). Therefore, fetal estradiol production works as intra ovarian signal to initiate follicle formation, acquisition of activation capac ity, and oocyte meiotic progress to diplotene stage (Fortune et al., 2010). Once follicles have acquired the ability to activate, the balance between inhibitory and stimulatory regulators in the surrounding environment determines their fate (Fortune et al ., 2010). At this point, primordial follicles constitute the ovarian reserve from which follicles are uninterruptedly recruited for development until ovary depletion (Aerts and Bols, 2010). Studies using in vitro models suggest that anti Mullerian hormone (AMH) secreted by granulosa cells of secondary and small antral follicles is an important inhibitor of follicle activation (Gigli et al., 2005; Fortune et al., 2010). On the other hand, insulin and kit ligand seem to be important regulators of follicle act ivation (Fortune et al., 2010). Some scientists also suggest that the avascular ovarian cortex limit the supply of nutrients and oxygen, which in turn would limit the activation process (Fortune et al., 2000; Cushman et al., 2002). The interval from the a ctivation of primordial follicles to the formation of preovulatory follicle is estimated to last 180 days, in which the majority of time would be spent in the pre antral stages (138 days), and less time in the antral stages (42 days;

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46 Lussier et al. 1987). Nevertheless, the global mechanism controlling the activation and recruitment of primordial follicles to continue development is still unclear. Follicular factors such as testosterone, fibroblast growth factor (FGF) 7 and vascular endothelium growth facto r (VEGF) seem to be important for early transition from primary follicle to small pre antral follicle (Fortune et al., 2010; Buratini and Price, 2011). Furthermore, pre antral development seems to occur independently of gonadotropins (Knight and Glister, 2 001), although FSH receptors are present in granulosa cells of primordial follicles in different species, suggesting a role of gonadotropins for early follicle development (Cortvrindt et al., 1997; Findlay and Drummond, 1999). The FSH dependency however, seems to begin with the antral formation, which is characterized by granulosa cells proliferation and formation of the antrum It generally occurs when follicles attain more than 250 granulosa cells and mark the development to resume meiotic competence by the oocyte (Aerts and Bols, 2010). McGee and Hsueh (2000) suggest that the majority of the primordial follicle population is maintained in a resting state and there would be two phases of follicle recruitment, initial and cyclic. The initial phase would be characterized by continuous recruitment of dormant primordial follicles throughout life which are then able to develop until antral stages. Then, at this stage and under gonadotropin stimulation, part of these follicles undergo to the cyclic recruitment a nd develop through antral follicle stages in a cyclic manner. In most females, 99% of the follicle population perishes and undergoes atresia throughout folliculogenesis. It is estimated that the maximum number of PGCs in the cow reaches 2,100,000 and it i s reduced to on average of 130,000 (14,000 to 250,000) healthy oocytes at birth (Erickson, 1966). Although controversy exist regarding the

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47 possibility of germ cell renewal of ovarian reserve in postnatal life (De Felici, 2010), the most widely held view is that the bovine is born with a finite number of primordial follicles in the ovaries (Fortune et al., 2010). There is high variation in ovarian size, ovarian reserve, and number of follicles recruited in each cyclic recruitment in the bovine (Ireland et al ., 2011). The same authors suggested that reduction in the ovarian reserve is associated with measures of infertility in cattle and number of follicles in the ovary might influence fertility (Ireland et al., 2011). In a study evaluating antral follicle cou nt of 12 month old heifers, the number of healthy oocytes ranged from 1,920 to 40,960 (Ireland et al., 2008), which demonstrate not only the high variability among individuals, but also exemplify the loss of almost 69 to 98% of the mean reserve number obse rved at birth (Erickson, 1966) in the first year of life. Maternal nutrition and incidence of diseases during pregnancy affect these p arameters, contributing to inherent variation between females (Ireland et al., 2011). Despite all the uncertainty about co ntrolling mechanism of follicle recruitment and pre antral development, it is well known that oogenesis and folliculogenesis during this time is a complex process tightly regulated by both endocrine and locally produced factors, including extensive cross t alk between the arrested meiotic oocyte and the granulosa cells (Nicholas et al., 2009). It has been demonstrated that the oocyte is able to direct the granulosa cells proliferation, differentiation and function, thereby coordinating folliculogenesis, wher eas granulosa cells would be responsible for regulating oocyte maturation and to carry out fundamental functions that oocytes cannot such glycolysis, cholesterol biosynthesis, and transport of amino acids (Eppig et al., 2002; Mermillod et al., 2008; Su et al., 2009). This cross talk is coordinated by oocyte

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48 derived paracrine factors such as growth differentiation factor (GDF) 9, BMP 15, and FGF 8b (Su et al., 2009). These factors are also responsible for the differentiation of granulosa cells into cumulus cells (Gilchrist, 2011). All these mechanisms of oocyte control of folliculogenesis are crucial for acquirement of its own development competence (Gilchrist, 2011). Aerts and Bols (2010) indicated that the oocyte has a 100 fold expansion in volume througho ut folliculogenesis, which is allowed by the block in cell division an d supported by follicular cells, a s opposite to others cells in which cell division is a homeostatic mechanism to maintain a nucleo cytoplasm ratio T he oocyte grow th without cell divisi on and accumulation of cytoplasmic molecules and organelles allow the early fertilized zygote to divide without expansion of its total volume Estrous Cycle and Antral Follicle Development When a heifer reaches puberty and has the first ovulation, a rhythm ic pattern of reproductive cyclicity is established, which is characterized by estrous cycles that terminate with sexual receptivity and ovulation, and thus provide repeated opportunities for establishment of pregnancy. The estrous cycle is governed mainly by ovarian steroids via neuroendocrine regulation of hypothalamus and pituitary, pituitary gonadotropins, and uterine PGF Changes in ovarian steroid concentrations influence the pattern of gonadotropin secretion that allow the development of follicles and ovulation of a competent oocyte, receptivity to mating and preparation of the uterus for pregnancy (Kimmins and MacLaren, 2001). The length of the estrous cycle in cattle ranges from 18 to 24 d ays and i s governed by the uterine PGF secret ion. The es trous cycle is divided into two major phases, follicular and luteal, that in turn can be subdivided in proestrus and estrus within the follicular phase, and metestrus and diestrus within the luteal phase (Peter et al.,

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49 2009). The follicular phase encompass es the period between CL regression and ovulation, and is characterized by a shift from progesterone to estrogen dominance. More specifically, proestrus is the early portion of the follicular phase between CL regression and initiation of sexual receptivity which in turn determines the onset of estrual phase that ends with the ovulation of the dominant follicle. The luteal phase is the period between ovulation and CL regression which encompasses metestrus and diestrus. The metestrus begins after ovulation, includes formation of CL and initiation of progesterone secretion. Diestrus in turn is when the CL matures, becomes responsive to PGF and sustains secretion of progesterone, ending with its demise during luteolysis. The development of ovarian follicles and corpora lutea and their secretion of steroid hormones are mainly driven by FSH and LH, which are glycoprotein hormones secreted o n blood by gonadotroph cells of the anterior lobe of the pituitary gland. Follicle stimulating hormone binds to its receptor in granulosa cells and is responsible for stimulating initial antral follicle growth and recruitment of a follicular wave, whereas LH binds to receptors in theca and granulosa cells and is responsible for development of selected large antral follicles and ovulation. Both induce steroidogenesis in the follicle, and preovulatory LH also stimulates luteinization of follicular cells, form ation of CL and secretion of progesterone. The secretion of FSH and LH in turn is stimulated by hypothalamic release of GnRH, and modulated by feedback controls from ovarian steroid hormones and inhibin at both the hypothalamus and pituitary levels. Synthe sis and secretion of GnRH occurs in GnRH neurons located in the preoptic chiasmatic area and arcuate nucleus of the hypothalamus. After synthesis, GnRH is stored in small

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50 vesicles and later secreted in a pulsatile fashion by the pulse generator terminals o f the neurons in the median eminence of the pituitary portal system. This system allows direct communication between the hypothalamus and the pituitary gland and, consequently, the immediate uptake of pictogram amounts of secreted hypothalamic hormones by gonadotrophs (Senger, 2003). The pattern of GnRH pulsatile secretion dictates how follicles develop, mature, and whether they ovulate or undergo atresia. Although secretion of GnRH is modulated by ovarian steroids, GnRH neurons do not express progesterone (Skinner et al., 2001) or estrogen receptor secretion occurs indirectly through intermediary neurons that possess the relevant steroid receptors and respond to their stimulation (Clarke and Pompo lo, 2005). These neurons act in the GnRH neurons through neurotransmitters that may have stimulatory (kisspeptin, dopamine and glutamine) and or inhibitory effects (aminobutyric acid, nitric oxide and opioids) on GnRH secretion (Clarke and Pompolo, 2005). Emerging evidence suggest s that steroid hormones can act directly on GnRH neurons through non classical membrane receptors (Kelly and Ronnekleiv, 2009), but control of GnRH secretion by this mechanism was yet not demonstrated. Both p rogesterone and estrog en inhibit GnRH secretion, with exception of unopposed elevation of estradiol that in this case causes a positive feedback on GnRH secretion (Clarke and Pompolo, 2005). Based on that concept basically two modes, a tonic and a surge pattern of GnRH secreti on have been described. During the luteal phase, high concentrations of progesterone secreted by a functional CL combined with low to moderate concentrations of estradiol maintains only the tonic mode, in which

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51 pulses of GnRH are released with low frequenc y and high amplitude. Nevertheless, during the follicular phase, high concentrations of estradiol secreted by the dominant follicle combined with low concentrations of progesterone caused by the demise of the CL stimulate the surge mode, in which pulses of GnRH are released with high frequency and low amplitude. The pulsatile pattern for LH secretion follows that of hypothalamic secretion of GnRH and, therefore when the surge mode of GnRH is stimulated, it also results in a LH surge. As example, LH pulse fr equency during the early luteal phase is 9 to 16 pulses every 24 h; in mid diestrus is 6 pulses every 24 h; and in proestrus is 14 to 24 pulses every 24 h (Aerts and Bols, 2010). The pattern of FSH secretion however, does not seem to be tightly coupled wit h GnRH secretion, although GnRH is necessary for its normal synthesis and secretion (Clarke and Pompolo, 2005). Negative feedback of estradiol and inhibin at the pituitary level seems to play major roles in modulation of FSH secretion. Inhibin is glycoprot ein hormone member of the transforming growth factor (TGF) cells, and its concentrations increase as follicles grow and is negatively correlated with FSH concentrations, similarly to estradiol (Bleach et al., 2001). The development of ultrasonography was central for the understanding and characterization of the patterns of follicle development in cattle It allowed the characterization of follicle growth in a wave like fashion, with the majority of cycles presenting 2 or 3 waves of growth, but only the last wave resulting in ovulation (Senger, 2003). In high producing dairy cows, the length of the estrous cycle was described as averaging 23 days, with 79% of the cycles having two waves of follicle growth (Sartori et al., 2004). The emergence of follicle waves is always preceded by a transient rise in

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52 circulating concentrations of FSH, which in turn induces recruits a cohort of small antral follicles (Adams et al., 1992). The FSH surge determines the development of the firs t follicle wave of the estrous cycle and it is observed approximately 28 h after onset of estrus (Adams et al., 1992). The peak in FSH occurs 0.7 day before follicle emergence, which is characterized by the appearance of a cohort of follicles of 4 mm in di ameter in the ovaries (Ginther et al., 1989; Adams et al., 1992). Nonetheless, using detailed ovarian ultrasonography examination, Jaiswal et al. (2004) described that even small follicles between 1 to 3 mm develop in a wave like manner associated with FSH surge. Interestingly, using mitotic index to estimate follicle development, Lussier et al. (1987) reported that a follicle would take 27 days to grow from 0.13 to 0.67 mm, but only 6.8 days to grow from 0.68 to 3.67 mm in diameter. After emergence, all r ecruited follicles of the cohort undergo a common growth phase, although it is likely that one is physiologically more advanced that others (Ginther et al., 1996b). Nevertheless, production of estradiol and inhibin by granulosa cells increases as follicle diameter increases and causes a negative feedback on pituitary and hypothalamus, inhibiting secretion of FSH (Bleach et al., 2001). With the decline in FSH concentrations, the majority of recruited follicles cease to grow and become atretic, and only few c ontinue development until the deviation and selection stage. The time of follicular deviation has been defined as the beginning of the difference in growth rates between the future dominant follicle and its largest subordinate (Ginther et al., 1996b). In Bos taurus, it occurs when the largest follicle has approximately 8.5 mm and the second largest follicle approximately 7.2 mm in diameter. It is important to

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53 emphasize that before deviation all follicles have the ability to become dominant. When the larges t follicle is ablated before deviation, the second largest follicle becomes dominant (Ginther et al., 1997). Nonetheless, if ablation of the dominant follicle is conducted after follicle deviation, the subordinate follicles are no longer able to develop li kely because they have undergone atresia and cell death, and a new FSH surge is induced 12 h later, resulting in emergence of new follicle wave within 24 h (Adams et al., 1992). It is generally accepted that the progressive decline in FSH concentrations a nd increase in LH concentrations are the main events determining follicle dominance. The dominant follicle is the main inhibitor of FSH secretion, but at the same time it is able to survive under the low concentration of this hormone. In fact, follicle dev iation occurs near when FSH concentration reaches the nadir and it may be a determinant for the selection of a single ovulatory follicle in monotocous species (Mihm and Evans; 2008). Therefore, only the dominant follicle is able to transit from a FSH depen dent phase to a LH dependent phase of follicle growth, whereas subordinate follicles perish, become atretic and regress. This ability to survive and continue to grow under this condition is supported by a series of molecular and biochemical changes occurri ng previous deviation that primarily increase its responsiveness to gonadotropins, and the amount of LH receptors and steroidogenesis capacity, ensuring follicle selection, dominance and final development (Fortune et al., 2004; Liu et al., 2009; Hayashi et al., 2010). In 10 to 30% of the lactating dairy cows, follicle co dominance occurs and a second follicle is selected to become dominant (Wiltbank et al., 2006).

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54 Follicular microenvironment is also critical for follicle dominance and final development. Th e intra follicular IGF system is considered one of the most important factors determining dominance. Insulin like growth factor 1 is able to induce granulosa cell proliferation, improve responsiveness to gonadotropins and act synergistically with them to i ncrease estradiol, activin, inhibin, follistatin, and VEGF in follicles that together become essential for cell proliferation and final follicle development (Fortune et al., 2004; Beg and Ginther, 2006). Nonetheless, concentrations of free IGF 1 do not inc rease in the dominant follicle around deviation, but decrease in the subordinate follicle, and when IGF 1 was injected inside the subordinate follicle, it became dominant (Ginther et al., 2004). The availability of IGF 1 in the follicle microenvironment i s controlled by the IGFBPs, especially IGFBP 4 and 5. In the free form, IGF 1 is bioavailable and capable of stimulating its receptor, and amount of free IGF 1 is determined by the proteolytic activity of the enzyme pregnancy associated plasma protein A (P APP A) in the dominant follicle. This protease is responsible for degrading IGFBPs and increasing availability of free IGF 1 (Fortune et al., 2004; Beg and Ginther, 2006). Some have suggested that acquisition of PAPP A activity is one of the earliest modif ication observed in the future dominant follicle (Fortune et al., 2004). The FSH action on granulosa cells to induce acquisition of LH receptors would be a later event in follicle dominance compared with the IGF system. Nevertheless, a recent study (Luo e t al., 2011) suggests that acquisition of LH receptors on granulosa cells precedes the changes in PAPP A and the increase in free IGF 1. Expression of LH receptors in the granulosa cells of dominant follicles was observed 12 h before follicle deviation, w hereas the increase in PAPPA expression was only detected at the

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55 moment of follicle deviation (Luo et al., 2011). Surprisingly, using a gonadotropin antagonist in the same study, the authors suggested that the LH receptors in granulosa cells would be induc ed by LH secretion itself. The LH signaling also increases expression of steroidogenic enzymes in theca (STAR, CYP11A1) and granulosa cells (CYP19A1). Before deviation, LH receptors are only expressed in theca cells through which LH stimulates expression o f steroidogenic enzymes essential for production of androgens that are then used by granulosa cells to produce estradiol. After deviation, expression of LH receptors in the granulosa cells allow the follicle to respond to LH and undergo further development (Aerts and Bols, 2010b; Luo et al., 2011). Acquisition of LH receptors by the granulosa cell also characterizes the acquisition of ovulatory capacity by the follicle in response to an LH surge. Induction of ovulation can be accomplished using exogenous Gn RH or LH only after follicle deviation, which is commonly used to manipulate the estrous cycle in cattle. Cocaine and amphetamine regulated transcript (CARTPT) and its peptide CART have been found in greater concentrations in atretic than in healthy folli cles (Lv et al., 2009). It has been also demonstrated that CART negatively regulates FSH and IGF 1 actions on granulosa cells in vitro reduces CYP19A1 expression and inhibit estradiol production in vivo (Lv et al., 2009). Moreover, CART concentrations in healthy follicles decrease after dominance (Lv et al., 2009). Follicle dominance is generally accepted as an important evolutionary mechanism to control number of offspring per pregnancy in monotocous species. Interestingly, CARTPT is not expressed in ovar ies of polytocous species such as pig and mice, which t h eor et ically requires a less stringent selection of

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56 follicles to be ovulated, suggesting that CART could be a functional mediator of selection of a single dominant follicle as in monocotous species (Sm ith et al., 2010). After deviation, the dominant follicle becomes LH dependent for final development and ovulation. However, if progesterone concentrations are high such as during the development of the first follicle wave or second follicle wave in anima ls presenting 3 waves of development, LH is blocked and pulsatile LH secretion attenuated As a result, the follicle enters a static phase and, eventually, atresia. On the other hand, when the CL regresses and progesterone declines, LH secretion increases and the dominant follicle is able to continue developing and ovulate. In cases of subluteal or low concentrations of progesterone, dominant follicles develop to large diameters and remain dominant longer, but ovulation does not occur because progesterone b locks the LH surge, which forms a persistent dominant follicle (Mihm et al., 1994). Regression or ovulation of the dominant follicle culminate with decreased concentrations of estradiol and inhibin, which then allow a rise in FSH concentrations and emergen ce of a new follicle wave. The emergence of the second follicle wave occurs around day 9 to 11 in cows with two wave cycles, and around day 8 or 9 in those with t h ree wave cycles, whereas the third follicle wave emerges around d 15 to 16 (Adams et al., 200 8). A certain amount of estradiol is required to trigger estrous behavior and the LH surge. Circulating concentrations of steroid hormones are determined by their secretion and catabolism. High producing lactating cows have high feed intake to sustain milk production, which is associated with greater splanchnic blood flow. The increased hepatic blood flow increases the clearance of ovarian steroids, which influences their circulating concentrations (Sangsritavong et al., 2002; Wiltbank et al., 2006). It has been

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57 hypothesized that dominant follicles of high producing dairy cows need to grow longer than normally to reach the threshold of estradiol concentrations to elicit estrus and an LH surge (Sartori et al., 2004). This mechanism would be responsible for ex tended dominance and subsequent decreased oocyte quality in dairy cows. It is thought that these follicles and oocytes in proestrus are overexposed to higher LH pulsatility that compromises the physiological kinetics of oocyte meiotic resumption and matura tion process. Additionally, duration of estrus is also negatively correlated with milk production (Lopes et al., 2004). The average estrous length was described as 8.7 hours in high producing dairy cows, but it was only 6.2 h for cows with milk production > 39 kg/day compared with 10.9 h for cows with production < 39 kg/d (Lopes et al., 2004). At the end of proestrus, the LH surge induces breakdown of the germinal vesicle of the oocyte nucleus and resumption of meyosis from the diplotene arrest. The surge o f LH overrides several factors such as hypoxanthine, cyclic adenosine 3', 5' monophosphate, cyclic guanosine 3', 5' monophosphate, reactive oxygen species, protein kinase A, and protein kinase C in the follicular environment responsible for the meiotic arr est. Such modifications culminate with reduced cyclic adenosine monophosphate and protein kinase A in the oocyte that in turn activates maturation promote factor (MPF) and finally induces meiotic resumption (Tripathi et al., 2010). Meiotic cell division th en progress until metaphase II, when additional molecular modifications induce spindle and MPF stabilization and consequently a new meiotic arrest of the oocyte now in the metaphase II stage, which is resume only after fertilization (Tripathi et al., 2010) Additional modifications and maturation of the oocyte cytoplasm also occur, and a tight synchrony between nuclear and cytoplasmic

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58 maturation is essential for oocyte development competence. The LH surge also induces modifications in steroidogenic enzymes and a dramatic increase in expression of PGF PGE 2 VEGF, and FGF 2 by the granulosa cells (Miyamoto et al., 2010). Additional events occurring at this time include the extrusion of the first polar body and cumulus cells expansion, which are important for chromosome number regulation, maturation a nd fertilization. Oocyte quality can be also affected by the follicle microenvironment. The follicular fluid is constituted by plasma crossing the blood follicular barrier and molecules secreted by cells in the follicular wall. It forms the biochemical en vironment surrounding the oocyte before ovulation and it is determinant to oocyte quality (Gosden et al., 1988). Fluid derived from thecal capillaries move into the antral cavity by osmotic gradient formed by the secretion of matrices of hyaluronan and ver sican by the granulosa cells, which are too large to cross the follicular antrum (Rodgers and Irving Rodgers, 2010). Thus, follicular fluid composition has components of plasma and resembles plasma composition. In lactating dairy cows, there is a high corr elation between concentrations of metabolites in plasma and in the follicular fluid (Leroy et al., 2004). A ddition of NEFA and BHBA to medium of culture imp airs follicular steroidogenesis as well as oocyte competence to mature, fertilize and develop to the blastocyst stage (Gomez, 1997; Hashimoto et al., 2000; Armstrong et al., 2001; Leroy et al., 2005, 2006, 2008). Corpus Luteum Formation, Function and Regression The CL is an endocrine gland formed by the remaining follicular cells after ovulation. It is p rimarily responsible for the secretion of progesterone during the luteal phase of estrous cycle or throughout gestation in case of pregnancy establishment. After follicle rupture, CL formation is characterized by intensive tissue remodeling and

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59 cellular mi gration. These events are facilitated by invagination of follicular wall and breakdown of the basal membrane that allow the migration of theca cells, fibroblast and endothelial cells to the central part of the developing CL. With the sprouting of endotheli um cells, angiogenesis takes place and forms a new vascular network that is crucial to support the differentiation of follicular cells and rapid CL development. The CL has one of the greatest blood flows per unit of tissue, and the consumption of oxygen in a cell basis is estimated to be 2 to 6 times greater than that for the liver, kidney or heart (Niswender et al., 2000; Robinson et al., 2008). Endothelial cells may account for up to 50% of the cells in the mature CL, which is even greater than the amount of luteal cells (30%) that are responsible for progesterone production and secretion (Miyamoto et al., 2010). The remaining 20% of cells are constituted by pericytes, fibrocytes, nerves, immune and smooth muscle cells, demonstrating that CL is a heterogen eous tissue (Farin et al., 1986). Reorganization and arrangement of luteal cells occurs in such a way that all different types of cells are intermixed in close proximity to one another and normally adjacent to one or more capillaries, which ensure the supp ly of all nutrients and controlling factors for adequate progesterone production (Niswender et al., 2000). The bovine CL grows from 0.5 g immediately after ovulation to 5.5 g within 10 days, which is mainly caused by the high mitotic rate and by a two fold increase in cell size of large luteal cells whose numbers remain somewhat constant (Niswender et al., 2000; Robinson et al., 2008). Moreover, 22% of the volume of the mature bovine CL is accounted for by the capillary lumina (Niswender et al., 2000). The preovulatory LH surge induces differentiation of follicular cells into luteal cells that are able to produce progesterone instead of primarily estradiol. Thus, the main

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60 molecular/functional modifications caused by the LH surge include the regulation of ste roidogenic enzymes that shift production of granulosa cells from estradiol/androgen hydroxysteroid hydroxylase cytochrome P450 and a romatase cytochrome P450. There is also upregulation of angiogenic factors such as VEGF and FGF 2 that are essential for the neovascularization process described above (Miyamoto et al., 2010). The precursor for synthesis of progesterone is cholesterol, wh ich is obtained primarily from de novo synthesis from acetate and long chain fatty acids, but also from dietary sources when animal byproducts are fed to cows. Cholesterol is transported to the ovaries as part of lipoproteins. In cattle, it is mainly synth etized in the liver and transported by high density lipoproteins (HDL). Cholesterol in HDL is taken up by luteal cells via receptor mediated endocytosis and then transported to the mitochondria, which is the site for the initial steps of steroidogenesis. T he transport across the inner mitochondrial membrane is considered the rate limiting step in progesterone synthesis, and is controlled by the steroidogenic acute regulatory protein (StAR; Rekawiecki et al., 2008). Endozepine and its benzodiazepine receptor seem also to be involved in controlling this step (Niswender et al., 2000). Cholesterol at the inner mitochondrial membrane is cleaved by cytochrome P450scc forming pregnenolone, which is transported to the smooth endoplasmic reticulum and converted to pr ogesterone by the HSD (Niswender et al., 2000). Therefore, StAR, cytochrome P450scc and HSD are pivotal proteins controlling progesterone synthesis in luteal cells.

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61 Within luteal cells, two distinct populations are observed, small and larg e luteal cells, which are derived from theca and granulosa cells respectively. In small luteal cells, the main regulator of progesterone synthesis is LH, which increases cAMP and then activates PKA that in turn increases expression of StAR, cytochrome P450 scc and HSD, which increases the transport of cholesterol to the P450scc complex (Niswender et al., 2000). Although large luteal cells have LH receptors and they are responsible for almost 85% of the total progesterone synthesized by the CL, they do not respond to LH with progesterone production (Miyamoto et al., 2010). It seems that those cells have higher concentrations of cAMP and that PKA would be constitutively activated, sustaining the basal secretion. Alternatively, additional luteotropic hormones such as GH, IGFs, FGFs, oxytocin, PGs and noradrenalin stimulate progesterone synthesis in large luteal cells. The control of progesterone production by these local factors gives the CL certain autonomy, allowing auto regulation of progesterone production. Moreov er, progesterone supports its own synthesis and protects luteal cells from apoptosis (Okuda et al., 2004a; Liszewska et al., 2005). Progesterone acts in luteal cells through progesterone nuclear receptors and through non genomic pathways activated by bind ing to progesterone membrane receptors resulting in stimulation of progesterone synthesis (Rekawiecki et al., 2008). Progesterone in combination with estradiol regulates the expression of steroidogenic receptors in the uterus and hypothalamus. Through ste roidogenic control, temporal and spatial changes in expression of steroid receptors are critical to changes in uterine biology that in turn determine the end of luteal phase or establishment/maintenance of pregnancy. When embryo development and pregnancy

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62 e stablishment do not occur, regression of CL is required for normal estrous cyclicity, ovulation, and a new attempt for pregnancy. The initial mechanism causing the demise of the CL is coordinated by uterine pulsatile secretion of PGF during the late stages of diestrus. Uterine PGF reaches the ovaries primarily by a countercurrent exchange mechanism between of utero ovarian vein and ovarian artery (Hixon and Hansel, 1974). Prostaglandin F is synthesized in the uterus from arachid onic acid released after hydrolysis of membrane phospholipids by action of phospholipase A 2 (PLA 2 ) and in smaller scale by phospholipase C (PLC). Prostaglandin G/H synthase catalyzes the conversion of arachidonic acid to PGH 2 which is considered a rate li mit step in the synthesis of prostaglandins. Prostaglandin F synthase then convert PGH 2 to PGF The prolonged exposure of the uterus to progesterone during diestrus results in reestablishment of the phospholipid pool in endometrial cells and enhancement of PGF synthase. Exposure to progesterone for approximately 10 days induces downregulation of its own receptors at the luminal epithelium of the endometrium, which in turn allows upregulation of estrogen and oxytocin receptors that otherwise were previously blocked by the action of progesterone (Spencer and Bazer, 1995; Wathes et al., 1996). Simil ar events seem to occur also in the hypothalamus, in which progesterone exposure also has been demonstrated to downregulate its own receptors, which would be important for estradiol action on hypothalamus (McCra c ken, 1999). Taken together, these events rep resent a transition from progesterone to estradiol action in the reproductive axis (McCra c ken, 1999). Estradiol produced by the dominant follicle of the last follicular wave of estrous cycle is able to stimulate hypothalamic oxytocin pulse generator to

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63 sec rete pulses of oxytocin, which in turn binds to its receptors in the luminal epithelium. Oxytocin binding to receptors in the uterus activates PLA 2 that hydrolyzes the ester bond between phospholipids and arachidonic acid. Free arachidonic acid in the cyto plasm of the endometrial cell is processed by PGF endoperoxide synthase to result in pulses of PGF Initially, PGF secretion is in a subluteolytic fashion sufficient to induce luteal secretion of oxytocin. Luteal oxytocin in turn, further stimulates s ecretion of PGF in a pulsatile fashion that acts in the ovary, forming a positive feedback loop mechanism between the uterus and the ovaries, resulting in demise of the CL. One to two pulses of PGF in 24 h are required for regression of the CL. During this process, production of intraluteal PGF seems to complete the process of CL regression (Wiltbank and Ottobre, 2003). The pulsatile pattern of PGF is required for CL regression (Schramm et al., 1983; Ginther et al., 2009), and it is coordinated by u terine transduction of oxytocin pulse generator, which is then amplified by luteal secretion of oxytocin and co regulated by transient refractoriness of oxytocin receptors in the uterus and PGF receptors in the CL (Silvia et al., 1991; McCra c ken, 1999). Regression of the CL is divided into two steps: functional CL regression that is first observed and characterized by a rapid decrease in progesterone production, and the morphological regression of the CL. Uterine PGF binds to its receptors in luteal ce lls that are coupled with PLC and activates two second messengers, inositol triphosphate, which increases intracellular concentrations of Ca +2 and diacylglycerol, which activates phosphokinase C (PKC; Sakamoto et al., 1995). These two second messengers ar e involved in a series of cellular reactions and are believe to coordinate all the cellular

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64 changes occurring during luteolysis (Skarzynski and Okuda, 2010). Receptors of PGF are also observed in endothelial cells of blood vessels of the periphery of the CL and may play a role during luteolysis (Shirasuna et al., 2008). It is generally accepted that PGF initially induces luteal release of nitric oxide that leads to a rapi d and transient increase in blood flow in the periphery of the CL, which is accompanied by upregulation of inflammatory cytokines and apoptotic factors. Th ese initial actions of PGF are followed by a drastic suppression of angiogenic factors and increase s in vasoactive compounds that induce vasoconstriction, reduction in blood f lux and hypoxia of luteal cells, which in turn cause angiolysis and inhibit progesterone synthesis by disrupting activi ty of steroidogenic enzymes, inducing further apoptosis of lu teal cells. Additional events include increased secretion of luteal oxytocin and PGF decreased expression of luteotropic hormone receptors in luteal cells, and reduction in uptake and transport of cholesterol, all of which suppress steroidogenesis. Finally, increase in the extracellular matrix proteases and invasion of immune cells are described and are associated with luteal tissue remodeling including disruption of the vascular bed and the luteal cells themselves. Shirasuna and coauthors (2010) demonstrated a rapid and expressive migration of neutrophils 5 min after PGF administrati on, despite lack of mRNA for PGF receptor for prostaglandins in these immune cells. They suggest that immune cells participate in the very early stages of luteolysis. It occurred previously to the increase in mRNA of neutrophils chemokines, which was obs erved 15 min after PGF administration. The initial increase in blood flux associated with increase expression of

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65 selectins in the lumen of luteal blood vessels likely explain the increased neutrophil uptake to the luteal tissue (Shirasuna, personal commu nication). In the first 5 d after ovulation, the CL is refractory to the luteolytic action of exogenous PGF administration (Miyamoto et al., 2009; Shrestha and Ginther et al., 2011). Although administration of PGF during metestrus reduces progesterone synthesis (Cerri et al., 2011; Shrestha and Ginther et al., 2011), a single treatment is unable to induce luteolysis in most cows. This fact constitutes a challenge when attempting to manipulate the estrous cycle in cattle in metestrus and early diestrus. Receptors of PGF are highly expressed in luteal cells throughout the estrous cycle and thus do not justify the refractoriness of the tissue (Sakamoto et al., 1995). Miyamoto et al. (2009) proposed that PGF in the early CL decreases the expression of important vasoacti ve mediators that are related with luteolysis, whereas it stimulates angiogenic factors and the IGF system, which actually would stimulate progesterone production. In fact, blood flow and a transient increase in progesterone are observed after a luteolytic dose of PGF given on d 3 of the estrous cycle, but this is followed by a decline in concentrations within 2 h of treatment (Shrestha and Ginther et al., 2011). Wiltbank and Ottobre (2003) suggested that the inability of the early CL to produce intraluteal PGF mig ht explain it refractoriness to the luteolytic actions of exogenous PGF Abrogation of Luteolysis and Maternal Recognition of Pregnancy When pregnancy is established, the luteolytic mechanism is abrogated Paracrine action of interferon by trophectoderm cells of the elongating conceptus blocks the upregulation of oxytocin and estradiol receptors in the luminal epithelium of the endometrium, thereby preventing the pulsatile secretion of uterine PGF (Spencer et al., 2007). Interestingly, the downregulation of progesterone

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66 receptors in the luminal epithelium continues and is important for establishment of the servomechanism of nourishment of the growing conceptus by regulation of interferon stimulate genes (ISGs) in the endometrium that ar e crucial for conceptus development and inhibition of the conceptus allograft rejection. Moreover, antiluteolytic action and most stimulation of ISGs by IFNT are also dependent on progesterone action (Spencer et al., 2007). The bovine conceptus stays free floating in the uterus during preimplantation stages and there is no direct communication between trophoblastic cells and uterus. Thus, in order to block the luteolytic cascade, sufficient amounts of IFNT are needed to be secreted by the conceptus, which in turn is dependent of adequate development and elongation. Protein and mRNA levels of IFNT at the blastocyst stage are low, but increase with the elongation of the conceptuses and consequent trophectoderm proliferation and substantial increases in total mass of IFNT producing cells (Ealy and Yang, 2009). Therefore, uterine and endocrine environment is extremely important to allow adequate embryo development and elongation. The rise in progesterone concentrations after ovulation is one of the major factors that have been studied in this regard. Earlier rise in progesterone concentrations has demonstrated benefits to conceptus elongation and IFNT production (Garret et al., 1988; Carter et al., 2008; Clemente et al., 2009). This difference in development is p rimarily caused by effects on endometrium physiology, as it is associated with histotroph secretion that benefits conceptus development (Forde et al., 2009). Elevated progesterone concentration anticipates downregulation of progesterone receptors in the lu minal epithelia and the establishment of the servomechanism of uterus/conceptus.

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67 Conversely, a slow rise in progesterone concentrations after ovulation retard embryo development and IFNT secretion at preimplantation stages (Forde et al., 2010). It might c onstitute a problem in high producing dairy cows that experience extensive catabolism of steroids and typically have lower concentrations of progesterone than heifers (Sartori et al., 2004). In fact, low progesterone concentration between d 4 and 7 after A I have been associated with reduced fertility in lactating dairy cows, although a weak relationship between milk yield and progesterone was found (Strong et al., 2005). Whether this association is mediated by a less competent CL or simply by a delay in ovu lation remains to be clarified. In that study (Strong et al., 2005), a quadratic relationship between progesterone concentrations and pregnancy was observed, suggesting that there is an ideal concentration in which fertility was maximum, and both very low and very high concentrations were detrimental to pregnancy. Concentration of progesterone can be compromised by catabolism (Sangsritavong et al., 2002), but also by impaired production. Ovulation of small follicles results in formation of small CL and cons equently fewer luteal cells to produce progesterone, which can reduce fertility in dairy cows (Vasconcelos et al., 2001). It is possible that NEB and diseases might potentially affect progesterone production by compromising steroidogenesis ( Sheldon et al., 2009). Despite the reason, low concentration of progesterone during diestrus compromises conceptus elongation and, consequently, secretion of IFNT, which may result in failure to abolish the luteolytic cascade and embryonic loss. It has been suggested th at the CL of pregnant cows is more resistant to the action of PGF than the CL of the estrous cycle (Inskeep et al., 1975; Silvia and Niswender,

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68 1984). Recent work suggested that exit of IFNT from the uterus and stimulation of ISGs in the CL during early pregnancy may be responsible for this increased resistance to luteolysis (Oliveira et al., 2008; Bott et al., 2010). Using the sheep as model, Oliveira and coauthors (2008) detected significant amounts of IFNT into the uterine vein of pregnant ewes, and de monstrated that infusion of small amounts of IFNT in the uterine vein of nonpregnant estrous cyclic ewes extended the estrous cycles to approximately 32 days. Moreover, ISGs have also been identified in peripheral blood mononuclear cells of sheep (Yankey e t al., 2001) and dairy cows (Gifford et al., 2007), and they have been suggested as mechanism to enhance maternal antiviral responses to possible infections and consequent protection of the conceptus (Hansen et al., 2010). In the CL, ISGs have been identif ied mostly in large luteal cell, but also in smaller quantities in small luteal cells, and have been associated with stabilization of Akt pathway, which is important for cell survival and blocked during luteolysis by PGF (Oliveira et al., 2008). Reproductive Efficiency and Development of Timed Artificial Insemination Protocols Reproductive efficiency is critical for the profitability and sustainability of dairy farms The value of a pregnancy has been estimated at US $2 78 (De Vries, 2006). Within a given type of dairy production system, there is an optimal time for cows become pregnant in which profitability is maximized, and cows that are not pregnant beyond this optimal time become economically less efficient and costl y (Meadows et al., 2005). As discussed by Britt (1985), a decline in reproductive efficiency in most herds reduces milk yield per day of calving interval, increases the risk of culling, increases the costs of new attempts for pregnancy, reduces the number of replacement heifers, and increases costs with veterinary interventions. Certainly, within these factors, milk yield

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69 and replacement availability are likely to be the most important components. Milk production per cow in US had a steady increase of 1.3% per year in the last 60 years, which is projected to continue for the next 40 years (Santos et al., 2010b). This increase in milk production is primarily explained by implementation of AI, genetic selection for productive traits, improvements in nutrition and management practices, and intensification of production. Contrasting with the improvement in milk production, reproductive efficiency has declined during the same period (Butler, 2003). As consequence, several associations between milk production and fertility of dairy cows have been made, where most of the time the optimization of both factors was considered incompatible. Several papers were published in the last decade describing the increase of milk production as the major reason for the decline in reproductive efficiency (Lucy, 2001; Royal et al., 2002; Washburn et al., 2002a; Butler, 2003). However, studies comparing fertility and milk production within herds or among herds have showed no direct association between the two (Santos et al., 2009; LeB lanc, 2010). It is generally accepted nowadays that an increase in milk production does not directly impair fertility of dairy cows, but does modify behavior, metabolic, nutritional and health needs. It can influence estrous behavior, reducing intensity an d duration (Wiltbank et al., 2006). Therefore, as production increases, matching the environment to the more productive genotype becomes paramount for the reproductive success of dairy cows. Implementation of new reproductive techniques and management pr actices, and concurrent increase in consciousness of producers when applying science based technologies have become integral components in management of dairy cows in recent

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70 years (Caraviello et al., 2006; LeBlanc et al., 2006; Browlie et al., 2011). These management changes associated with inclusion of health and reproductive traits in genetic selection programs for dairy cows have altered the genetic trend for reproduction at the same time that milk production continues to increase (Norman et al., 2009). The development of timed AI programs is an important example of a strategy that has contributed to improvements in reproductive performance (Wiltbank et al., 2010), and implementation results in economic benefits for dairy herds under different production and reproductive scenarios (De Vries, 2006; Lima et al., 2010; McDougall, 2010). Reproductive programs have evolved according to the current understanding of the mechanisms that control the estrous cycle and availability of pharmaceuticals capable of alte ring the course of reproductive events during the cycle. Initial attempts of estrous synchronization were conducted by supplementing progesterone or progestins either in the diet or in injectable forms (Lauderdale, 2009). In general, longer duration of dai ly treatments or those conducted at the end of the estrous cycle resulted in good synchronization of estrus but of low fertility, which limited the success of those programs. Then, the development of natural and synthetic PGF for use in cattle resulted i n major strides in the development of synchronization programs that did not compromised fertility (Lauderdale et al., 1974). Different strategies were then developed using PGF to concentrate expression of estrus in a short period of time and, consequentl y, facilitate detection of estrus and AI. It is expected that 70% of estrous cyclic cows will respond to a single injection of PGF administered at random stages of the estrous cycle, and that 90% would respond to a second injection of PGF given 10

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71 to 1 4 days later, with most cows expressing estrus between 2 to 7 days after injection (Thatcher et al., 2004). However, limitations of these programs are the lack of precise control of follicle development and the low estrous detection after treatment (approx imately 60%; Chebel et al., 2006). Cow factors such as prevalence of anovulation, low intensity and duration of estrus (Wiltbank et al., 2006) and lameness, associated with environmental factors that suppress estrous expression such as heat stress and poor footing, and human errors limit the efficacy of synchronization programs using only methods to control luteal lifespan. Controlling follicle development by incorporating GnRH in programs with PGF allowed greater control of follicle development (Thatcher et al., 1989; Macmillan and Thatcher, 1991). Injection of GnRH induces an LH surge 2 h later and ovulation of the dominant follicle around 28 h after treatment, which is followed by synchronized recruitment of a new follicle wave (Bodensteiner et al., 199 6). Injection of GnRH at random stages of the estrous cycle followed 7 days later by an injection of PGF improved estrous synchronization and resulted in acceptable fertility (Thatcher et al., 1989; Burke et al., 1996). Later, it was determined that with the inclusion of a second injection of GnRH 48 h after the PGF injection could synchronize ovulation within 24 to 32 h after treatment, eliminating the need for estrous detection (Pursley et al., 1995; Burke et al., 1996). This protocol termed Ovsynch allowed 100% of eligible cows to receive AI with adequate fertility, thereby improving pregnancy rate (Bu rke et al., 1996; Pursley et al., 1997; Tenhagen et al., 2004). It has been demonstrated that ovulation synchronization and fertility following the Ovsynch protocol are optimized when cows receive the first GnRH of the protocol in

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72 early diestrus (Vasconcel os et al., 1999). In fact, cows at this stage of the estrous cycle have reduced occurrence of spontaneous luteolysis during the proto col and a greater probability of bear ing a dominant follicle that ovulates in response to the first GnRH injection. Moreove r, ovulation at this stage assures that the ovulatory follicle will develop under high systemic concentrations of progesterone and also limits the period of follicle dominance, which are both important factors affecting fertility (Bleach et al., 2004; Cerr i et al., 2009; Bisinotto et al., 2010a). Moreira et al. (2001) then developed a presynchronization protocol to maximize the proportion of cows starting timed AI protocol at early diestrus, which would optimize synchronization and P/AI of Ovsynch protocol. The protocol termed Presynch consisted of two injections of PGF administered 14 d apart, with the second injection administered 12 before the first GnRH injection of Ovsynch protocol. Compared with the conventional Ovsynch, the program Presynch/Ovsynch increases P/AI on d 32 after AI from 36.6 to 48.5%. However, the difference was driven only by improvements in fertility of estrous cyclic cows, as no differences were observed in fertility of anovular cows, which in fact are not expected to respond the PGF treatments. The benefits of Presynch were later confirmed by other studies (El Zarkouny et al., 2004; Navanukraw et al., 2004). The study of Navanukraw et al. (2004) extended the interval between the second PGF of the Presynch to the first GnRH of the timed AI program to 14 days in order to facilitate the implem entation of the program by using weekly basis injections. However, a later study by Galvo et al. (2007a) found that reducing the interval from 14 to 11 days increased ovulation to the first AI and improved P/AI. No one of these studies however evidenced i mprovements in fertility of anovular cows by the use of Presynch.

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73 Anovulation is a major problem for good reproductive success in dairy farms. Although the use of timed AI programs allows to inseminate anovular cows, these animals have smaller P/AI and inc reased risk of pregnancy loss, which compromises pregnancy rate and increases culling compared with their cyclic counterparts (Rhodes et al., 2003; Santos et al., 2004). Poor synchronization of ovulation does not seem to be an issue for anovular cows (Gme n et al. 2003), and does not explain the low fertility experienced by them. On the other hand, the low concentrations of progesterone during the development of the ovulatory follicle seem to be a major factor impairing their fertility (Bisinotto et al., 20 10a). The low concentrations of progesterone during growth of the ovulatory follicle in anovular cows overexposes the follicle and oocyte to LH, which compromises oocyte maturation (Revah and Butler, 1996). Additionally, low progesterone concentrations alt er the composition of the follicular fluid (Cerri et al., 2011) and uterine physiology in the subsequent estrous cycle (Shaham Albalancy et al., 2001; Cerri et al., 2011), which might affect fertility. Embryo quality on d 7 after AI in cows ovulating folli cles developed under low concentrations of progesterone is reduced, but reversed by progesterone supplementation (Rivera et al., 2011). Interestingly, low progesterone results in larger conceptuses and greater secretion of IFNT at the preimplantation stage s (Ribeiro, Bisinotto and Santos, unpublished). Therefore, development of protocols that also improve fertility of anovular cows is necessary. Induction of ovulation before enrolment in timed AI programs is a method used to increase the proportion of cows in diestrus at the initiation of the program, and this is expected to improve fertility in dairy cows. Based on this concept, presynchronization protocols including the use of GnRH injections (Bello et al., 2006; Galvo et al., 2007a;

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74 Souza et al., 2008) or progesterone supplementation (Chebel et al., 2006, Bicalho et al., 2007, Rutigliano et al., 2008; Stevenson, 2011) have been proposed aiming to induce estrous cyclicity of anovular cows before the timed AI protocol. Bello et al. (2006) demonstrated that combining PGF followed 2 d later by GnRH improved ovulatory response to the first GnRH of the Ovsynch protocol when it was initiated 6 d after presynchronization. The use of progesterone supplementation with controlled internal drug release (CIDR) inser ts during presynchronization induces estrous cyclicity in approximately 50% of the anovular cows, but did not improve fertility (Chebel et al., 2006, Bicalho et al., 2007). Galvo et al. (2007a) reported that use of GnRH during presynchronization increased the proportion of cows bearing CL at the first GnRH of timed AI protocol, but it did not improve P/AI. Souza and coauthors (2008) howeve r, developed a protocol termed d ouble Ovsynch, which combines two standard Ovsynch protocols, one functioning as presyn chronization followed by the second 7 days later functioning as timed the AI protocol. Compared with Presynch, it resulted in greater fertility in primiparous cows, perhaps by induction of estrous cyclicity in this group known to have more prevalence of an ovular cows (Santos et al., 2009). A simple alternative to be used in timed AI programs and also a potential alternative for synchronization of anovular cows is progesterone supplementation. The use of CIDR between the injections of GnRH and PGF maintain blood concentration of progesterone sufficient to prevent premature estrous behavior, LH surge and ovulation during the timed AI protocol. In general, it benefits fertility of beef cows (Lamb et al., 2001), dairy heifers (Rivera et al., 2005) a nd also dairy cows when they are not presynchronized or when part of them are selectively inseminated following estrous

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75 detection before enrolment in the timed AI protocol (El Zarkouny et al., 2004; Melendez et al., 2006; Chebel et al., 2010; McDougall, 20 10a). It is possible that inclusion of progesterone during the timed AI might negate the need for presynchronization, which would minimize labor and reduce the length of the protocol. This strategy with progesterone becomes more attractive in programs of s hort duration in which follicle dominance is restricted such as in the 5 d timed AI protocol (Bisinotto et al., 2010b; Santos et al., 2010a). The 5 d timed AI protocol is a modification of the conventional Ovsynch or 7 d program, in which the interval betw een the first GnRH and PGF shortens from 7 to 5 days. The rationale of such programs is to improve fertility by reduction of 2 days in the period of follicle dominance. Bridges et al. (2008) demonstrated that this program with a 72 h of proestrus improved fertility in beef cows. Santos et al. (2010a) demonstrated improvements in fertility when the 5 d timed AI protocol was compared with a standard 7 d program. Reducing the period of follicle dominance in 1.5 to 2 days was sufficient to improve embryo quality (Cerri et al., 2009) a nd P/AI of lactating dairy cows (Bleach et al., 2004). Extension of the period of dominance compromises oocyte quality and fertility in cattle (Mihm et al., 1994a; Austin et al., 1999) likely because of overexposure of the follicle and oocyte to LH (Mihm e t al., 1994a; Mihm et al., 1994b; Revah and Butler, 1996). This might be especially important when the follicle is growing under low concentrations of progesterone, and LH pulsatility is consequently greater (Aerts and Bols 2010). In fact, Santos and co au thors (2010a) observed that the benefit of reducing the period of follicle dominance was more pronounced for cows with low progesterone

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76 concentration in plasma (< 1 ng/mL) at the beginning of timed AI program than for those with high concentration. The lim iting factor to reduce the period of follicle dominance in timed AI programs is the luteolysis of the newly formed CL resulting from ovulation to the first GnRH injection of the protocol. Although the CL develops within 2 to 3 days after ovulation, it is r efractory to the luteolytic action of PGF until d 5 after ovulation (Miyamoto et al., 2010). Adequate fertility in any timed AI program requires adequate luteolysis. Concentrations of progesterone on the day of AI > 0.25 ng/mL on the day of AI or 24 h after induction of luteolysis reduced P/AI in dairy cows (Santos et al., 2010a) and dairy heifers (Rabaglino et al., 2010). Thus, for 5 d programs, two injections of PGF given on days 5 and 6 after the first GnRH are needed for adequate CL regression. It may be particularly important in presynchr onized cows because of increased ovulation to the first GnRH injection and, consequently, greater occurrence of newly formed CL at PGF which did not respond adequately with a single PGF injection on d 5 (Santos et al., 2010a). The disadvantage of this approach is that cows have to be handle d an additional day. Nonetheless, the second PGF injection did not improve fertility in the 5 d timed AI program in dairy heifers (Rabaglino et al., 2010) and in one study with beef cows (Cruppe et al., 2010). The lack of benefit to the second PGF treatment is likely the result of low ovulation to the first GnRH injection of the timed AI protocol. Although this program requires handling of cows in more days of the week, it improves P/AI in dairy cows (Santos et al ., 2010a), which becomes a very attractive alternative to maximize fertility, particularly in programs with seasonal breeding. Responses to the 5 d timed AI program might vary with altering the presynchronization scheme,

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77 supplementation of progesterone, pr oestrus length, or alternative strategies to induce luteolysis of an early CL. All the aforementioned should be evaluated to further optimize response and implementation of this protocol. General Features and Reproductive Management in Seasonal Grazing Dai ry Farms Economics of the dairy industry in US has encouraged producers to pursue production methods that incur in reduced costs and inputs. It has generated renewed interest in grazing or pasture based dairy production as an alternative to reduce costs in volved with investments on infrastructure and technology, labor and feeding (Staples et al., 1994; Macdonald et al., 2008) T he goals and management strategies in grazing dairy farms are generally distinct from the conventional confinement farms In dairy farms that use confinement, the focus is on maximization of the outputs per cow, whereas in grazing farms the focus is to maximize production per unit of land at the same time that inputs are kept at minimum. Efficient pasture based dairy production is nor mally characterized by high milk output per unit of land, whereas farms using confinement are characterized by high milk output per cow (Clark and Kanneganti, 1998). In some cases, net profit has been reported to be greater in well managed grazing farms co mpared with cows in confinement farms (Parker et al., 1992; Dartt et al., 1999; White et al., 2002). Forage production on p asture in grazing dairy farms should be the major source of nutrient s for cows and, therefore, ability to grow high quality forages is a special concern in grazing dairy production Moreover, pasture utilization should be maximized by matching forage growth with the nutrient demands by the cows and, thus, seasonality of total mass production and quality of forages are important factors driving

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78 management decisions. In the Southeast US, Bahiagrass ( Paspalum notatum ) and Bermudagrass ( Cynodon dactylon ) are the foundation of forage production for grazing animals (Fike et al., 2003). Both are perennial warm season forages, and the cultivar Bermudagrass Tifton 85 is of special interest for grazing dairy farms because of the nutritive value and high yields. For cool season, the annual forage ryegrass ( Lolium multiflorum ) is the most common forage used and, although production is smaller compar ed with warm season grasses, it has excellent quality because of high digestibility and crude protein content. Evidently, the stocking ratio (number of animals allocated to an area of land) determines the pasture allowance and, consequently the intake of f orage by the animals. Allowance and DMI intake have a positive but curvilinear relationship, so at the inflexion point is the maximum biological and economic efficiency of pasture utilization. I ncreasing stocking ratio decreases pasture allowance, DMI and milk production per cow. However, when not excessively used it also determine s greater pasture growth, improved pasture quality and greater milk production per area of pasture which is mostly desired (Macdonald et al., 2008). T he ideal stocking ratio va ries according to the type of forage used, estimated forage DM available and production potential of cows and should be carefully evaluated in each particular situation Milk yield per cow is generally lower in dairy farms that use grazing compared with confinement (Kolver, 2003). Low DMI and, consequently, metabolizable energy intake of pasture only diets has been identified as a major factor limiting milk production in grazing dairy farms This is particularly important when high performance genotypes, not selected within a pasture system, are used (Kolver, 2003). Additionally to

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79 production, extensive loss of BCS postpartum also becomes a concern for pasture only diets (Boken et al., 2005; Fontaneli et al., 2005). Thus, although grazing dairy producers h ave reduced production costs, supplemental concentrate are often fed. Moreover, the availability of relatively inexpensive concentrates makes the supplementation possible and desirable (Fike et al., 2003). The d airy industry in the US is often cited as hav ing favorable milk price to cost ratio, which favors the maximization of milk production per cow (Clark and Kanneganti, 1998). Thus, the primary goals of supplementation are to increase DMI and maximize profit per cow and per unit of land (Bargo et al., 20 03). Overall objectives still include: 1) increase milk production per cow, 2) increase stocking rate and milk production per unit of land, 3) improve the use of pasture with the higher stocking rate, 4) maintain or improve BCS to improve reproduction duri ng pasture shortage, 5) increase length of lactation during periods of pasture shortage, and 6) increase milk protein content by energy supplementation (Bargo et al., 2003). In a study reported by Soder and Rotz (2001), profitability of grazing farms incre ased as supplementation level increased, and at higher levels of supplementation, the grazing dairy farms showed greater profitability than the farms using confinement. Bargo and coauthors (2003) reviewed the responses of supplementation of high producing dairy cows on pasture (25 kg/day in early lactation), using mostly data from US farms. Milk response varied according to the substitution rate, in which the lower the substitution the higher the milk response to supplementation. Nonetheless, milk producti on in early lactation had a linear increase of 1 kg of milk/kg concentrate as the amount of concentrate increases from 1.2 to 10 kg DM/d. Comparing responses of the greatest amount of supplementation (10 kg DM/d) against the pasture only diet, it

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80 resulted in an increase of 24% in total DMI, 22% in milk production, 4% in milk protein percentage, and reduction of 6% in milk fat percentage. During late lactation cows had a lower marginal milk response. Also, fat supplementation also seemed a reasonable alterna tive increasing milk production approximately 6% without affecting milk protein and fat. Nevertheless, Fontaneli et al. (2005) demonstrated that supplementing concentrate at a ratio of 1 kg for each 2 kg of milk produced in a pasture based system, milk pro duction was 19% lower compared with a control confinement system fed a total mixed ration (29.8 vs. 25.1 kg/d). Furthermore, as the amount of concentrate fed increases, and substitution occurs, the risk of ruminal acidosis, diarrhea, and displacement of ab omasum increases. In general, concentrates should not represent more than 50% of total DMI (Bargo et al., 2003). Additionally, in some regions it is possible that forage availability exceed the nutrient demand of cows during specific times and, therefore i t can also be conserved to be used in periods of forage shortage (Burke and Verkerk, 2010). Environmental conditions are also important factors for grazing dairy production because they dictate forage growth/quality and, in some regions, climatic constrai ns might limit production Snow cover of 4 to 5 months in northern climates limits pasture utilization In the Southeast US heat stress during summer represents an important challenge to dairy production. The temperature humidity index stays above the lim it co nsidered as heat stress for dairy cows 4 to 6 months a year making difficult the year round production in grazing farms. This is particularly important when shade and prevention of direct solar radiation is unavailable. Heat stress is especially impo rtant for reproductive performance, because of its detrimental impacts on oocyte quality and

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81 early embryo development (Hansen et al., 2009). De Vries et al. (2005) reported a decrease in 21 d pregnancy rate from 17.9 to 9.0% during the months (May to Octob er) in dairy farms located in Florida and Georgia. Lima et al. (2010) reported a reduction of in the proportion of cows pregnant in the first 21 d of breeding from 41.2 to 27.7 % and from 27.5 to 22.5% for the overall 21 d pregnancy rate in a confinement fa rm during the summer months in Florida despite use of intensive evaporative cooling. Therefore, although it is not a rule, seasonality of production is a choice for management of dairy cows in grazing farms which is used to maximize pasture nutrient util ization and overcome climatic constrains. In Florida, a late fall calving season is used in order to have cows at peak production and inseminated when there is no heat stress, and to match greater nutrient requirements with periods of high quality forage Seasonal production also represents a strategy to facilitate management, in which producers can focus their work on specific activities through different periods of the year (calving, calf rearing breeding, dry off and management of dry cows, etc ). Noneth eless, adoption of season ality in production has a series of implications to the management of the farm First, in order to have an ideal and concentrate calving season o n a year ly basis (365 d calving interval), reproductive efficiency is extremely import ant. A b reeding season must be implemented and cows must become pregnant in a short and pre established period of time, having a calendar date to be followed in all cows irrespective of individual calving date. Cows not pregnant at the end of the breeding season are normally involuntary culled at the end of lactation, impacting profitability negatively (Rhodes et al., 2003; Lucy et al., 2004). Moreover, a cow that becomes pregnant near the end of the season obviously also calves late in the following calvin g season and consequently

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82 has a short interval to reestablishment of energy balance and estrous cyclicity, normally resulting in wors e reproductive performance. In farms using one calendar day for dry off, late calving also represents a shorter lactation and consequently less milk production and profits. Thus, reproductive efficiency becomes even more cr itical for profitability of grazing than for high producing cows in confinement, as in the latter extended periods of breeding are feasible. Even in gra zing farms using year round production, as cows have less persistent lactation curves than high producing cows in confinement (Boken et al., 2005), extending days open results in greater losses of milk per day of calving interval. A recent survey by Brownl ie et al. (2011) indicated that dairy managers in grazing farms in New Zealand prioritize their management decisions to improve reproductive efficiency, which they reported to have improved in the last 3 years. This demonstrates the importance of reproduct ion for producer in grazing systems. In order to achieve adequate reproductive performance in grazing systems, P/AI must be high, and submission rates are essential (Morton, 2010). In general, detection of estrus and P/AI are higher for grazing cows than for cows under confinement (Lucy et al., 2004). Metabolism is expected to have less impact on steroid clearance because of the less DMI and splanchnic blood flow. Also, maintaining cows on pasture is expected to reduce the incidence and prevalence of lamen ess, thereby improving estrous expression. Nonetheless, the efficiency of detection of estrus in grazing systems also decreases as the herd sizes increases (Morton et al., 2010). Furthermore, 13 to 48% of the cows are anovular at the beginning of the breed ing season, which limits submission to AI or to natural service (Rhodes et al., 2003). Similar to cows in confinement

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83 systems, anovular cows in grazing systems present reduced P/AI, increased pregnancy loss, slower pregnancy rate, longer interval to concep tion, and increased risk of culling (Rhodes et al., 2003; McNaughton et al., 2007). Timed AI programs are, therefore, a reasonable technology to enhance AI submission rate and the proportion of cows pregnant early in the breeding season. In New Zealand, ti med AI has been used more extensively for first insemination of cows not observed in estrus in the weeks preceding the beginning of planed mating season, and implementation of these programs improved reproduction and resulted in economic benefits for estro us cyclic and anovular cows (McDougall, 2010ab). In the New Zealand model, the timed AI protocols utilized are based mostly on progesterone supplementation with intravaginal inserts without presynchronization. Cows presumed to be estrous cyclic are normall y inseminated after detection of estrus for a period of approximately 6 weeks, whereas those not observed in estrus prior to the initiation of the planned mating season receive synchronization of ovulation. After 6 weeks of insemination, bulls are placed w ith cows for another 8 weeks of breeding by natural service. This type of management requires daily detection of estrus before and during the breeding season. By implementing timed AI on the first day of the breeding season, detection of estrus can be rest ricted to target periods such as when most nonpregnant cows are expected to return to estrus. It is known that timed AI is more beneficial than detection of estrus in grazing systems regardless of estrous cyclicity (MacDougall, 2010a). Grazing farms in th e US do not have a standard and well characterized reproductive program, but they normally utilize a combination of AI and natural service

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84 in a breeding period of 9 to 12 weeks (Washburn, 2009). Unfortunately, there is limited information regarding reprodu ctive efficiency in these systems in the US. Nonetheless, Cordoba and Fricke (2001) reported an improvement in reproductive efficiency of grazing dairy cows in seasonal systems in Wisconsin by using timed AI programs at the initiation of breeding season. I nclusion of North America genetics to cattle in New Zealand and other cou n tries to increase the gene pool of the local Holstein Fri esian and to enhance milk yield is a ; it has occurred widely in the last 30 years ( Harris and Kolver, 2001; Royal et al., 2002). This trend in use of superior genetics selected for high milk yield has been blamed for declines in reproductive efficiency in some countries. In grazing farms in the US however, there has not been a clear sep aration among genetic selection for different types of dairy systems. Grazing farms use similar genetics as that used by high producing herds under confinement. Increments in milk production increase the nutrient requirements, which can be critical in past ure only diets. Therefore, it can potentially increase severity and duration of NEB, loss of BCS postpartum, and consequently generate health problems, delay resumption of estrous cyclicity, and compromise reproductive performance. Limited nutrition usuall y has more negative effects on fertility of animals that partition more nutrients toward milk than body reserves. Moreover, supplementation of concentrate for high producing dairy cows in grazing systems may result in increase of milk production without al leviating NE L balance, health and reproduction (Horan et al., 2004; Pedernera et al., 2008; Lucy et al., 2009). When cows of high genetic potential for milk production are used in

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85 grazing systems, then management decisions should consider energy balance an d health as criteria for supplementation, and not only yields of milk and milk components. When selecting cattle for grazing systems, traits other than production alone should be considered. Inclusion of health, longevity, and reproductive traits in genet ic selection is critical component of animal breeding for dairy farms (Harris, 2005). Alternatives to grazing farms include the low producing New Zealand Holstein Friesian or Jersey genetics or incorporation of more productive genetic lines such as North A merican Holstein or Jerseys in crossbreeding programs. Although cows with these types of genetics generally produce less milk, they have greater adaptability to systems of limit nutrient intake (Harris and Kolver, 2001). Studies have reported advantages in energy balance and reproductive parameters of those genetic lineages compared with purebred North American Holsteins (Heins et al., 2008; Lucy et al., 2009). When supplementation is not restricted, incorporating a more productive genotype such as North Am erican Holsteins becomes attractive. Nevertheless, purebred Holsteins are large frame, have greater needs for maintenance, and have larger body size that likely makes walking long distance more demanding on feet and legs. Crossbreeding incorporating US gen etics has the advantage of using potentially more productive cows and incorporating aspects of hybrid vigor, which reduces inbreeding and might benefit production, health, reproduction and survival. Incorporating a three way cross system with 3 different b reeds maximizes hybrid vigor (Hansen et al., 2005). It is generally accepted that grazing cows are healthier than confined cows because their environment is potentially less contaminated, they have access to more exercise, and consume mostly forages (Harr is and Kolver, 2001) However, when

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86 supplementation is attractive, the intake of concentrates by grazing cows might be as high as that of high producing cows in confinement. Furthermore, grazing makes it difficult to protect cows from the elements and, in subtropical and tropical regions, heat stress becomes a major welfare issue that limits performance. In general, little is known about the epidemiology of diseases in grazing farms in the US. Occurrence of diseases in grazing farms associated with lack of diagnosis and treatment may result in significant loss of profitability by reducing milk production and impairing reproductive performance. McDougall (2001a) reported that cows experiencing dystocia or retention of fetal membranes had lower P/AI and slower pregnancy rate than unaffected counterparts. The author suggested that intervention programs to diagnose and treat periparturient diseases may improve reproductive performance of seasonal grazing systems. In a study with only 78 cows, Burke et al. (2010) observed that those with uterine inflammation had delayed resumption of estrous cyclicity. A comprehensive study with 2,793 grazing cows demonstrated that those with mucopurulent or purulent vaginal discharge, diagnosed at 35 days before the planned start of breeding (21.2% of the population), had reduced reproductive efficiency (McDougall et al., 2007). The importance of diagnosis and intervention in problems cows was characterized by McDougall (2001b), in which detection of cows experiencing dystocia, re tained fetal membranes, or uterine diseases and subsequent therapy with intrauterine antimicrobial 3 to 6 weeks before the breeding season improved pregnancy rate.

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87 CHAPTER 3 EPIDEMIOLOGY OF PERI PARTURIENT DISEASES AND THEIR IMPACTS ON FERTILITY OF DAIRY COWS IN SEASONAL GRA ZING FARMS The objectives were to characterize the epidemiology of periparturient diseases and their impacts on reproductive performance of dairy cows in seasonal grazing farms when subjected to timed artificial insemination (AI) at the beginning of the breeding period. A total of 957 multiparous cows were evaluated and incidence of diseases characterized. At calving, dystocia, twin birth, stillbirth, and retained fetal membranes were recorded and grouped as calving problem. On d 7 3 a nd 14 3 postpartum, cows were evaluated for metritis and blood was sampled and analyze d for concentrations of Ca, non hydroxybutirate (BHBA). Cows were considered with severe negative energy balance (SNEB) if NEFA > 700 Serum Ca on d 7 3 postpartum < 8.5 mg/dL was considered as subclinical hypocalcemia. Clinical endometritis was evaluated on d 28 3 postpartum by scoring the vaginal d ischarge. Ovaries were scanned on d 35 3 and 49 3 postpartum for determination of estrous cyclicity. All cows were enrolled in a timed AI program and inseminated on the first day of the breeding season. From parturition until 30 d after AI, incidence o f mastitis, lameness, and digestive and respiratory problems were recorded. Pregnancy diagnoses were performed 30 and 65 days after AI. Overall, 37.5% of the cows presented at least one clinical disease and 59.0% had at least one subclinical health problem Incidence of individual diseases was: 8.5% for calving problem 5.3% for metritis 15% for clinical endometritis 15.3% for mastitis 2.5% for respiratory problems 4.0% for digestive problems 3.2% for lameness 20.0% for SNEB 35.4% for subclinical ket osis and 43.3% for subclinical hypocalcemia Clinical and subclinical

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88 diseases had additive negative impacts on reproduction, delaying resumption of estrous cyclicity and reducing pregnancy per AI (P/AI). Individually, subclinical hypocalcemia, SNEB, metr itis, and respiratory and digestive problems reduced estrous cyclicity by d 49 postpartum. Severe NEB, calving problem, metritis, clinical endometritis and digestive problem reduced P/AI on d 65 after AI. Moreover, calving problems and clinical endometriti s increased the risk of pregnancy loss between gestation d 30 and 65. Concentrations of Ca and NEFA were negatively correlated and associated with incidence of metritis. In conclusion, postpartum diseases were prevalent in seasonal grazing dairies and they were associated with delayed resumption of estrous cyclicity, reduced P/AI, and increased risk of pregnancy loss. Management of grazing cows to optimize fertility should focus on reducing periparturient diseases and lipid mobilization and improving Ca hom eostasis. Introduct ory Remarks Seasonal calving is often used in grazing dairy farms to maximize pasture nutrient utilization and avoid temporary environmental constrains such as heat stress during early lactation and the breeding period. In this type of d airy production system, reproductive efficiency is essential to obtain a concentrated calving season o n a yearly basis (McDougall and Compton, 2006). Cows must become pregnant in a short and pre established period of time, which has a calendar day to begin for all cows irrespective of individual calving date. T o achieve adequate reproductive performance, high submission rate and pregnancy per artificial insemination (P/AI) are mandatory (Morton, 2010). Thus, cow and management factors that compromise these parameters should be minimized. Although estrous detection may not be a major problem in grazing farms 13 to 48% of cows are anovular at the beginning of the breeding season, which

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89 limits submission to artificial insemination ( AI ) after detection of estru s (Rhodes et al., 2003). The adoption of timed AI programs maximizes submission rates, but conception of anovular cows are still poor (McDougall, 2010; Ribeiro et al., 2011). Moreover, factors such as extensive loss of body condition (BCS) and postpartum h ealth problems have been implicated with extended anovulation period, smaller P/AI and greater risk of pregnancy losses (Santos et al., 2009, 2010b). Therefore, minimizing anovulation, loss of BCS and health problems become cornerstones to achieve high rep roductive efficiency in dairy herds. It is a general consensus that energy balance of dairy cows in early postpartum is linked with reproduction (Butler, 2003; Chagas et al., 2007), which in turn is mainly determined by caloric intake (r 2 = 0.57; Santos e t al., 2010b). Dietary caloric intake is of special concern in grazing farms as nutrient supply by pasture only diets is ofte n limited, especially when genetics from high producing cows not selected for production under grazing are used (Kolver, 2003). Eve n when concentrate is supplied, high producing cows may increase milk production without alleviating the extent and duration of negative energy balance (NEB) and loss of BCS (Pedernera et al., 2008; Lucy et al., 2009). Recent studies have linked NEB postpa rtum and metabolic disorders with compromised immune cell functions (Grinberg et al., 2006; Hammon et al., 2006; Kimura et al. 2010). This relationship might partially explain the immune suppression observed in lactating dairy cows in early postpartum (Keh rli et al., 1989) Incidence and severity of health problems vary, but they are normally associated with reduced appetite (Drackley, 1999) which further compromises energy balance, resulting a vicious cycle that impair lactation and reproduction (Drackley 1999; Santos et al., 2010b).

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90 E ffects of anovulation and loss of BCS have been well characterized in grazing dairy herds (Rhodes et al., 2003), but there is little information on the incidence and prevalence of postpartum health problems and their impact s on reproduction. It is generally accepted that grazing cows are more fertile and healthier than high producing cows in confinement dairies (Harris and Curris, 2001; Lucy et al., 2004). Also, management practices to prevent, detect and treat postpartum he alth problems do not seem to be as strict as commonly used in high producing herds. Because grazing dairy cows likely experience nutrient deficit postpartum, they also likely become susceptible to health problems, which might be masked at least partially b y lack of diagnosis. Occurrence of diseases associated with lack of diagnosis and treatment may impair reproduction and result in significant economic loss to producers, particularly given the importance of reproductive efficiency in grazing dairy farms (M cDougall, 2001a). Therefore, the objectives of this study were to characterize the epidemiology of periparturient clinical and subclinical diseases and their impact on resumption of estrous cyclicity, P/AI, and pregnancy loss of grazing dairy cows (North American genetics) in seasonal grazing dairy farms subjected to timed AI at first day of breeding season. The hypotheses of the present study were that incidence of clinical an d subclinical diseases would be relatively high in seasonal grazing systems and that diseases would compromise reproduction of dairy cows. M aterials and M ethods Cows, Pastures and Management The study was conducted in two commercial grazing dairy farms located in Florida. Both were fall/winter calving herds with similar genetics and m anagement practices. The average milk production per cow was approximately 6,000 kg/lactation. A total of

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91 957 lactating multiparous dairy cows (255 Holsteins, 88 Jerseys, and 614 crossbreds) were enrolled. Crossbred cows population was mostly composed by F 1 (50/50) and F2 (25/75) generation of crossbreeding between Holstein and Jersey genetics. Different genetic groups were managed together in a pasture based system in both herds and North American genetics was used. Cows were maintained under irrigated pas ture paddocks of 2.7 ha and managed in a daily rotational method with a stocking rate of approximately 10 cows/ha. The pasture was composed by annual ryegrass ( Lolium multiflorum Lam. ( Cynodon s pp ) during late spring and summer. Cows were offered variable amounts of concentrate (7 to 13 kg/cow/d) during and immediately after each milking according to forage availability and stage of lactation. The concentrate was based on soybean hulls, citrus pu lp, whole cottonseed, cottonseed hulls, corn gluten feed, corn meal, soybean meal, molasses, and a mineral vitamin premix, and designed to contain approximately 15% of crude protein 4.5% of fat, and 28% of neutral detergent fiber Cows were milked twice d aily. Characterization and Diagnosis of Health Problems At calving, dystocia characterized by assisted calving, twin birth, stillbirth, and retained placenta characterized by presence of fetal membranes the day after calving were recorded and grouped as c alving problem. Cows were evaluated for metritis on d 7 3 and 14 3 postpartum by transrectal palpation, and it was characterized by an enlarged uterus with fetid watery red brown vaginal discharge (Sheldon et al., 2006). Cows with metritis had their re ctal temperature measured and those with temperature > 39.5C were classified as having puerperal metritis. Clinical endometritis was evaluated on d 28 3 postpartum by scoring the vaginal mucus using a vaginal mucus collection

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92 device (Metricheck, Simcro, New Zealand). Mucus was scored in a scale from 0 to 5 as described previously by McDougall et al. (2007), and score > 2 was considered clinical endometritis. From parturition until d 30 after the first postpartum AI, incidence of mastitis, digestive, resp iratory and lameness problems were also evaluated for all cows. At every milking all cows were examined for signs of clinical mastitis by the herd personnel immediately before milking. Clinical mastitis was characterized by the presence of abnormal milk or by signs of inflammation in one or more quarters. Digestive problems were characterized by diarrhea, bloat, or displacement of abomasum. Cows that stood and walked with arched back and to have short strides in one or more legs were classified as clinicall y lame. Blood was sa mpled from 771 cows on d 7 3 and 14 3 postpartum by puncture of the coccygeal vein or artery and blood collection into evacuated tubes with no additives (Becton Dickinson, Franklin Lakes, NJ). Blood samples were maintained at ambien t temperature for 30 min for clotting and then placed in ice and transported to the laboratory within 5 h of collection. Tubes were centrifuged at 2,000 g for 15 min for serum separation. Serum samples were frozen at 20C and later ana lyzed for concentr ations of non hydroxybutyrate (BHBA), and total Ca. Concentrations of NEFA were determined according Johnson and Peters (1993) using the NEFA C kit (Wako Diagnostics, Inc., Richmond, VA). Concentrations of BHBA were determin ed using the kit Wako Autokit 3 HB (Wako Diagnostics, Inc., Richmond, VA) according to manufacturer instructions. C oncentrations of Ca were determined by atomic absorption spectroscopy (AANALYST 200, PerkinElmer, Inc.). Cows were considered in severe NEB ( SNEB)

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93 BHBA > 10 mg/dL in at least one of the two samples (Ospina et al., 2010). Calcium was analyzed only for the first week postpartum (d 7 3) and subclinical hypocalcemia was characterized as concentratio n of Ca < 8.5 0 mg/dL (Martinez et al., 2011 ). These cut points were determined in the referred studies as the best values to predict incidence of clinical diseases postpartum. Retention of fetal membranes, metritis, clinical endometritis, mastitis, digesti ve problems, respiratory problems, lameness, and death not associated with one of the previously mentioned clinical diseases were all grouped as clinical diseases. Severe NEB, subclinical ketosis, and subclinical hypocalcemia were all grouped as subclinica l diseases. Health of cows was further categorized as : health y, with no diagnosis of disease; a single disease, when a single disease was diagnosed; or multiple diseases when more than 1 disease was diagnosed. These categories were applied three times, con sider ing only clinical, only subclinical or both health problems. Cows having diagnosis of both clinical and subclinical problems were also classified based on morbidity as : healthy with no clinical or subclinical disease; only subclinical; only clinical; or both clinical and subclinical diseases. Reproductive Management All cows were enrolled in a presynchronized timed AI program for first postpartum insemination according to preplanned breeding season despite days postpartum. Cows received 2 injections of 25 mg of prostaglandin ( PG ) F (Lutalyse sterile solution; 5 mg/mL of dinoprost tromethamine, Pfizer Animal Health, Madison, NJ ) administered 14 d apart and timed AI protocol started 10 d after the second PGF The 5 d timed AI protocol (Santos et al., 2010) was used and consisted o f an injection of 100 g of gonadotropin releasing hormone ( GnRH ; Cystorelin; 50 g/mL of gonadorelin diacetate

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94 tetrahydrate, Merial Ltd., Inselin, NJ) on d 0 of the protocol, followed by an injection of PGF on d 5 and 6, and induction of ovulation with GnRH concurrently with timed AI on d 8. T ailheads were painted using paintsticks (All Weather Paintstick; LA CO Industries, Chicago, IL) on day 6 of the timed AI protocol for detection of signs of estrus on the day of AI. Estrus was characterized by remova l of tailpaint. All cows were timed inseminated regardless of estrous expression. Determination of Estrous Cyclicity Pregnancy Diagnoses and Body Condition Scoring Ultrasonographic examinations of the ovaries were performed using a 7.5 MHz linear transrec tal transducer (Easy Scan, BCF Technology, Livingston, UK) for presence of a corpus luteum ( CL ) on days 35 3 and 49 3 postpartum. Cows were classified as estrous cyclic on d 49 if a CL was observed in at least one of the two examinations, or as anovula r if no CL was observed in both examinations. Pregnancy was diagnosed in all cows on d 30 after AI via transrectal ultrasonography of the uterus and its contents, and was characterized by visualization of a live embryo. Cows diagnosed as pregnant on d 30 were reexamined by transrectal palpation 35 d later. Pregnancy per AI was calculated as the number of pregnant cows on d 30 and 65 after an insemination divided by the total number of cows inseminated. Pregnancy loss was calculated as the number of cows th at lost pregnancy between gestation d 30 and 65 divided by the number of pregnant cows on d 30. Cows were scored for body condition in a 1 to 5 scale (1= emaciated, 5= obese; Ferguson et al., 1994) at 7 and 35 d postpartum, and again at AI and 30 d after AI.

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95 Statistical Analyses Binary data were analyzed by logistic regression using the LOGISTIC procedure of SAS version 9.2 (SAS/STAT, SAS Institute Inc., Cary, NC, USA). Fertility responses of interest were estrous cyclicity on d 49 postpartum, estrus at A I, P/AI on d 30 and 65 after insemination, and pregnancy loss. All multivariate logistic regression models included the effects of farm and breed of cow. Initially, fertility responses were analyzed with each individual clinical and subclinical health pro with P < 0.15 were used to build multivariate logistic regression models. T o evaluate the impact of clinical diseases on fertility of grazing cows, data were analyzed with multivariate logist ic regression with cows classified as having no disease, a single disease, or multiple diseases. In addition, data were also analyzed with each individual clinical disease selected from the univariate analysis. Similarly, to evaluate the impact of subclini cal diseases on fertility, data were analyzed with multivariate logistic regression with cows classified as having no subclinical disease, a single subclinical disease, or multiple subclinical diseases. Additional multivariate analyses were performed with both clinical and subclinical diseases included in the same models. Cows were classified as healthy when no clinical or subclinical disease was diagnosed, or as having subclinical disease only, clinical disease only, or both clinical and subclinical diseas es in the same cow. Contrasts were performed to determine the impact on disease, and the additive impact of having both clinical and subclinical disease as oppose d to each either one of the two. For uterine disease in particular, multivariate logistic reg ression models were built with cows classified as having no clinical uterine disease, clinical endometritis only,

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96 metritis only, or both clinical endometritis and metritis in the same cow. Contrasts were performed to determine the impact on uterine disease and the additive impact of having both clinical endometritis and metritis as oppose to each disease individually. The GLIMMIX procedure of SAS was used for analyses of concentrations of NEFA, BHBA, and Ca in serum. Concentrations were analyzed for each individual clinical and subclinical disease and models included the fixed effect of breed of cow and the random effect of farm. Similar analyses were performed using the reproductive outcomes for estrous cyclic ity on d 49 estrus at AI, pregnant on d 30 and 65 after AI and pregnancy loss as independent variables The CORR procedure of SAS was used to determine correlations among serum Ca, NEFA, BHBA, BCS on d 7 and 35 postpartum, and BCS change in the first 35 d postpartum. Differences with P P considered tendencies. R esults Clinical and subclinical diseases were prevalent in postpartum grazing dairy cows (Table 3 1). Overall, 37.5% of the cows presented at least one clinical health pro blem and 59.0% at least one subclinical health problem. The mean (SD) and median d ay postpartum at diagnosis of the first case of clinical disease were 29.0 29.1 and 28.0, respectively. Of the clinical diseases evaluated, clinical endometritis and masti tis were the most prevalent. Of the subclinical diseases evaluated, hypocalcemia was the most prevalent, affecting 43.3% of the cows in the first 10 d postpartum. Only 27.0% of the cows were not diagnosed with either a clinical or subclinical disease postp artum (Table 3 1). Dystocia, twins, stillborn and retention of fetal membranes affected, respectively,

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97 1.4, 1.8, 4.4, and 3.2% of the cows in the study, which resulted in 8.5% of them classified as having calving problems. Cows with subclinical hypocalcemi a were more likely ( P = 0.03) to have metritis (4.0 vs. 7.9%) and tend ed ( P = 0.09) to be more likely to have clinical endometritis (13.3 vs. 18.1%). Additionally, cows with subclinical hypocalcemia were also more likely ( P < 0.01) to be classified also as having SNEB (16.2 vs. 27.5%) and subclinical ketosis (35.3 vs. 41.9%). Incidence of calving problems increased ( P < 0.01) the probability of metritis (3.00 vs. 30.9%) and clinical endometritis (13.4 vs. 34.7%), and cows with metritis also had greater ( P < 0.01) incidence of clinical endometritis (12.9 vs. 55.1%). Of all cases of metritis, 52.9% presented hyperthermia and were classified as puerperal metritis. Morbidity for clinical diseases was not affected ( P = 0.62) by breed of cows (Holstein = 40.0% vs Jersey = 37.5% vs. crossbred = 36.5%). Nevertheless, the incidence of some individual diseases differed with breed (Table 3.1) Holstein cows had greater ( P < 0.01) incidence of twins than crossbred and Jersey cows. Moreover, Holstein cows also had great er ( P < 0.01) incidence of mastitis, but smaller ( P = 0.05) incidence of clinical endometritis than crossbred and Jersey cows (Table 3.1) On the other hand, Jersey cows had greater ( P = 0.02) incidence of lameness than Holstein and crossbred cows. For sub clinical diseases, crossbred cows had greater ( P < 0.0 1 ) morbidity than Holstein cows (60.3 vs. 57.1%), and both did not differ ( P = 0.22) from that of Jersey cows (56.1%). Among the subclinical health problems evaluated, breed did not affect ( P > 0.25) th e proportion of cows with SNEB or hypocalcemia, but

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98 crossbred cows were more likely to experience subclinical ketosis than Holstein cows ( P = 0.01), but not Jersey ( P = 0.12; Table 3.1) The mean (SD) and median d ay postpartum at first AI were, respectiv ely, 86.015.1 and 83. From calving until first AI, 11.5% of cows enrolled in the study left the herd either because of death (2.6%) or culling (8.9%). Breed of cow did not influence the proportion of cows leaving the herd before first AI; however, a great er ( P < 0.01) proportion of cows having clinical disease left the herd than cows not diagnosed with clinical disease (20.6 vs. 6.0%). Estrous Cyclicity Diseases influenced estrous cyclicity at 49 d postpartum (Table 3 2). Cows considered as healthy were more likely ( P < 0.05) to be estrous cyclic than cows with at least one clinical or subclinical disease. Among cows with diseases, those having both clinical and subclinical had lower probability ( P = 0.02) of being estrous cyclic than cows with clinical d isease only. When only clinical diseases were considered, estrous cyclicity was reduced ( P < 0.01) in cows diagnosed with more than one health problem, but not in those with a single health problem (Table 3 3). Cows with multiple clinical diseases were les s likely ( P = 0.02) to be estrous cyclic than those with a single disease. Among the clinical diseases that influenced resumption of estrous cyclicity by 49 d postpartum were metritis, respiratory and digestive problems. When only subclinical diseases were considered, an incremental decline in the prevalence of estrous cyclicity at 49 d postpartum was observed with increasing number of diseases. Of the subclinical diseases evaluated, estrous cyclicity was reduced ( P < 0.01) in cows with SNEB and subclinical hypocalcemia. Estrous cyclicity on d 49 was affected by breed, and Holstein

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99 cows had a smaller proportion of estrous cyclic cows than crossbreds ( P < 0.01), but not than Jerseys (Holstein = 83.1 vs. Jersey = 88.5 vs. crossbred = 91.7%). Pregnancy per AI a nd Pregnancy Loss Sixty two percent of the cows were pregnant on d 30 after AI, and this proportion decreased to 54.7% on d 65 after AI. Diseases influenced P/AI on d 30 and 65 after insemination (Table 3 2). Cows considered as healthy had greater ( P < 0.0 5) P/AI on d 30 and 65 than cows diagnosed with subclinical disease only, clinical disease only, or both clinical and subclinical disease. An additive effect ( P < 0.05) of clinical and subclinical disease was observed for P/AI on d 30 in which cows with on ly subclinical or only clinical disease had greater P/AI than those with both diseases. When only clinical diseases were considered, then P/AI on d 30 and 65 suffered an incremental decline ( P < 0.01) with increasing number of diseases (Tables 3 4 and 3 5) Among clinical diseases that affected ( P < 0.05) P/AI on d 30 were metritis and digestive problems. On d 65 after insemination, calving problems, metritis, clinical endometritis, and digestive problems all reduced ( P < 0.05) P/AI. When subclinical diseas es were considered, then P/AI on d 30 and 65 were only reduced ( P < 0.01) in those cows diagnosed with more than one disease (Tables 3 4 and 3 5). Of the subclinical diseases, only SNEB reduced ( P < 0.01) P/AI. Anovular cows on d 49 postpartum had smaller ( P < 0.001) P/AI on d 30 (36.8 vs. 64.9) and 65 (33.7 vs. 57.1%) after AI than counterparts estrous cyclic cows. Breed had no effect ( P > 0.10) on P/AI on d 30 and 65 after insemination. On d 65, 48.3% of Holsteins, 53.2% of Jerseys, and 57.7% of crossbre ds were pregnant. Pregnancy loss affected 10.9% of the pregnant cows. Cows with multiple clinical diseases had greater ( P < 0.01) pregnancy loss than healthy cows and than those with

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100 a single clinical disease (Table 3 6). Calving problem and clinical endo metritis increased ( P < 0.02) pregnancy loss in the first 65 d of gestation. No association was observed between subclinical disease and pregnancy loss. Breed of cows did not influence ( P = 0.72) pregnancy loss, and 11.2% of Holsteins, 10.6% of Jerseys, an d 10.9% of crossbreds lost their pregnancies between 30 and 65 d after AI. Uterine Diseases and Fertility On d 30 after AI, healthy cows had greater ( P < 0.05) P/AI than cows with at least one uterine disease (63.9 vs. 53.1%). Healthy cows tended ( P = 0.06 ) to have P/AI greater than those with metritis only and had greater ( P < 0.01) P/AI than those with both metritis and clinical endometritis (Table 3 7). Similar to d 30, P/AI on d 65 was greater ( P < 0.05) for healthy cows than those with uterine disease For cows with uterine disease, having both metritis and clinical endometritis had an additive suppressive effect ( P < 0.05) on P/AI, and it was 18.2% for cows having both diseases compared with 44.9% for cows having either one of the two diseases. As for P/AI, diseases affecting the uterus of cows also influenced pregnancy loss, which increased ( P < 0.05) despite the type of uterine disease. Concentrations of NEFA, BHBA, and Ca in Serum of Grazing Cows Concentration of NEFA in serum was greater ( P = 0.02) for cows with metritis than those without metritis (Table 3 8). Cows with subclinical ketosis and hypocalcemia had greater ( P < 0.01) concentrations of NEFA than those without the respective subclinical diseases. Cows with calving problem and those with l ameness had smaller ( P < 0.01) concentrations of BHBA than their herdmates without those diseases. Cows with SNEB and subclinical hypocalcemia had greater ( P < 0.05) concentrations of BHBA than those without the respective subclinical diseases. Concentrati ons of serum Ca were smaller

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101 ( P < 0.04) for cows with metritis and clinical endometritis. Cows with SNEB and subclinical ketosis had smaller ( P < 0.01) concentrations of Ca than those without the respective subclinical diseases. Correlation among the serum concentrations of Ca, NEFA, BHBA, BCS on d 7 and 35, and BCS change from d 7 to 35 are presented on Table 3 9. Calcium was negatively correlated with NEFA and BHBA, and positively correlated with BCS on d 7 and 35. Moreover, NEFA was positively correlated with BHBA and BCS on d 7, but negatively correlated with BCS on d 35 and change in BCS. As the change in BCS went from negative (cows losing BCS) to positive values (cows gaining BCS), serum NEFA concentrations decreased. Similarly, BHBA was also positive ly correlated with BCS on d 7, and negatively correlated with BCS on d 35 and change in BCS. As the change in BCS went from negative to positive values, serum BHBA concentrations decreased. Cows that were estrous cyclic on d 49 postpartum had greater ( P < 0.01) concentrations of Ca and smaller ( P = 0.02) concentrations of NEFA than anovular cows (Table 3 10). Concentration of NEFA was smaller ( P < 0.01) for cows that were pregnant on d 30 and 65 after AI than in nonpregnant cows. Although concentration of BHBA was smaller ( P = 0.04) for pregnant than open cows on d 30, it did not differ according to pregnancy evaluated on d 65 after AI. Concentration of Ca was not different between pregnant and non pregnant cows. Moreover, the concentrations of NEFA, BHBA, and Ca were different for cows experiencing or not pregnancy loss. D iscussion This study aimed to characterize the epidemiology of clinical and subclinical periparturient diseases and their impacts on reproduction of dairy cows in seasonal grazing farms. M ilk production is generally lower in grazing than confinement cows, and

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102 grazing dairy cows are generally considered more fertile and healthier than high producing dairy cows in confinement farms (Harris and Curris, 2001; Lucy et al., 2004). Nonetheless, th e present study demonstrates that incidences of clinical and subclinical health problems were relatively high in grazing dairy in the two farms studied. Furthermore, despite the high fertility observed following first AI, cows diagnosed with either clinica l or subclinical diseases had reduced prevalence of estrous cyclicity on d 49 postpartum and P/AI after the first AI, and increased risk of pregnancy loss. Surprisingly, only 27% of the cows did not experience any type of health problem, and in these cows estrous cyclicity on d 49 and P/AI on d 30 were both high, being 95.6 % and 73.5%, respectively. Similar to our findings, Santos et al. (2010b) observed a high prevalence of clinical diseases in high producing cows. Approximately 44.2% of the 5,719 high producing cows in 7 confinement farms were diagnosed with at least one clinical disease in the first 60 d postpartum. For cows without clinical diseases, 84.1% resumed estrous cyclicity by d 65 postpartum and 51.4% became pregnant at first AI. Therefore, i t is clear that despite of type of dairy production system, grazing or confinement, postpartum health is critical for adequate reproductive performance. It is unquestionable that the transition period is critical for health and survival of dairy cows. Of all the cows that leave a dairy farm because of culling or death, almost 12% do so in the first 3 weeks postpartum, and 24% in the first 2 months of lactation (Godden et al., 2003). These cows represent a major economic loss to the producer as culling and death in early lactation compromises lifetime milk production of a cow. Delivery of a calf with consequent risks for dystocia and uterine diseases (McDougall, 2001a; Sheldon et al., 2009), peripartum immune suppression (Hammon et al., 2006),

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103 changes in dry matter intake (Drackley, 1999; Hammon et al., 2006), nutrient imbalance (Kimura et al., 2006), and contaminated environment (LeBlanc et al., 2006) are major risk factors leading to the occurrence of health problems in this period. In a survey of 2,363 dai ry cows in 55 confinement herds in different regions of the US and Canada (Chapinal et al., 2011), the incidences of twin births, dystocia, retained fetal membranes, clinical hypocalcemia, metritis an d displacement of abomasum were 3.5%, 11.3%, 7.4%, 2.4%, 16.7%, and 3.6% respectively Although dairy producers have become more conscientious about feeding and management of transition cows in recent years (LeBlanc et al., 2006), many still neglect the importance of this period, which result in herds with hig h incidence of health problems. In grazing farms energy balance can be of great concern because of low dry matter intake and the typically less caloric dense diets consumed by cows (Kolver, 2003). Resumption of postpartum estrous cyclicity is directly li nked with the nutritional status of the cow (Butler, 2003). Cows suffering from more severe negative energy balance have delayed first postpartum ovulation, which compromises fertility (Butler, 2003). Similarly, cows that experience greater losses of BCS h ave extended anovulatory period, decreased P/AI and increased risk of pregnancy loss (Santos et al., 2009). It is important to emphasize that all cows used in this study were of North American genetics, which in general partition more nutrients toward milk production at the expense of body reserves compared with New Zealand genetics (Lucy et al., 2009). Nonetheless, t here were three distinct genetic groups with expected differences in milk yields : greater for Holstein, intermediary for crossbreds and small er for Jersey I nterestingly, no major differences o n the incidence of diseases were observed among

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104 them Crossbreed cows has better reproductive performance in seasonal grazing farms than Holstein cows (Ribeiro et al., 2010, 2011) I n the present study a greater proportion of crossbred cows were estrous cyclic cows by d 49 compared with Holstein cows but P/AI did not differ between the two genetic groups Thus, differences in resumption of estrous cyclicity and P/AI observed in previous studies do not se em to be related to differences in incidence of diseases among breeds It is likely that additional factors such as differences in ovarian steroid hormone metabolism nutrient partitioning and hybrid vigor favor reproductive efficiency of crossbred cows. Diseases have been linked with a delay in postpartum estrous cyclicity (Santos et al., 2010b). In the current study, clinical and subclinical diseases were associated with estrous cyclicity and they both increased the prevalence of anovular cows on d 49 p ostpartum. Cows with SNEB and those with subclinical hypocalcemia had smaller incidence of estrous cyclic cows by 49 d postpartum. High serum NEFA concentrations are indicator of lipid mobilization and body weight loss (Drackley, 1999). Cows with severe lo ss of body fat are usually under a more negative nutrient balance, which would likely also affect Ca balance. In fact, serum concentrations of NEFA and Ca were negatively correlated, indicating that as NEFA increased, serum Ca decreased. This is expected a s cows with less dry matter intake and greater nutrient output in milk are expected to have increased body fat mobilization and reduced serum Ca concentrations. Similar to our finds, Reinhardt et al. (2010) also reported high incidence (47%) of subclinical hypocalcemia in multiparous cows, and those with hypocalcemia had higher concentrations of NEFA for than those with normocalcaemia. Moreover, the composition of the follicular fluid reflects in part that of blood plasma, and changes in

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105 metabolites in bloo d also influence the respective metabolites in the follicle (Leroy et al., 2008). Cows with delayed estrous cyclicity had greater concentrations of serum NEFA, and the latter has been shown to negatively influence follicular steroidogenesis and oocyte dev elopmental competence in vitro (Leroy et al., 2008). As expected, cows diagnosed with metritis were less likely to be estrous cyclic than those not having metritis. Cows with uterine diseases are known to experience delayed postpartum ovulation (Sheldon et al., 2009), and it is thought that bacteria and products of inflammation from the uterus influence follicle growth and steroidogenesis in early lactation (Sheldon et al., 2009). Reproductive efficiency is critical for the sustainability of grazing dairy farms. In seasonal dairy production, cows that become pregnant early in the breeding season also calve early in following calving season, which assures a longer lactation and more days for resumption of positive energy balance and estrous cyclicity until i nitiation of the following breeding season. Collectively, early pregnancy on a breeding season usually improves reproductive performance in the subsequent season (McDougall and Compton, 2006; Ribeiro et al., 2011). In order t o optimize pregnancy early in t he breeding period, submission rate and P/AI should be high. Synchronization programs can override the negative effect of anovulation on submission rate, but not on P/AI (Santos et al., 2009; McDougall, 2010). Cows in the current study were all subjected t o timed AI for first insemination, so submission rate was 100% despite cyclic status or periparturient problems. Nevertheless, P/AI was markedly reduced in cows suffering from clinical and subclinical health problems. It was observed that

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106 presence of clinical and subclinical diseases had additive negative effects on fertility of dairy cows. In general, diseases that affected the uterus had the greatest impact on P/AI. Indeed, metritis and clinical endometritis had additive effects reducing P/AI and resulting in the greatest pregnancy loss. McDougall (2001a) reported that cows with dystocia or retention of fetal membranes had lower P/AI and slower pregnancy rate than unaffected counterparts. A comprehensive study with 2,793 grazing cows demo nstrated that clinical endometritis affected 21.2% of the population and reduced reproductive efficiency during the breeding season (McDougall et al., 2007). Intrauterine antibiotic treatment with cephapirin has been demonstrated to be an effective alterna tive to improve reproductive efficiency of cows experiencing uterine health problems postpartum in seasonal grazing farms (McDougall, 2001b). In fact, a fter parturition, almost all cows have a uterus contaminated by a wide range of bacteria, and the develo pment of uterine diseases depends of the ability of the local immune system to control bacterial growth (Sheldon et al., 2009). Development of u terine diseases compromises restoration processes during uterine involution and uterus physiology, and might hav e carry over effects until later stages of lactation, compromising not only pregnancy establi shment but also its maintenance a s observed in the present study Hammon et al. (2006) reported that impaired neutrophil function and NEB before parturition were a ssociated with uterine diseases in early lactation In fact, cows with metritis in th e current study had greater concentrations of NEFA and smaller of Ca in the first 10 d postpartum. Kimura et al. (2010) demonstrated that store of intracellular Ca and act ivation responses of peripheral mononuclear cells are reduced in

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107 periparturient cows developing clinical hypocalcemia, suggesting that low Ca concentrations during the peripartum may contribute to impaired immune cell function. Thus, Ca homeostasis and ene rgy balance are interrelated and both affect immune cell function, which increase the susceptibility of cows to developed clinical diseases by the incidence of hypocalcemia and SNEB. Summary Incidence of postpartum clinical and subclinical health problems in grazing dairy cows in the two herds studied w as high and associated with resumption of estrous cyclicity P/ AI, and pregnancy loss. In general, diseases reduced the prevalence of estrous cyclic cows 49 d postpartum, reduced P/AI on d 30 and 65 after th e first insemination, and increased the risk of pregnancy loss. As the number of clinical diseases diagnosed per cow increased, fertility declined in a parallel manner. The decline in fertility was caused by reduced P/AI and increased pregnancy loss. Simil arly, cows with multiple subclinical diseases had marked suppression in P/AI. When combined, subclinical and clinical diseases had additive negative effects on fertility of dairy cows. Uterine diseases were prevalent and both metritis and clinical endometr itis depressed fertility. Interestingly, cows having both uterine diseases suffered more than those having either one of the two. In summary, although P/AI was high in the two herds studied, this study demonstrates that periparturient clinical and subclini cal diseases are highly prevalent in grazing dairy cows and, as observed in high producing cows in confinement, they delay estrous cyclicity, reduce P/AI and increase the risk of pregnancy loss. Management of grazing cows to optimize fertility should focus on reducing periparturient diseases and lipid mobilization and improving Ca homeostasis.

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108 Table 3 1. Incidence of clinical and subclinical diseases in early postpartum grazing dairy cows Health problem Overall i ncidence, % Incidence according breed, % Holstein Crossbred Jersey P Clinical disease (n = 957) Healthy 62.5 60.0 63.5 62.5 0.62 Single clinical disease 26.7 29.0 26.4 22.7 0.49 Multiple clinical diseases 10.8 11.0 10.1 14.8 0.40 Type of clinical disease Calving p roblem 8.5 9.8 7.8 9.1 0.90 Metritis 5.3 4.3 5.5 6.8 0.79 Clinical endometritis 15.0 11.7 a 15.8 b 19.3 b 0.05 Mastitis 15.3 22.0 a 12.9 b 12.5 b <0.01 Respiratory problem 2.5 2.4 2.3 4.6 0.14 Digestive problem 4.0 3.9 4.2 2.3 0.41 Lamene ss 3.2 3.9 a 2.3 a 8.0 b 0.02 Subclinical disease (n = 771) Healthy 41.0 42.9 a 39.7 b 43.9 a b 0.01 Single subclinical disease 33.2 25.8 a 36.7 b 31.8 a b 0.02 Multiple subclinical disease 25.8 31.3 23.6 24.3 0.62 Type of subclinical disea se 1 SNEB 20.0 25.8 18.2 13.6 0.56 Subclinical ketosis 35.4 40.1 a 33.4 b 34.9 ab 0.03 Subclinical hypocalcemia 43.3 35.2 46.7 49.1 0.27 Clinical and subclinical health problems (n = 771) Healthy 27.0 26.7 26.4 31.8 0.13 Single disease 32.7 29.5 34.8 27.3 0.49 Multiple diseases 40.3 43.8 38.7 40.9 0.38 1 SNEB = severe negative energy balance based on serum NEFA > ketosis based on serum BHBA > 10 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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109 Table 3 2. Impact of clinical and/or subclinical diseases on estrous cyclicity on d 49 postpartum and pregnancy per artificial inseminat ion (AI) on d 30 and 65 after AI Estrous cyclic AOR ( 95% CI) 1 P AOR ( 95% CI) P AOR ( 95% CI) P Healthy 95.6 a 1.00 ----------Subclinical disease only 88.9 b,c 0.35 (0.16 0.76) <0.01 1.00 ------Clinical disease only 93.0 a,b 0.63 (0.23 1.7 5) 0.37 1.78 (0.75 4.21) 0.19 1.00 --Subclinical and clinical disease 83.5 c 0.23 (0.10 0.50) <0.01 0.65 (0.37 1.14) 0.13 0.36 (0.15 0.88) 0.02 Pregnant d 30 *, AOR ( 95% CI) P AOR ( 95% CI) P AOR ( 95% CI) P Healthy 73.5 a 1.00 ---------Subclinical disease only 63.1 b 0.67 (0.44 0.99) 0.05 1.00 ------Clinical disease only 54.8 b,c 0.44 (0.26 0.75) <0.01 0.66 (0.40 1.09) 0.11 1.00 --Subclinical and clinical disease 50.0 c 0.39 (0.24 0.61) <0.01 0.58 (0.38 0.87) 0.03 0.87 (0.51 1 .51) 0.63 Pregnant d 65 *, AOR ( 95% CI) P AOR ( 95% CI) P AOR ( 95% CI) P Healthy 66.2 a 1.00 ----------Subclinical disease only 57.1 a,b 0.72 (0.49 1.05) 0.09 1.00 ------Clinical disease only 46.3 b,c 0.45 (0.26 0.76) <0.01 0.62 ( 0.38 1.03) 0.06 1.00 --Subclinical and clinical disease 42.1 c 0.39 (0.25 0.61) <0.01 0.54 (0.36 0.82) <0.01 0.87 (0.50 1.51) 0.62 a,b,c Superscripts within a day of pregnancy differ ( P < 0.05). Contrasts: Effect of uterine disease (Healthy vs. all o thers) P < 0.05; Additive effect of clinical and subclinical diseases (subclinical disease only + clinical disease only vs. subclinical and clinical disease) P < 0.05. 1 AOR = adjusted odds ratio; CI = confidence interval.

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110 Table 3 3. Impact of postpartu m diseases on resumption of estrous cyclicity by d 49 postpartum Univariate analysis Multivariate analysis Health problem Cyclic,% OR ( 95% CI) 1 P AOR ( 95% CI) 2 P Clinical disease Healthy 91.1 1.00 --1.00 --Single clinical disease 88.3 0.74 (0.45 1.20) 0.22 0.75 (0.46 1.22) 0.25 Multiple clinical diseases 77.8 0.34 (0.19 0.61) <0.01 0.35 (0.20 0.62) <0.01 Type of clinical disease 3 Calving problem 84.5 0.65 (0.33 1.27) 0.21 ----Metritis 78.7 0.43 (0.21 0.89) 0.02 0.3 7 (0.18 0.79) 0.01 Clinical endometritis 89.1 1.00 (0.56 1.80) 0.99 ----Mastitis 88.3 0.92 (0.52 1.62) 0.77 ----Respiratory problem 63.6 0.20 (0.08 0.49) <0.01 0.21 (0.08 0.55) <0.01 Digestive problem 62.9 0.19 (0.09 0.38) <0.01 0.1 9 (0.09 0.40) <0.01 Lameness 79.3 0.46 (0.18 1.15) 0.10 0.71 (0.26 1.97) 0.51 Subclinical disease Healthy 94.8 1.00 --1.00 --Single subclinical disease 89.6 0.48 (0.25 0.91) 0.02 0.44 (0.23 0.84) 0.01 Multiple subclinical d iseases 83.5 0.28 (0.15 0.53) <0.01 0.28 (0.15 0.54) <0.01 Type of subclinical disease 3,4 SNEB 80.5 0.34 (0.20 0.56) <0.01 0.43 (0.25 0.75) <0.01 Subclinical ketosis 87.5 0.64 (0.39 1.04) 0.07 1.32 (0.70 2.45) 0.39 Subclinical hypocalcemi a 84.6 0.40 (0.24 0.67) <0.01 0.39 (0.23 0.67) <0.01 1 OR = odds ratio; CI = confidence interval 2 AOR = adjusted odds ratio 3 Compared with cows not diagnosed with the respective health problem. 4 SNEB = severe negative energy balance based on serum ketosis based on serum BHBA > 10 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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111 Table 3 4. Impact of postpartum diseases on pregnancy per AI on d 30 after first insemination Univariate analysis Multivariat e analysis Health problem Pregnant,% OR ( 95% CI) 1 P AOR 2 ( 95% CI) P Clinical disease Healthy 66.9 1.00 --1.00 --Single clinical disease 56.5 0.64 (0.46 0.89) <0.01 0.63 (0.46 0.88) <0.01 Multiple clinical diseases 40.8 0.34 (0.21 0.5 6) <0.01 0.35 (0.21 0.57) <0.01 Type of clinical disease 3 Calving problem 44.3 0.46 (0.27 0.77) <0.01 0.65 (0.37 1.15) 0.14 Metritis 38.6 0.37 (0.20 0.68) <0.01 0.35 (0.19 0.66) <0.01 Clinical endometritis 54.1 0.68 (0.47 1.01) 0.05 0.80 ( 0.53 1.21) 0.30 Mastitis 54.5 0.70 (0.47 1.02) 0.06 0.70 (0.47 1.05) 0.08 Respiratory problem 45.0 0.49 (0.20 1.20) 0.12 0.69 (0.27 1.77) 0.44 Digestive problem 27.3 0.22 (0.09 0.57) <0.01 0.25 (0.10 0.67) <0.01 Lameness 45.8 0.51 (0.23 1.1 5) 0.10 0.56 (0.24 1.30) 0.18 Subclinical disease Healthy 68.0 1.00 --1.00 --Single subclinical disease 63.6 0.82 (0.57 1.19) 0.30 0.84 (0.58 1.22) 0.36 Multiple subclinical diseases 52.2 0.52 (0.35 0.76) <0.01 0.59 (0.40 0.87) <0.01 Type of subclinical disease 3,4 SNEB 45.6 0.42 (0.29 0.62) <0.01 0.47 (0.32 0.70) <0.01 Subclinical ketosis 56.8 0.69 (0.50 0.94) 0.02 1.09 (0.74 1.60) 0.68 Subclinical hypocalcemia 59.3 0.89 (0.64 1.24) 0.50 ----1 OR = odds ra tio; CI = confidence interval. 2 AOR = adjusted odds ratio. 3 Compared with cows not diagnosed with the respective health problem. 4 ketosis based on serum BHBA > 10 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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112 Table 3 5. Impact of postpartum diseases on pregnancy per AI on d 65 after first insemination Univariate analysis Multivariate analysis Health problem Pregnant, % OR ( 95% CI) 1 P AOR 2 ( 95% CI) P Clinical disease Healthy 60.3 1.00 --1.00 --Single clinical disease 48.8 0.63 (0.45 0.87) <0.01 0.62 (0.45 0.86) < 0.01 Multiple clinical diseases 29.3 0.27 (0.16 0.46) <0.01 0.28 (0.17 0.47) <0.01 Type of clinical disease 3 Calving problem 32.8 0.38 (0.22 0.66) <0.01 0.52 (0.29 0.93) 0.03 Metritis 25.6 0.27 (0.13 0.54) <0.01 0.38 (0.18 0.80) 0.01 C linical endometritis 42.0 0.55 (0.37 0.81) <0.01 0.64 (0.42 0.96) 0.03 Mastitis 47.5 0.71 (0.49 1.05) 0.09 0.80 (0.53 1.20) 0.28 Respiratory problem 35.0 0.44 (0.17 1.11) 0.08 0.46 (0.18 0.79) 0.11 Digestive problem 22.7 0.24 (0.09 0.64) <0.01 0.23 (0.08 0.62) <0.01 Lameness 45.8 0.69 (0.31 1.57) 0.38 ----Subclinical disease Healthy 60.3 1.00 --1.00 --Single subclinical disease 56.0 0.84 (0.59 1.20) 0.33 0.84 (0.59 1.20) 0.33 Multiple subclinical diseases 47.0 0.58 (0.40 0.85) <0.01 0.58 (0.40 0.85) <0.01 Type of subclinical disease 3,4 SNEB 42.2 0.52 (0.35 0.76) <0.01 0.52 (0.35 0.76) <0.01 Subclinical ketosis 51.8 0.79 (0.58 1.08) 0.15 1.07 (0.74 1.56) 0.71 Subclinical hypocalcemia 51.4 0.83 (0.60 1.15) 0.27 ----1 OR = odds ratio; CI = confidence interval. 2 AOR = adjusted odds ratio. 3 Compared with cows not diagnosed with the respective health problem. 4 ketosis based on serum BHBA > 10 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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113 Table 3 6. Impact of postpartum diseases on pregnancy loss between gestati onal d ays 30 and 65 Univariate analysis Multivariate analysis Health problem Loss, % OR ( 95% CI) 1 P AOR 2 ( 95% CI) P Clinical disease Healthy 9.2 1.00 --1.00 --Single clinical disease 12.3 1.38 (0.71 2.67) 0.34 1.38 (0.71 2.67) 0.34 Multiple clinical diseases 26.7 3.58 (1.48 8.67) <0.01 3.58 (1.48 8.67) <0.01 Type of disease 3 Calving problem 25.9 3.12 (1.26 7.76) 0.01 2.93 (1.16 7.39) 0.02 Metritis 31.6 3.98 (1.33 11.9) 0.01 2.32 (0.70 7.70) 0.17 Clinical endometriti s 20.6 2.52 (1.27 5.01) <0.01 2.39 (1.19 4.79) 0.01 Mastitis 10.9 1.00 (0.43 2.32) 0.99 ----Respiratory problem 22.2 2.38 (0.48 11.8) 0.29 ----Digestive problem 16.7 1.64 (0.19 14.3) 0.65 ----Lameness 0.0 --0.28 ----Subclinical disease Healthy 10.2 1.00 --1.00 --Single subclinical disease 11.3 1.12 (0.56 2.27) 0.75 1.12 (0.56 2.27) 0.75 Multiple subclinical diseases 9.6 0.94 (0.41 2.16) 0.88 0.94 (0.41 2.16) 0.88 Type of subclinical disease 3,4 SNEB 6.6 0.57 (0.20 1.64) 0.29 ----Subclinical ketosis 8.3 0.70 (0.35 1.41) 0.32 ----Subclinical hypocalcemia 13.6 1.56 (0.80 3.04) 0.19 ----1 OR = odds ratio; CI = confidence interval. 2 AOR = adjusted odds ratio. 3 Compared with cows not diagnosed with the respective health problem. 4 ketosis based on serum BHBA > 10 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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114 Table 3 7. Impact of clinical uterine diseases on pregnancy per AI on d 30 and 65 after insemination and on pregnancy loss between gestational d ays 30 and 65 Pregnant d 30 AOR ( 95% CI) 1 P AOR ( 95% CI) P AOR ( 95% CI) P Healthy 63.9 a 1.00 ----------Clinical endometritis only 58.6 ab 0.82 (0.53 1.27) 0.38 1.00 ------Metritis only 42.9 bc 0.43 (0.18 1.03) 0.06 0.52 (0.20 1.35) 0.18 1.00 --Metritis and clinical endometritis 37.5 c 0.32 (0.14 0.74) <0.01 0.39 (0.15 0.98) 0.04 0.75 (0.22 2.50) 0.64 Pregnant d 65 *, AOR ( 95% CI) P AOR ( 95% CI) P AOR ( 95% C I) P Healthy 57.6 a 1.00 ----------Clinical endometritis only 47.2 b 0.68 (0.44 1.04) 0.07 1.00 ------Metritis only 33.3 b,c 0.37 (0.15 0.93) 0.03 0.55 (0.20 1.50) 0.23 1.00 --Metritis and clinical endometritis 18.2 c 0.16 (0.05 0.47) <0. 01 0.23 (0.07 0.74) 0.01 0.42 (0.10 1.75) 0.24 Pregnancy loss AOR ( 95% CI) P AOR ( 95% CI) P AOR ( 95% CI) P Healthy 9.1 a 1.00 ----------Clinical endometritis only 17.9 b 2.19 (1.02 4.67) 0.04 1.00 ------Metritis only 22.2 b,c 2. 80 (0.56 14.00) 0.21 1.28 (0.23 7.15) 0.78 1.00 --Metritis and clinical endometritis 42.9 c 7.33 (1.57 34.12) 0.01 3.35 (0.64 17.51) 0.15 2.62 (0.30 23.15) 0.39 a,b,c Superscripts within a day of pregnancy differ ( P < 0.07). Contrasts: Effect of uter ine disease (Healthy vs. all others) P < 0.05; Additive effect of metritis and clinical endometritis (clinical endometritis only + metritis only vs. metritis and clinical endometritis) P < 0.05. 1 AOR = adjusted odds ratio; CI = confidence interval.

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115 Tab le 3 hydroxybutyrate (BHBA) on d 14 3 according to incidence of postpartum diseases BHBA, mg/dL Ca, mg/dL Health problem No Yes P No Yes P No Yes P Clinic al disease Calving problem 408.115.6 428.740.0 0.88 10.160.50 7.011.30 <0.01 8.600.04 8.530.12 0.57 Metritis 403.715.6 490.145.3 0.02 9.910.49 11.411.42 0.73 8.620.04 8.260.13 <0.01 Clinical endometritis 406.215.6 409.728.7 0 .80 9.940.50 10.220.94 0.90 8.620.05 8.450.08 0.04 Mastitis 405.416.1 429.729.1 0.16 10.000.51 9.950.90 0.49 8.580.05 8.660.08 0.33 Respiratory problem 408.515.3 490.078.6 0.17 10.040.48 5.922.56 0.45 8.600.04 8.390.22 0.35 Digesti ve problem 408.615.4 446.959.4 0.87 10.000.49 9.841.70 0.90 8.600.04 8.390.17 0.22 Lameness 407.515.6 449.762.2 0.68 10.090.49 8.431.69 <0.01 8.600.04 8.580.18 0.95 Subclinical disease SNEB 1 ------8.230.45 18.430.73 <0.01 8.650.05 8.350.08 <0.01 Ketosis 309.614.5 625.418.9 <0.01 ------8.660.05 8.460.06 <0.01 Hypocalcemia 361.418.0 468.719.1 <0.01 9.260.60 10.770.69 0.05 ------1 mg/dL; subclinical hypocalcemia based on serum Ca < 8.5 mg/dL.

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116 Table 3 9. Correlation coefficients (r) among serum concentrations of metab olites and body condition score Ca d 7 3 NEFA 1 d 7 3 BHBA 2 d 14 3 BCS 3 d 7 3 BCS d 35 3 BCS change 4 Ca d 7 3 r 0.17 0.07 0.16 0.19 0.00 P < 0.01 0.07 < 0.01 < 0.01 0.91 NEFA d 7 3 r 0.17 0.56 0.20 0.12 0.32 P < 0.01 < 0.01 < 0.01 0.00 < 0.01 BHBA d 14 3 r 0.07 0.56 0.19 0.08 0.28 P 0.07 < 0.01 < 0.01 0.04 < 0.01 BCS d 7 3 r 0.16 0.20 0.19 0.58 0.57 P < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 BCS d 35 3 r 0.19 0.12 0.08 0.58 0.34 P < 0.01 < 0.01 0.04 < 0.01 < 0.01 BCS change r 0.00 0.32 0.28 0.57 0.34 P 0.91 < 0.01 < 0.01 < 0.01 < 0.01 1 NEFA = nonesterified fatty acids. 2 hydroxybutyrate. 3 BCS = body condition score. 4 BCS change = change in BCS from d 7 to 35 postpartum.

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117 Table 3 10. Ser um concentrations of Ca and non hydroxybutyrate (BHBA) on d 14 3 according to fertility response Ca, mg/dL BHBA, mg/dL Fertility resp onse No Yes P No Yes P No Yes P Estrous cyclic on d 49 8.130.10 8.660.04 <0.01 494.234.5 398.515.6 0.02 11.321.12 9.890.50 0.50 Estrus at AI 8.620.05 8.570.08 0.52 406.316.4 408.326.9 0.31 10.540.54 8.810.91 0.05 Pregnant d 30 8.580.06 8.63 0.05 0.44 459.620.2 374.317.2 <0.01 11.300.67 9.550.58 0.04 Pregnant d 65 8.580.06 8.640.05 0.34 444.719.2 379.918.2 0.01 11.080.64 9.740.62 0.20 Pregnancy loss 8.640.06 8.560.13 0.55 376.617.9 339.339.2 0.29 9.570.63 8.471.38 0.32

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118 CHA PTER 4 PREGNANCY PER A RTIFICIAL I NSEMI NA TION OF DAIRY COWS FOLLOW ING PRESYNCHRONIZATION A ND SPLITTING PROSTAG LANDIN F INJECTION IN THE 5 D TIMED A RTIFICIAL I NSEMINATION PROTOCOL Objectives were to compare pregnancy per artificial insemination (P/AI) of dairy cows subjected to the 5 d timed artificial insemination ( AI ) protocol either presynchronized or with supplemental progesterone during timed AI protocol, and using double dose of PGF either as single or split injections. In Experiment 1, lactating d airy cows (n = 737; Holstein = 250, Jersey = 80, and crossbred = 407) in two seasonally grazing farms were, within farm, blocked by breed, parity, and d in milk (DIM). Within each block, cows were randomly assigned to 1 of 4 treatments in a 2 x 2 factorial arrangement of treatments, with two synchronization and two luteolytic strategies. The day of AI was considered study d 0. Half of the cows were presynchronized (G6G: PGF on study d 16 and GnRH on d 14) followed by the 5 d timed AI protocol using 1 mg of cloprostenol either as a single (G6G SinglePG: GnRH on d 8, PGF on d 3, and GnRH + AI on d 0) or split into two injections (G6G SplitPG: GnRH on d 8, PGF on d 3 and 2, and GnRH + AI on d 0). The other half of the cows were not presynchronized, but received a controlled internal drug release (CIDR) containing progesterone between GnRH and the first PGF injections, and 1 mg of cloprostenol was used as a single (CIDR SinglePG: GnRH + CIDR on d 8, removal of CIDR and PGF on d 3, and GnRH + AI on d 0) or split into two injections (CIDR SplitPG: GnRH + CIDR on d 8, removal of CIDR and PGF on d 3, PGF on d 2, and GnRH + AI on d 0). Ovaries were scanned by ultrasonography on d 8 and 3 and plasma analyzed for progesterone on d 3 and 0. In Experiment 2, 655 high producing lactating Holstein cows in a confinement dairy had their estrous cycle presynchronized with an injection of PGF at

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119 46 3 and 60 3 DI M. Cows were blocked by parity and randomly assigned to 5 d timed AI protocol using 50 mg of dinoprost either as a single (GnRH on d 8, PGF on d 3, and GnRH + AI on d 0) or split into two injections (GnRH on d 8, PGF on d 3 and 2, and GnRH + AI on d 0). Pregnancies per AI were determined on d 35 and 64 after AI in both experiments. In Experiment 1, presynchronization with G6G increased the proportion of cows with a corpus luteum (CL) on d 8 (80.6 vs. 58.8%), ovulation to the first GnRH of the prot ocol (64.2 vs. 50.2%), and presence (95.6 vs. 88.4%) and number (1.79 vs. 1.30) of CL at PGF Luteolysis was greater for the split injection of PGF (95.9 vs. 72.2%), especially for presynchronized cows (96.2 vs. 61.7%). An interaction was observed for P/AI on d 35. For cows not presynchronized, method of PGF administration had no effect on P/AI (CIDR SinglePG = 30.2 vs. CIDR SplitPG = 34.3%), whereas for presynchronized cows, splitting the dose into two injections improved P/AI (G6G SinglePG = 28.7 vs. G6G SplitPG = 45.4%). In Experiment 2, splitting the dose of PGF increased P/AI on d 35 (44.5 vs. 36.4%) and 64 (40.3% vs. 32.6%) after AI. In conclusion, presynchronization and splitting the dose of PGF either as cloprostenol or dinoprost into two injections increases P/AI in lactating dairy cows subjected to the 5 d timed AI protocol. Int roduct ory Remarks Presynchronizing the estrous cycle of dairy cows with either 2 injections of prostaglandin (PG) F (Moreira et al., 2001; El Zarkouny et al., 2004) or a combination of gonadotropin releasing hormone ( GnRH ) and PGF (Bello et al., 2006) increases the proportion of cows initiating timed artificial insemination (AI) protocols at early diestrus. Cows at this stage of the estrous cycle at initiation of timed AI protocols h ave a greater probability to ovulate in response to the first GnRH inje ction (Vasconcelos et al., 1999;

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120 Bello et al., 2006) and reduced occurrence of spontaneous luteolysis before the end of the program (Moreira et al., 2001; El Zarkouny et al ., 2004). Such responses assure that the ovulatory follicle will develop under high systemic concentrations of progesterone and limits the period of follicle dominance, all of which are important factors affecting fertility (Cerri et al., 2009a; Bisinotto et al., 2010a; Santos et al., 2010a). Furthermore, incorporating GnRH into presynchr onization protocols induces estrous cyclicity in anovular cows (Ribeiro et al., 2011). Nevertheless, presynchronization increases labor, animal handling and extends time of the program until AI, which may constitute a nuisance for some dairy producers. An alternative to improve synchronization without lengthening timed AI programs is progesterone supplementation during the protocol. The use of controlled internal drug release (CIDR) inserts containing progesterone between GnRH and PGF injections maintain blood progesterone concentrations that prevent premature estrous behavior, luteinizing hormone ( LH ) surge and ovulation. It has been used during timed AI protocols to benefit fertility of dairy cows when the estrous cycle is not presynchronized (El Zarkou ny et al., 2004; McDougall, 2010) or when part of them are selectively inseminated following detection of estrus before enrolment in the timed AI protocol (Melendez et al., 2006; Chebel et al., 2010). Additionally, supplementation of progesterone might ben efit cows with low endogenous concentration of progesterone during the development of the ovulatory follicle. The use of supplemental progesterone in place of presynchronization is attractive for protocols with reduced period of follicular dominance, as in these programs follicle turnover and aging of the oocyte might be less critical.

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121 Cows subject to the 5 d timed AI protocol had increased pregnancy per AI (P/AI) than those subjected to a 7 d program (Santos et al., 2010a), although two injections of PGF given on d 5 and 6 after the first GnRH were needed for adequate corpus luteum (CL) regression. It may be particularly important in presynchronized cows because of increased ovulation to the first GnRH injection and consequently greater occurrence of ne wly formed CL at PGF which do not respond well on regression after a single PGF injection on d 5 (Santos et al., 2010a). Nevertheless, it is possible that a larger dose of PGF administered as a single injection on d 5 might enhance the luteolytic re sponse. This would facilitate management of cows in the 5 d timed AI programs. The objectives of the present study were to compare P/AI of lactating grazing dairy cows subjected to the 5 d timed AI protocol either presynchronized or supplemental with proge sterone and receiving twice the luteolytic dose of PGF either as a single or split injections. The h ypotheses tested were that non presynchronized cows subjected to the 5 d timed AI protocol with supplemental progesterone would have similar P/AI as presynchronized cows subjected to the same protocol without progesterone supplementation. Additionally, luteolysis and P/AI in cows subjected to the 5 d timed AI protocol would be similar if twice the luteolytic dose of PGF is used regardless if administered as a single treatment on d 5 of the program or split i nto two injections on d 5 and 6. Materials and Methods Experiment 1 Cows, p asture s and m anagement The Experiment 1 was conducted in two commercial grazing dairy farms located in Florida. Both were fall/winter calving herds with similar genetics and manage ment

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122 practices. The average milk production per cow was approximately 5,000 kg/lactation. A total of 737 lactating dairy cows (250 Holsteins, 80 Jerseys, and 407 crossbreds) were enrolled in this study. Crossbred cows population was mostly composed by F1 ( 50/50) and F2 (25/75) generation of crossbreeding between Holstein and Jersey genetics. Different genetic groups were managed together in a pasture based production system in both herds. Cows were maintained under irrigated pastures of 2.7 ha and managed i n a daily rotational program with a stocking rate of approximately 10 cows/ha. The pasture was composed by annual ryegrass ( Lolium multiflorum Lam.) during winter and early Cynodon spp) during late spring and summer. C ows were offered variable amounts of concentrate (7 to 13 kg/cow/d) during and immediately after each of the two milkings according to forage availability and stage of lactation. The concentrate was based on soybean hulls, citrus pulp, whole cottonseed, co ttonseed hulls, corn gluten feed, corn meal, soybean meal, molasses, and a mineral vitamin premix, and designed to contain approximately 15 % of crude protein 4.5% of fat, and 28% of neutral detergent fiber Experimental d esign and r andomization The exper imental design was completely randomized with blocks. Within herd, cows were blocked in groups of 4 according to breed (Holstein, Jersey and crossbred), parity (primiparous and multiparous), and d in milk (DIM) Within each block, cows were randomly assign ed to 1 of 4 treatments arranged as a 2 x 2 factorial. The factors were synchronization strategy and luteolytic strategies (Figure 4 1). Synchronization and luteolytic treatments All cows in the study were subjected to a 5 d timed AI protocol (Santos et al ., 2010a), but with variants in synchronization and luteolytic strategies according to the

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123 experimental design. The day of AI was considered the study d 0. Half of the cows were presynchronized using a GnRH based protocol ( G6G ; Bello et al., 2006) with the timed AI protocol starting 6 d later, and the other half of the cows were not presynchronized, but received a CIDR insert (Eazi Breed TM CIDR Cattle Insert; Pfizer Animal Health, Madison, NJ) containing 1.38g of progesterone between study d 8 and 3. On s tudy d 3 cows in each synchronization treatment were submitted to 1 of 2 luteolytic treatments with 1 mg of a PGF analog (Estrumate, 250 g/mL of cloprostenol sodium, Intervet/Schering Plough Animal Health, Summit, NJ) either as a single injection on d 3 (SinglePG) or split into two injections of 500 g each on d 3 and 2 (SplitPG) All cows were timed inseminated on study d 0. Ovarian u ltrasonography and o vulatory r esponses Ultrasonographic examinations of the ovaries were performed using a 7.5 MHz li near transducer (Easy Scan, BCF Technology, Livingston, UK) on study d 8 and 3. the first GnRH of timed AI protocol injection was characterized by the appearance of a n ew CL on d 8. New CL at PGF was characterized by the presence of a new CL independently of the presence or size of follicles on d 8. Progesterone a nalysis and l uteolysis On study d 3 and 0, c oncurrent with the injection of PGF and AI, respectively, a subgroup of 212 cows in one of the herds had blood sampled by puncture of the coccygeal vein or artery into evacuated tubes containing K 2 EDTA (Becton Dickinson, Franklin Lakes, NJ). For cows re ceiving a CIDR, blood was sampled on d 3 at least 15 min after insert removal and 0.6 ng/mL were deducted from the concentration according

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124 with the expected contribution of progesterone from the intravaginal insert (Cerri et al., 2009b). Samples were imme diately placed o n ice and transported to the laboratory within 5 h of collection. Tubes were centrifuged at 2,000 g for 15 min for plasma separation. Plasma samples were frozen at 20C and later analyzed for concentration of progesterone by RIA using a commercial kit (Coat A Count; Siemens Healthcare Diagnostics, Los Angeles, CA). Samples were analyzed in a single assay with sensitivity of 0.05 ng/mL calculated at 2 SD below the mean counts per min at maximum binding. The intra assay CV was calculated fo r each duplicate and it averaged 4.7%. Plasma samples of a cow on estrous cycle d 4 (0.9 ng/mL) and 8 (4.3 ng/mL) were repeated several times in the assay and their CV were 15.6% and 8.8%, respectively. Seventeen cows with progesterone concentration < 1 ng /mL on d 3 were not used for analysis of luteolysis because it was assumed they did not have a functional CL. 3 and < 1 ng/mL on d 0 were considered as having CL regression. Receiver operator characteris tic ( ROC ) curve was used to determine the concentrations of progesterone at PGF and AI that resulted in highest accuracy for prediction of pregnancy on d 35 after AI. Cows having these progesterone concentrations were considered as having an ideal proges terone profile. Detection of e strus, b ody c ondition s core and d ays in m ilk On study d 2 tailheads of all cows were painted using paintsticks (All Weather Paintstick; LA CO Industries, Chicago, IL) for detection of estrus on the day of AI based on removal of tailpaint. Cows were scored for body condition in a 1 to 5 scale (BCS: 1= emaciated, 5 = obese; Ferguson et al., 1994) at AI and 35 days later. For statistical

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125 Similarly, cows were categorized according to body condition change from AI to pregnancy diagnosis as having lost, no change or gained BCS. Cows were also categorized according to their DIM at AI as low (< 50 DIM), medium (50 to 90 DIM), or high (> 90 DIM). Pregnancy d iagnoses and p regnancy l osses Pregnancy was diagnosed on d 35 after timed AI via ultraso nographic examination of the uterus and its contents, and was characterized by visualization of a live embryo. Cows diagnosed as pregnant on d 35 were reexamined by transrectal palpation on d 64 after timed AI. Pregnancies per AI were calculated as the num ber of pregnant cows on d 35 or 64 after AI divided by the total number of cows inseminated. Pregnancy loss was calculated as the number of pregnant cows on d 35 minus the number of pregnant cows on d 64 divided by the number of pregnant cows on d 35. Expe riment 2 Cows, h ousing and d iets Experiment 2 was conducted in a 5,000 cow commercial dairy farm located in Florida with rolling herd average of 10,400 kg/year. Lactating Holstein cows, 254 primiparous and 401 multiparous, were assigned to the study. Primi parous and multiparous cows were housed separately in free stall barns equipped with sprinklers and fans. Both received the same total mixed ration to meet or exceed the nutrient requirements for a lactating Holstein cow producing 45 kg of milk/d with 3.5% fat and 3.2% true protein (NRC, 2001). Cows were fed twice daily and milked thrice daily. Diet consisted of corn silage, rye grass silage, finely ground corn, dried citrus pulp, whole soybean meal,

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126 molasses, minerals and vitamins. The diet was designed t o contain approximately 15.9% of crude protein 5.1% of fat, 24% of starch, and 33% of neutral detergent fiber Experimental d esign and r andomization The experimental design was a comple tely randomized with blocks. Weekly, cohort of cows between 43 and 49 DIM were blocked by parity (primiparous or multiparous) and randomly assigned to one of two luteolytic treatments (Figure 4 2). As in Experiment 1, study d 0 was considered the day of AI Synchronization p rotocol and l uteolytic t reatments E strous cycle were presynchronized with two injections of 25 mg of PGF given at 46 3 and 60 3 DIM (Moreira et al., 2001). At 72 3 DIM cows were assigned to the 5 d timed AI protocol, and treatmen ts were 50 mg of dinoprost (Lutalyse, 5 mg/mL dinoprost tromethamine sterile solution, Pfizer Animal Health) either as a single injection on study d 3 (SinglePG) or split into two injections on d 3 and 2 (SplitPG) Pregnancy d iagnoses, m ilk y ield and b o dy c ondition s core Pregnancy was determined 35 and 64 d after AI as described in Experiment 1. Yields of milk were recorded for individual cows once monthly, and the average for the first 3 mo nths postpartum was used for statistical analysis. Cows were cat egorized according to milk production above or below the mean value within parity. The BCS at AI and 35 d later were recorded, categorized and analyzed as in Experiment 1. Statistical Analyses Experiment 1 All statistical models included the effects of syn chronization treatment, luteolytic treatment, and interaction between the two. The effects of herd, parity, breed, DIM, BCS at AI, change in BCS, sire, and AI technician were included when P

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127 Data with binomial distribution were analyzed by multivariate logistic regression models using the LOGISTIC procedure of SAS version 9.2 (SAS/STAT, SAS Institute Inc., Cary, NC, USA). A stepwise backward elimination was used and covariates were removed based on the Wald statistics criterion when P > 0.10. Synchronization and luteolytic treatments were forced in the final models. The probability of detecting a CL on study d 8 was modeled using the logistic function with the intercept and the coef ficient estimates from the logistic regression analyses according to synchronization treatment and DIM or BCS of cows using the formula: P = 1/[1+(e (a+b 1 X 1 + a+b 2 X 2 ) ]. Concentration of progesterone on study d 3 and 0 were analyzed by ANOVA using th e GLM procedure of SAS The models included the effects of synchronization treatment, luteolytic treatment, the interaction between the two treatment factors, BCS at AI, breed, parity, presence of CL on d 0, ovulation to the first GnRH, and number of CL a t PGF Receiver operating characteristic analysis option of Med Calc version 11.2.1 (MedCalc Software, Mariakerke, Belgium) was used to determine the optimal concentration of progesterone at PGF and AI that predict P/AI on d 35 with greatest combined sensit ivity and specificity. Experiment 2 All statistical models included the effect of treatment, which was forced in the final models. The effects of parity, BCS at AI, change in BCS, milk yield, AI technician, and sire were included when P Data with binomial distribution were analyzed by multivariate logistic regression models using the LOGISTIC procedure of SAS A stepwise backward elimination was used and covariates were removed based on the Wald statistics criterion when P > 0.10. Treatment was fo rced in all final models.

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128 In both experiments, differences with P 0.05 < P Results Experiment 1 The BCS of cows at AI and d 35 did not differ ( P they averaged 2.80 0.03 and 2.71 0.02, respectively. Similarly, D IM at AI did not differ among treatments and they were 79.8 1.9 for G6G and 78.5 1.9 for CIDR and 78.6 2.0 for SinglePG and 79.6 1.9 for SplitPG. According to ROC, the progesterone concentrations that resulted in the best combined sensitivity and s pecificity to predict (study d 3) and 3 and 0, respectively, were considered as having the ideal progesterone profile. Presynchronization with G6G increased ( P < 0.01) the proportion of cows with a CL on the d ay of the first GnRH of the timed AI protocol, ovulation to the first GnRH (study d 8), and presence and nu mber of CL and progesterone concentration on the day of the PGF injection of the protocol (study d 3) compared with cows receiving only progesterone supplementation (Table 4 1). The proportion of cows with CL on study d 8 when the first GnRH of the timed AI was administered increased ( P < 0.01) with DIM and BCS of cows (Figure 4 3). Interestingly, the benefit of G6G on the proportion of cows with a CL was influenced by DIM and by BCS. The G6G increased ( P < 0.05) the proportion of cows with CL when they had fewer than 90 DIM (Figure 4 3, Panel A) and when the BCS w 4 3, Panel B).

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129 Both synchronization and luteolytic treatments influenced luteolysis. In general, G6G resulted in a smaller ( P = 0.05) proportion of cows undergoing luteolysis than CIDR. Similarly, cows receiving SinglePG had smaller ( P < 0.01) incidence of luteolysis than those receiving SplitPG, particularly when presynchronized with G6G (Table 4 1). As a consequence, SinglePG cows had greater ( P < 0.01) concentrations of progesterone at AI and a smaller ( P < 0.01) proportion of them had the ideal progesterone profile. Additionally, synchronization and luteolytic treatments affected detection of estrus at AI, following the same pattern as that for CL regression. Fewer ( P < 0.01) cows receiving G6G were detect ed in estrus compared with cow s receiving CIDR. Similarly, treatment with SinglePG reduced ( P = 0.04) detection of estrus compared with SplitPG. An interaction ( P = 0.05) between synchronization and luteolytic treatments was observed for P/AI on d 35 after AI. For CIDR cows, method of PGF administration had no effect on P/AI, whereas for G6G cows, splitting the dose into two injections improved P/AI (Table 4 1). On d 64 after AI, however, no interaction ( P = 0.17) between treatments was observed, but presynchronization tended ( P = 0.10) to increase P/AI and SplitPG increased ( P = 0.02) P/AI than SinglePG. There were no differences in pregnancy loss among treatments. As expected, cows having ideal progesterone profile had greater ( P < 0.01) P/AI on d 35 and 64 than those not having it, and they also had less ( P < 0.04) pregnancy loss between d 35 and 64 of gestation (Figure 4 4). Cows with a CL at the first GnRH injection of the timed AI protocol had greater ( P < 0.01) P/AI than cows without CL (39.2 vs. 24.3%), and this effect was observed despite synchronization and luteolytic treatments. Cows with low DIM had smaller ( P <

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130 0.01) P/AI than those with moderate and high DIM (23.5 vs. 37.6 vs. 40.8%). Similarly, P < 0.01) P/AI than cows with BCS of 2.75 to 3.0 0 P < 0.01). Additionally, cows that experienced loss of BCS from AI to study d 35, compared with those maintaining or gaining BCS, had smaller ( P < 0.01) P/AI than on d 35 (30.5 vs. 36.2 vs. 39.4%) and 64 (27.1 vs. 32.1 vs. 35.1%) after insemination. The BCS and DIM did not affect pregnancy loss between d 35 and 64 of gestation. The BCS did not differ among breed groups and averaged 2.82 0.03, 2.82 0.04 and 2.78 0.02 at AI, and 2.70 0.02, 2.74 0.04 and 2.70 0.02 on d 35 for Holsteins, Jerseys and crossbreds, respectively. The DIM at AI differed ( P < 0.01) among breeds and w as greater for Holsteins, followed by Jerseys and then crossbreds (Holstein = 85.6 2.2 vs. Jersey = 81.6 3.5 vs. crossbred = 70.1 1.7). Holstein cows tended ( P = 0.07) to have more CL on d 0 of the protocol than Jersey and crossbred cows (Table 4 2). However, no differences were found for ovulation to the first GnRH injection, presence and number of CL at PGF luteolysis, and estr us at AI (Table 4 2). Holstein cows had smaller ( P = 0.02) concentration of progesterone on the day of the PGF injection of the timed AI protocol than Jersey and crossbred cows, but these differences disappeared at AI. The proportions of cows with ideal progesterone profile did not differ with breed. Pregnancies per AI on d 35 and 64 differed among breeds because they were less for Holstein than crossbreds cows (Table 4 2). However, an interaction ( P < 0.01) between synchronization treatment and breed was observed, and the smaller P/AI for Holsteins than crossbreds was only observed when they received CIDR (Holstein = 18.7 vs. Jersey = 34.3 vs. crossbred = 40.9%), but not when they

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131 were presynchronized with G6G (Holstein = 39.1 vs. Jersey = 31.0 vs. crossb red = 37.4%). Ovulation to the first GnRH of the 5 d timed AI protocol did not affect P/AI in this study (no ovulation = 33.4 vs. ovulated = 35.6 %). Because luteolysis was compromised with SinglePG, further analysis of the impact of ovulation to the first GnRH of the timed AI protocol was performed only with cows receiving SplitPG. For cows receiving SplitPG, then ovulation to the first GnRH of the timed AI increased ( P = 0.01) P/AI (no ovulation = 36.4 vs. ovulation = 43.0%), and an interaction ( P = 0.04) between ovulation and breed was detected. Only Holstein cows had fertility compromised by no ovulation to the first GnRH injection (no ovulation = 20.0 vs. ovulation = 42.4%), which was not observed for Jersey (36.0 vs. 36.4%) and crossbred cows (47.6 vs. 44.6%). Exp eriment 2 Days in milk and BCS at AI did not differ between treatments and averaged 75.3 0.4 d and 2.85 0.02. Luteolytic treatments did not influence detection of estrus at AI (SinglePG = 29.7% vs. SplitPG = 34.1%). Splitting the dose of PG F into two treatments in the 5 d timed AI protocol increased P/AI on d 35 ( P = 0.02) and 64 ( P = 0.04) after AI, but it did not alter pregnancy loss (Figure 4 5). No interactions were observed between treatment and parity, BCS, or milk production on dete ction of estrus at AI, P/AI, and pregnancy loss. Discussion The 5 d timed AI program has been used to reduce the period of follicle dominance and improve P/AI in dairy cows and heifers (Rabaglino et al., 2010; Santos et al., 2010a) and beef cows (Bridges e t al., 2008). The limiting factor to reduce the period of follicle dominance in timed AI programs is the regression of the newly formed

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132 CL resulting from ovulation to the first GnRH injection of the protocol. In the current study, the luteolytic dose of ei ther cloprostenol in Experiment 1 and dinoprost in Experiment 2 were doubled because previous studies indicated that the standard luteolytic dose of PGF was not sufficient to optimize luteal regression and P/AI in the 5 d timed AI (Kasimanickam et al. 2 009; Santos et al., 2010a). In both experiments, splitting the dose of PGF into two injections administered on d 5 and 6 of the protocol improved fertility of beef and dairy cows. Pregnancy per AI of dairy cows has improved when follicle dominance is li mited either by increasing turnover with presynchronization or by reducing the interval from emergence to ovulation by inducing early luteolysis. However, there are limitations to when luteolysis can be induced because the CL is less responsive to PGF in the first 5 d of development (Miyamoto et al., 2009). It has been proposed that the early CL has distinct molecular responses to PGF compared with the mid cycle CL (Miyamoto et al., 2009). To solve this problem in 5 d timed AI protocols, the administrat ion of a second luteolytic dose of PGF 7 to 24 h after the first dose resulted in improved luteolysis and fertility (Kasimanickam et al., 2009; Santos et al., 2010a). The disadvantage of this approach is that cows have to be handle d an additional day. F urthermore, the mechanism by which the second dose helps ensure luteolysis is not clear. Because an interval as short as 7 h between injections was sufficient to improve fertility of beef cows (Kasimanickam et al., 2009), we hypothesized that increasing th e dose as a single injection would result in similar CL regression and P/AI compared with the same amount of PGF administered split into two injections. The results of Experiment s 1 and 2 clearly indicate that for presynchronized cows, the

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133 double dose of PGF either as cloprostenol or dinoprost administered solely on d 5 was not sufficient to optimize luteolysis and P/AI in the 5 d timed AI protocol. For cows that ovulated to the first GnRH injection and received a single PGF injection, only 45.7% proportion was 78.1%. In fact, w hen only cows that ovulated to the first GnRH of the 5 d timed AI protocol were considered, luteolysis and P/AI on d 35 were, respectively, 54.6 and 27.4% for G6G SinglePG, 94.6 and 48.7% for G6G SplitPG, 85.7 and 30.8% for CIDR SinglePG, and 96.3 and 34.5 % for CIDR SplitPG. Therefore, the higher dose of PGF administered as a single injection did not change the refractory response to luteolysis of the early CL observed in previous studies with the conventional luteolytic dose (Santos et al., 2010) although there is variation in response among individual an imals. In spite of the reduced luteal regression, there were cows with a newly formed CL that underwent complete luteolysis (45.7%) after single injection of 1 mg of cloprostenol on d 5 after induction of ovulation. Age of the CL can vary because not all c ows ovulate at the same time after treatment with GnRH. This subtle variation in age of the CL associated with changes in the process of luteinization might result in altered molecular control of luteal development and consequent differences in the timing to undergo complete luteolysis in response to PGF (Wiltbank and Ottobre, 2003). The competence of the ovulatory follicle is critical for fertility of lactating dairy cows, and extending dominance typically reduces P/AI. Dynamic biochemical and molecular changes occur in the follicle as it acquires and maintains dominance (Aerts and Bols 2010; Tripathi et al., 2010). Reducing the interval from follicle emergence to

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134 ovulation improves early embryo quality (Cerri et al., 2009a) and pregnancy per AI of lactat ing dairy cows following synchronized ovulation (Santos et al., 2010a) or spontaneous estr us (Bleach et al., 2004). As dominance extends, the oocyte is overexposed to LH pulses, which alters the hormonal concentrations in the follicular fluid and results i n compromised oocyte maturation (Revah and Butler, 1996). These changes culminate with ovulation of an aged oocyte of reduced fertility (Mihm et al., 1994). The negative effect of extended dominance might be exacerbated if the ovulatory follicle develops u nder low concentrations of progesterone. By using the 5 d timed AI program, which limits follicle dominance, we initially hypothesized that supplementation with progesterone during the protocol would result in fertility similar to that of presynchronized c ows. Contrary to that hypothesis, presynchronization of the estrous cycle with G6G improved fertility of dairy cows compared with use of CIDR, particularly in cows subjected to a better luteal regression with the SplitPG. Interestingly, Bisinotto et al. (2 010b) observed that use of a CIDR insert in the 5 d timed AI protocol was only effective to improve fertility of cows bearing a CL. Likely, the exogenous progesterone supplied by the insert raised progesterone sufficiently to optimize fertility only when t here was already progesterone production from the CL. Nonetheless, the advantage can also be simply result of avoiding premature LH surge after spontaneous luteolysis, which can occur in cows with a mid cycle CL at the insertion of the progesterone insert, but not in those without a CL at this moment. Different responses to synchronization treatments were observed according to the breed of the cows. Jersey and crossbred cows did not benefit from presynchronization with G6G, whereas for Holstein cows, presyn chronization and SplitPG were critical to

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135 improve P/AI. In fact, compared with Jersey and crossbred cows, Holsteins were less fertile when subjected to the CIDR treatment. Although presence of CL on the day of the first GnRH of the timed AI and ovulation t o the first GnRH did not differ among breeds, Holstein cows had lower concentrations of progesterone on study d 3. This difference likely reflects metabolism of progesterone in larger and more productive cows. It is known that concentration of progesteron e during the development of the ovulatory follicle is critical to fertility (Bisinotto et al., 2010a). It is possible that for Jersey and crossbred cows, presynchronization was less critical because of their greater concentrations of progesterone, whereas for Holstein cows, the G6G induced more of them to be in diestrus with an active CL when the 5 d timed AI program began. When cows are presynchronized, as in G6G in Experiment 1 and all cows in Experiment 2, splitting the PGF into two injections was critical to fertility, regardless of type of PGF used. However, the single PGF injection did not affect fertility in non presynchronized cows in Experiment 1. Similar responses have also been reported for dairy heifers (Rabag lino et al., 2010) and for some (Cruppe et al., 2010), but not all studies with beef cattle (Kasimanickam et al., 2009), in which the use of a single injection of PGF on d 5 was effective as the two injections. Results from the current study indicate tha t response to SinglePG in the 5 d timed AI protocol is dependent on the proportion of cows with a newly formed CL. In dairy heifers subjected to the 5 d timed AI protocol, ovulation to the initial GnRH is low, and less than 40% of them have a newly formed CL on the day of the PGF injection (Lima et al., 2011). On the other hand, in presynchronized dairy cows, ovulation to the first GnRH is high, usually greater than 60% (Bello et al., 2006; Cerri et al., 2009a; Santos et al., 2010a). Therefore, the

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136 rate of ovulation at the begin ning of the protocol will determine the effectiveness of single administration of PGF on d 5 or the need for additional PGF injection 7 to 24 h later. Summary Presynchronization and splitting the dose of PGF into two injections increased P/AI in cows subjected to the 5 d timed AI protocol. Presynchronization increased the proportion of cows with a CL at the beginning of the timed AI protocol and ovulation to the first GnRH of the protocol, both of which improved fertility when adequate luteolysis was obtained. Nevertheless, the benefits to presynchronization were observed primarily in Holstein cows. For Jersey and crossbred cows, progesterone supplementation during the 5 d timed AI protocol constituted an alternative synchronization strategy that resul ted in similar fertility compared with presynchronized cows. A single PGF injection containing twice the standard luteolytic dose of cloprostenol or dinoprost on d 5 of the timed AI protocol resulted in inadequate CL regression, especially in presynchron ized cows, which compromised fertility of dairy cows under grazing or confinement. The benefits of administer ing PGF on d 5 and 6 after GnRH in the 5 d timed AI protocol were observed with both dinoprost and cloprostenol.

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137 Table 4 1. Effects of synchron ization and luteolytic treatments on reproductive responses of grazing dairy cows Experiment 1 Treatment 1 G6G CIDR P 2 Item SinglePG SplitPG SinglePG SplitPG S L S x L Presence of CL at 1 st GnRH 82.1 (147/179) 79.1 (148/187) 57.9 (110/190) 59.7 (108/181) < 0.01 0.90 0.51 Ovulation to 1 st GnRH 3 65.4 (117/179) 63.1 (118/187) 54.7 (104/190) 46.7 (84/180) < 0.01 0.18 0.52 New CL at PGF 4 78.2 (140/179) 77.0 (144/187) 64.2 (122/190) 65.6 (118/180) < 0.01 0.96 0.62 Presence of CL at PGF 96.7 (173/179) 94.7 (177/187) 86.3 (164/190) 90.6 (163/180) < 0.01 0.53 0.18 Number of CL at PGF 1.83 0.06 1.76 0.06 1.29 0.06 1.31 0.06 < 0.01 0.62 0.31 Progesterone at PGF ng/mL 5.02 0.77 5.37 0.77 4.98 0.77 4.78 0.80 < 0.01 0.62 0.84 Progesterone at AI, ng/mL 0.76 0.22 0.28 0.21 0.58 0.20 0.27 0.21 0.21 < 0.01 0.36 Ideal progesterone profile 5 26.0 (13/50) 58.2 (32/ 55) 28.1 (16/57) 44.0 (22/50) 0.35 < 0.01 0.25 Luteolysis 6 61.7 (29/47) 96.2 (50/52) 82.0 (41/50) 95.7 (44/46) 0.05 < 0.01 0.30 Estrus at AI 20.8 (37/178) 32.1 (60/187) 33.7 (64/190) 37.6 (68/181) < 0.01 0.04 0.12 Pregnant, % Day 35 28.7 (5 1/178) 45.4 (84/185) 30.2 (57/189) 34.3 (61/178) 0.56 0.44 0.05 Day 64 27.7 (49/177) 40.0 (74/185) 26.1 (49/188) 29.2 (52/178) 0.10 0.02 0.17 Pregnancy loss, d 35 to 64 3.9 (2/51) 11.9 (10/84) 14.0 (8/57) 14.8 (9/61) 0.17 0.37 0.23 1 All cows were s ubjected to the 5 d timed AI protocol. G6G = injection of PGF followed 2 d later by an injection of GnRH, and starting timed AI protocol 6 d later; CIDR = controlled internal drug release insert containing 1.38 g of progesterone used b etween d 0 and d 5 of time AI protocol. SinglePG = injection of 1 mg of cloprostenol as a single injection on d 5 of the timed AI protocol; Spli tPG = injection of 1 mg of cloprostenol split into 2 injections of 0.5 mg on d 5 and 6 of the timed AI protocol. 2 S = effect of s ynchronization strategy (G6G vs. CIDR); L = effect of luteolytic treatment (SinglePG vs. SplitPG); S x L = interaction between S and L treatments. 3 Proportion of cows with a new CL on study d 3 that had a follicle > 8 mm on study d 8. 4 Proportion of co ws with a new CL on study d 3 independent of the presence of follicle > 8 mm on study d 8. 5 6 g/mL on study d 3 and < 1 ng/mL on study d 0.

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138 Table 4 2. Effect of breed on reproductive responses of grazing dairy cows Experiment 1 Breed Item Holstein Jersey Crossbreed P CL at 1 st GnRH 72.4 (181/250) 65.0 (52/80) 68.8 (280/407) 0.07 Ovulatio n to 1 st GnRH 1 56.4 (141/250) 50.0 (40/80) 59.6 (242/406) 0.15 New CL at PGF 2 73.6 (184/250) 66.3 (53/80) 70.7 (287/406) 0.35 CL at PGF 90.6 (229/250) 90.0 (72/80) 92.6 (376/406) 0.10 Number of CL at PGF 1.56 1.49 1.59 0.58 Progesterone at PGF (ng/mL) 4.55 0.72 a 5.36 0.83 b 5.20 0.72 b 0.02 Progesterone at AI (ng/ mL) 0.35 0.19 0.50 0.21 0.57 0.19 0.13 Ideal progesterone profile 3 39.6 (38/96) 27.3 (9/33) 43.4 (36/83) 0.15 Luteolysis 4 87.1 (74/85) 80.7 (25/31) 82.3 (65/79) 0.65 Estrus at timed AI 31.6 (79/250) 33.8 (27/80) 30.3 (123/406) 0.90 Pregnant, % Day 35 28.1 a (70/249) 32.5 a (25/77) 39.1 b (158/404) < 0.01 Day 64 24.1 a (60/249) 27.3 a (21/77) 35.6 b (143/402) < 0.01 Pregnancy loss 14.3 (10/70) 16.0 (4/25) 9.5 (15/158) 0.45 a,b Superscript within the same row differ (P < 0.05). 1 Proport ion of cows with a new CL on study d 3 that had a follicle > 8 mm on study d 8. 2 Proportion of cows with a new CL on study d 3 independent of the presence of follicle > 8 mm on study d 8. 3 4 3 and < 1 ng/mL on study d 0.

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139 Figure 4 1. Diagram of activities for Experiment 1. G6G = presynchronization of the estrous cycle with an injection of PGF followed 2 days later by a injection of GnRH. AI = artificial insemination; CIDR = controlled internal drug release containing 1.38 g of progesterone; GnRH = injection of 100 g of gonadotropin releasing hormone; PGF = injection of 1 mg of cloprostenol either as a single injection or split into two injections of 0.5 mg each.

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140 Figure 4 2. Diagram of activities for Experiment 2. E strous cycle s were presynchronized in all cows with two injections of PGF given 14 d apart. AI = artific ial insemination; GnRH = injection of 100 g of gonadotropin releasing hormone; PGF = injection of 50 mg of dinoprost either as a single injection or split into two injections of 25 mg each.

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141 Figure 4 3. Probability of CL at first GnRH of timed AI pr otocol (study d 8) according to treatment and days postpartum (Panel A) or body condition score (Panel B). G6G = injections of PGF and GnRH on study d 16 and 14, respectively, and starting the timed AI protocol on study d 8. CIDR = no presynchronizat ion and use of controlled internal drug release insert containing progesterone from study d 8 and 3. Treatment influenced ( P < 0.05) the probability of CL in cows with fewer than 90 d postpartum or in cows 1).

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142 Figur e 4 4. Pregnancy per AI on d 35 and 64 after timed insemination and pregnancy loss for cows with or without ideal progesterone profiles on study d 3 and 0. ng/mL on study d 0 were considered as having the ideal progesterone profile based on receiver operator characteristic curves ( E xperiment 1).

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143 Figure 4 5. Pregnancy per AI on d 35 and 64 after timed insemination and pregnancy loss in lactating dairy cows subjected to 5 d timed AI protocol and receiving 50 mg of dinoprost administered either as a single injection on study d 3 or split into two injections administered on study d 3 and 2 (Experiment 2).

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144 CHAPTER 5 REPRODUCTIVE PERFORM ANCE OF GRAZING DAIR Y COWS FOLLOWING PRESYNC HRONIZATION AND RESY NCHRONIZATION PROTOC OLS Objectives were to compare the impact of presynchronization and resynchronization methods on fertility responses of grazing dairy cows at first and second artificial insemination (AI) and pregnancy rate during t he entire breeding season. Lactating dairy cows (n = 1,263) in two seasonal grazing farms were blocked, within farm, by parity, breed and d in milk (DIM). Within each block, cows were randomly assigned to 1 of 4 treatments in a 2 x 2 factorial design with two presynchronization and two resynchronization treatments. E strous cycles were presynchronized with either a PGF based program (Presynch) consisting of 2 injections of PGF administered 14 d apart and starting the timed AI protocol 11 d later, or with a PGF GnRH based presynchronization program (G6G) consisting of an injection of PGF followed 3 d later by an injection of GnRH and starting the timed AI protocol 6 d later. All cows received the first insemination on the same day, which was considered study d 0 and also d 0 of the breeding season. The timed AI protocol (5 d Cosynch72) was the same for all cows and consisted of GnRH on d 8, PGF on d 3 and 2, and GnRH + timed AI on d 0. Blood was sampled and analyzed for progesterone on d 8. On d 1 2, cows in each presynchronization treatment remained either as untreated controls (RCON) or received a controlled internal drug release (CIDR) insert containing progesterone for 7 d (RCIDR). Estrus was observed daily starting on d 19 and cows in estrus we re inseminated on the same day. On d 35 bulls were placed with the cows for additional 65 d, completing a 100 d breeding duration. Holstein cows w 8, and had less expression of estrus and pregnancy per AI (P/AI), which resulted in a slower rate of

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145 pregnancy and a smaller proportion of pregnancy at the end of the study than Jersey or crossbred cows. In addition, body condition, DIM, and plasma progesterone concentration at the first GnRH of the timed AI protocol had marked effects on the reproductive performance of lactating grazing dairy cows. A greater proportion of G6G mL at the first GnRH of timed AI protocol compared with Presynch cows (82.0 vs. 74.3%). Presynchronization treatment did not influence P/AI, but cows in G6G had increased risk of pregnancy loss between d 30 and 65 after the first AI (12.9 vs. 8.1%). Nevert heless, an interaction between presynchronization and ng/mL had greater P/AI when previously treated with Presynch than G6G. On the other hand, G6G benefited P/AI of cows i nitiating the timed AI with progesterone < 1 ng/mL. Resynchronization with RCIDR altered the pattern of return to estrus, but it did not increase the rate of re insemination and decreased the proportion of pregnant cows at the end of the 100 d breeding per iod (80.6 vs. 84.4%). I ntroduc tory Remarks Seasonal breeding is a strategy often used in pasture based dairy production to simplify management and to match calving and breeding periods to better climatic conditions and forage quality/availability. Cows mus t become pregnant in a short and pre established period of time to maximize productive efficiency and reduce the risk of culling. High submission early in the breeding period is also important to maintain the required concentrated calving pattern (Rhodes e t al., 2003), which is economically important (McDougall, 2010). Synchronization protocols for timed artificial insemination ( AI ) allow all cows to be inseminated in the first day of the breeding season, increasing the proportion pregnant early in the bree ding period. They constitute an effective

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146 treatment for anovular cows, which is a major problem in seasonal grazing farms and also represent a profitable strategy when managing cows not expressing estrus before the anticipated mating period (McDougall, 20 10). Collectively, these facts justify the use of timed AI programs for reproductive management in grazing dairy herds using seasonal breeding. In programs based solely o n prostaglandin ( PG ) F and gonadotropin releasing hormone ( GnRH ) synchronization of the follicular wave and pregnancy per AI (P/AI) are optimized when cows ovulate to the first GnRH injection of the timed AI protocol (Vasconcelos et al., 1999; Chebel et al., 2006). Cows that initiate the timed AI protocol in early diestrus have reduced occurrence of spontaneous luteolysis and a greater probability to bear a dominant follicle that ovulates in response to a GnRH injection (Vasconcelos et al., 1999). Furthermore, inducing ovulat ion during early diestrus with the first GnRH limits the period of follicle dominance (Cerri et al., 2009), and assures that the ovulatory follicle develops under high systemic concentrations of progesterone, both of which have been shown to benefit fertil ity (Bisinotto et al., 2010; Santos et al., 2010). A program commonly used to improve response to timed AI protocols is to administer two injections of PGF 14 d apart, with the second injection 10 to 12 before the first GnRH of the timed AI protocol to p resynchronize the estrous cycle (Moreira et al., 2001; Galvo et al., 2007a). In addition to manipulating estrous cycle patterns, it might also benefit uterine health by inducing estrus in cyclic cows. Nevertheless, it has restricted effects in anovular co ws (as defined by those without corpus luteum but with follicle development beyond the expected deviation diameter), which limits the efficiency

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147 of presynchronization. In contrast, GnRH induces ovulation in 76% of the cows without a corpus luteum (CL; Galv o et al., 2007a) and 88% in anovular cows (Gmen et al., 2003). Therefore, combining GnRH and PGF for presynchronization might benefit anovular cows by inducing estrous cyclicity before the initiation of the timed AI program. Bello et al. (2006) demonst rated that combining PGF followed 2 d later by GnRH improved ovulatory response to the first GnRH of the Ovsynch protocol when it was initiated 6 d after presynchronization. In that study, 81% of the cows initiated a synchronized estrous cycle after the presynchronization treatment, and 92% ovulated synchronously after the Ovsynch. Incorporating the GnRH in the presynchronization might benefit anovular cows, whereas two PGF injections might better presynchronize the estrous cycle of cyclic cows, therefo re, there might be a tradeoff between the two strategies. Cows that fail to conceive to the first AI must be reinseminated shortly after the previous service to assure adequate reproductive performance in seasonal breeding programs. In herds that opt for additional AI, improving estrous detection and reinsemination of nonpregnant cows after the first AI is expected to enhance reproductive performance. Intravaginal inserts containing progesterone have been used to synchronize return to estrus in nonpregnant cows (Chenault et al., 2003; El Zarkouny and Stevenson, 2004; Galvo et al., 2007b). Early resynchronization using progesterone inserts concentrate d AI on fewer days, which might simplify labor and i n some studies improved embryo survival to the pretreat ment AI (El Zarkouny and Stevenson, 2004; Chebel et al., 2006).

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148 Our objectives were to compare the impact of presynchronization and resynchronization methods on fertility responses of grazing dairy cows during the breeding season. Our first hypothesis was that presynchronization with PGF /GnRH compared with PGF alone would improve the proportion of cows initiating the timed AI protocol in diestrus and enhance P/AI. The second hypothesis was that incorporation of an intravaginal progesterone insert in an early resynchronization strategy would increase reinsemination of nonpregnant cows and improve pregnancy rate. Combining these effects was expected to improve reproduction during the breeding season. Materials and Methods Cows, Pasture s and Management The study was conducted o n two commercial grazing dairy farms locate d in Trenton, FL. Both are fall calving herds and used similar genetics and management practices. The average milk production per cow was approximately 6,000 kg/lactation. A total of 1,263 la ctating dairy cows (457 Holsteins, 185 Jerseys, and 621 crossbreds) were enrolled. Crossbred cows population was mostly composed by F1 (50/50) and F2 (25/75) generation of crossbreeding between Holstein and Jersey genetics. Different genetic groups were ma naged together in a pasture based system in both herds. Cows were maintained under irrigated pasture paddocks of 2.7 ha and managed in a daily rotational program with a stocking rate of approximately 10 cows/ha. The pasture was composed of annual ryegrass ( Lolium multiflorum Lam.) during winter and early spring, Cynodon spp) during late spring and summer. Cows were offered variable amounts of concentrate (7 to 13 kg/cow/d) during and immediately after each milking according to forage availability and stage of lactation. The concentrate was based on soybean hulls, citrus pulp, whole cottonseed, cottonseed

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149 hulls, corn gluten feed, corn meal, soybean meal, molasses, and a mineral vitamin premix, and designed to contain approximatel y 15 % of crude protein 4.5% of fat, and 28% of neutral detergent fiber Cows were milked twice daily. Reproductive Management Cows were subjected to 100 d breeding seasons, from December 2008 to March 2009 in dairy A, and from January to April 2009 in dai ry B. Presynchronization treatments were scheduled such that all cows, within farm, received timed AI on the same day, which was considered d 0 of the breeding season and d 0 of the study. Non pregnant cows to the first AI had an additional opportunity to be inseminated on detection of estrus between d 19 and 35. On d 35, bulls were placed with the cows for an additional 65 d of natural service. Experimental Design and Randomization Within herd, cows were blocked by parity (primiparous and multiparous), bre ed group, and DIM. Within each block, cows were randomly assigned to 1 of 4 treatments in a 2 x 2 factorial, based on two presynchronization (Figure 5 1) and two resynchronization treatments (Figure 5 2). Presynchronization Treatments and Timed AI Protocol The presynchronization treatments were either a PGF based program ( Presynch ) consisting of 2 injections of PGF (Lutalyse sterile solution; 5 mg/mL of dinoprost tromethamine, Pfizer Animal Health, Madison, NJ ) administered 14 d apart and starting the t imed AI protocol 11 d later after the second PGF ; or a PGF GnRH based presynchronization program ( G6G ) consisting of an injection of PGF followed 3 d later by an injection of GnRH (Cystorelin; 50 g/mL of gonadorelin diacetate tetrahydrate, Merial Lt d., Inselin, NJ) and starting the timed AI protocol 6 d later. All

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150 cows were subjected to the 5 d timed AI protocol (Figure 5 1; Santos et al., 2010), and they were inseminated on d 0 regardless of detection of estrus. On d 3, tailheads were painted using an oil based tailpaint (Donaghy tail paint, Donaghy, Dunedin, NZ) for detection of estrus on the day of AI based on removal of tailpaint. The first postpartum insemination was performed by the same 9 technicians o n both farms. Seven Jersey (n = 728 AI), 4 Holstein (n = 398 AI), and 2 Swedish Red (n = 137 AI) sires were used and sires and techni cians were balanced across all four treatments. Resynchronization Treatments and Natural Service On d 12, all cows in each presynchronization treatment were submitte d to 1 of the 2 resynchronization treatments (Figure 5 2) according to the initial randomization. Cows in the control resynchronization ( RCON ) did not receive any further treatment, whereas cows resynchronized with a controlled internal drug release contai ning progesterone (Eazi Breed TM CIDR Cattle Insert; Pfizer Animal Health, Madison, NJ ) received an intravaginal insert from d 12 to 19 after the timed AI ( RCIDR ). T ailheads were painted on d 19 and they were observed once daily, after the morning milking, for signs of estrus between d 19 and 35. Cows in estrus were inseminated in the same morning. Tailpaint was re applied as needed and in all cows observed in estrus during the resynchronization perio d (d 19 to 35). Therefore, the four treatments were Presyn ch RCON (n = 319), Presynch RCIDR (n = 315), G6G RCON (n = 319), and G6G RCIDR (n = 310). On d 36, Holstein and Jersey bulls were placed with all cows for additional 65 d of natural service to complete the 100 d breeding season. Bulls between 18 and 36 mo nths of age were used at a ratio of 1 bull for every 20 nonpregnant cows at the beginning of the natural service period.

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151 Blood Samples Progesterone Analysis and Characterization of Ovarian Status On d 8, concurrent with the first GnRH of the timed AI pro tocol, blood was sampled by puncture of the coccygeal vein or artery into evacuated tubes containing K 2 EDTA (Becton Dickinson, Franklin Lakes, NJ). S amples were immediately placed o n ice and transported to the laboratory within 6 h of collection. Tubes we re centrifuged at 2,000 g for 15 min for plasma separation. Plasma samples were frozen at 30C and later analyzed for their concentrations of progesterone by RIA using a commercial kit (Coat a Count, Siemens Healthcare Diagnostics, Los Angeles, CA). Sam ples were analyzed in four assays and the sensitivity of the assays calculated at 2 SD below the mean counts per min at maximum binding was 0.05 ng/mL. The intra assay CV was calculated for each sample duplicate d and averaged 5.9%. Plasma samples of a cow 3 d after an injection of PGF (0.4 ng/mL) and on d 8 of the estrous cycle (4.0 ng/mL) were repeated several times in all assays to calculate the inter assay CV which averaged 20.4% and 5.5% for the samples containing 0.4 and 4.0 ng/mL, respectively. Ovarian status was categorized ac ng/mL or < 1 ng/mL. This cut off of 1 ng/mL was chosen based on receiver operator characteristic curve to predict P/AI on d 30 after the timed AI with highest combined sensitivity and specificity. At 1 ng/mL, th e sensitivity was 86.2%, whereas the specificity was 31.3%. Therefore, of all pregnant cows, 86.2% had progesterone concentration on Likewise, of all non pregnant cows, 31.3% had progesterone concentrati on ng/mL Twenty seven of the initial 1,263 cows did not have a blood sample collected and they were excluded from the statistical analyses of the effect of presynchronization treatment on ovarian status on d 8.

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152 Body Condition Score D ays in Milk and Milk Yield Cows were scored for body condition in a 1 to 5 scale ( BCS : 1= emaciated, 5= obese; Ferguson et al., 1994) on d 0 (timed AI) and 30 (first pregnancy diagnosis). For statistical analyses, cows were cat egorized accord change in BCS from AI to pregnancy diagnosis as lost, no change or gain. Cows were also categorized according to their DIM on d 0 as low (< 60 DIM), medium (60 to 80 DIM), or high (> 80 DIM). Milk yield was measured once during the study when cows averaged 90 DIM. Pregnancy Diagnoses and Calculation of Reproductive Responses Pregnancy was diagnosed in all cows on d 30 via ultrasonograph y of the uterus and its contents, and was characterized by visualization of an embryo with heartbeat. Cows with a corpus luteum and fluid in the ipsilateral uterine horn, but without an embryo with heartbeat were considered as not pregnant. Cows diagnosed as pregnant on d 30 were reexamined by transrectal palpation 35 d later. Cows reinseminated after the first AI were examined by ultrasound between 30 and 43 d after reinsemination, and those pregnant were reexamined by transrectal palpation between 63 and 76 d after reinsemination. For the purpose of describing the dates when pregnancies were diagnosed, the first diagnosis will be called d 30 and the second d 65 after AI for the first timed AI and the resynchronized insemination. Pregnancies from natural se rvice were diagnosed each 35 d after introduction of bulls and age of pregnancy was estimated based on size of the amniotic vesicle either by ultrasound (28 to 35 d of gestation) or by transrectal palpation (36 to 63 d of gestation).

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153 Pregnancy per AI ( P/AI ) was calculated as the number of pregnant cows on d 30 and 65 after an insemination divided by the total number of cows inseminated for the first and second AI. Re insemination rate was calculated as the number of nonpregnant cows on d 30 after the first AI that was reinseminated before introduction of the bulls. Pregnancy loss was calculated for first and second AI as the number of cows that lost pregnancy between gestation d 30 and 65 divided by the number of pregnant cows on d 30 of each diagnosis. Preg nancy during natural service was calculated as the number of cows pregnant to bulls divided by the number of cows that did not become pregnant to AI. Finally, pregnancy at the end of the study was calculated as the number of pregnant cows on d 65 after a b reeding (AI or natural service) divided by the total number of cows enrolled in the study. For survival analysis, cows that were sold, died or remained as nonpregnant at the end of the 100 d breeding season were censored when the respective event occurred. Statistical Analyses All statistical models included the effects of presynchronization, resynchronization, and interaction between the two main effects, all of which were forced in the final models. Additional covariates (BCS on d 0, BCS change between d 0 and 30, breed of cow, DIM at first AI, farm, progesterone category on d 8, parity, sire, and technician) were included when P Binary data were analyzed by logistic regression using the LOGISTIC procedure of SAS version 9.2 (SAS/STAT, SAS Insti tute Inc., Cary, NC, USA). A stepwise backward elimination was used and covariates were removed based on the Wald statistics criterion when P > 0.10. Adjusted odds ratio ( AOR ) and 95% CI were calculated.

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154 ortional hazard model with the PHREG procedure of SAS The hazard of pregnancy (adjusted hazard ratio, AHR ) estimates the relative rate of pregnancy according to the explanatory variables used in the model. The time variable used in the model was the inte rval in days between d 0 and pregnancy or censored (sold, dead, remained open on d 100). A cow was considered pregnant based on the d 65 pregnancy diagnoses. A stepwise backward elimination was used to remove covariates when P > 0.10. Proportionality was a ssessed by evaluating the Kaplan Meier curves. The median and mean days to pregnancy were obtained from the LIFETEST procedure of SAS Survival plots were generated with the MedCalc version 9.2 (MedCalc Software, Mariakerke, Belgium). Concentration of pro gesterone on d 8 and interval to reinsemination in cows rebred by AI were analyzed by ANOVA using GLM procedure of SAS Models included effects of presynchronization, resynchronization, interaction between presynchronization and resynchronization, BCS on d 0, breed of cow, farm, and parity. Differences with P P considered tendencies. Results The BCS did not differ among treatments and averaged 2.95 0.02 and 2.85 0.02 on d 0 and 30, respectively. Crossbred cows had greater ( P < 0.01) BCS than Holstei n and Jersey cows on d 0 (3.07 0.02 vs. 2.90 0.02 vs. 2.91 0.03) and on d 30 (2.98 0.02 vs. 2.81 0.02 vs. 2.78 0.03). Average milk yield did not differ among cows in the different treatments and averaged 27.0 0.6 kg/d, but Holsteins produced more ( P < 0.01) milk than crossbreds, and the latter more ( P < 0.01) than Jerseys (31.1 0.7 vs. 25.2 0.9 vs. 21.8 0.6 kg/d). As expected, DIM at d 0 were similar for the

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155 two presynchronization (G6G = 86.8 1.7 DIM, with a minimum of 38 and a median of 72 DIM, and Presynch = 88.6 1.9 DIM, with a minimum of 38 and a median of 72 DIM) and the two resynchronization treatments (RCIDR = 87.9 1.8 DIM, with a minimum of 38 and a median of 72 DIM, and RCON = 87.5 1.8 DIM, with a minimum of 38 and a medi an of 73 DIM); however, they differed ( P < 0.01) among breeds and Holsteins had fewer ( P < 0.001) DIM at first AI than the other breeds, but crossbreds and Jerseys did not differ (Holstein = 75.8 1.4 vs. crossbreed = 91.4 2.0 vs. Jersey = 95.9 3.7 DI M). Because no interactions between presynchronization and resynchronization treatments were observed for display of estrus, P/AI, pregnancy loss, and pregnancy rate, data are presented separately for the effects of presynchronization and resynchronization treatments. Presynchronization Treatments AI was greater ( P < 0.01) for G6G than Presynch (Table 5 1). In spite of the improvement in presynchronization of the estrous cycle with G6G, P/AI on d 30 and 65 did not diff er between the two presynchronization treatments, but pregnancy loss between d 30 and 65 after the first AI was greater ( P = 0.05) for G6G than Presynch. Nevertheless, there was an interaction between presynchronization treatment and ovarian status at firs t GnRH of the timed AI protocol (Figure 5 3). Within cows with progesterone < 1 ng/mL, G6G resulted in greater ( P < 0.05) P/AI on d 30 (41.5 vs. 26.3 %) and 65 (35.3 vs. 24.6%) after AI compared with Presynch. Conversely, within cows with progester P = 0.02) for Presynch than G6G on d 65 (45.1 vs. 52.6%) after AI. The concentration of progesterone for cows classified as <

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156 1 ng/mL at the first GnRH was greater ( P < 0.01) for G6G than Presynch (0.50 0.03 vs. 0.28 0. treatments and averaged 3.15 0.08 ng/mL. Presynchronization treatment did not affect fertility responses during the periods of reinsemination and natural service, which resulted i n similar proportions of cows pregnant at the end of the study. In fact, the median d ay to pregnancy were the same for G6G and Presynch because of the similar pregnancy rate (AHR = 0.96; 95% CI = 0.85 to 1.08; Table 5 2). Resynchronization Treatments The p timed AI were, as expected, similar between RCON and RCIDR (Table 5 3). The use of CIDR between d 12 and 19 after timed AI did not influence P/AI and pregnancy loss after the first AI Although RCIDR resulted in a similar proportion of nonpregnant cows reinseminated in estrus compared with RCON, it altered the pattern of return to estrus. Cows receiving a CIDR had a smaller incidence of estrus on d 19 and 20 (2.9 vs. 18.4%, P < 0.01), but greater on d 21 to 24 (62.6 vs. 50.0%, P < 0.01) than RCON cows, which resulted in a delay of 1.1 d in the mean interval to reinsemination. After d 24, the proportion of cows reinseminated in estrus did not differ ( P = 0.55) between RCON and RCIDR (34. 9 vs. 31.4%). The P/AI during the reinsemination period evaluated on d 30 and 65 after AI did not differ between RCIDR and RCON but, for cows reinseminated between d 21 and 24, it was less ( P = 0.01) for RCIDR than RCON (39.7 vs. 58.1%). A tendency ( P = 0. 08) for lower fertility in RCIDR compared with RCON cows was observed during natural service. Collectively, these differences resulted in a smaller ( P = 0.04) proportion of RCIDR than RCON cows pregnant at the end of the study (Table 5 3).

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157 Although the ra between RCON and RCIDR for all cows (Table 5 2), the same was not the case when only cows eligible to reinsemination were considered. When data were analyzed only with cows that did not become pre gnant to the first AI and were eligible to be reinseminated during the resynchronization period (after d 19), then those in RCIDR had a slower rate of pregnancy (AHR = 0.81; 95% CI = 0.68 to 0.97) than RCON cows. In fact, for those cows, the median d ay t o pregnancy were 64 (95% CI = 57 to 71) and 54 (95% CI = 46 to 64). Effects of Breed Holstein cows had, in general, poorer reproducti ve performance than Jersey and crossbred cows (Table 5 ng/mL on d 8 and in estrus at timed AI, and the risk to become pregnant after the first AI were all less ( P < 0.01) than those of Jersey and crossbred cows. Similar responses were observed after the first AI. Holstein cows were less likely ( P < 0.01) to be detected in estrus and reinseminated and had less P/AI on d 30 and 65 after the resynchronized AI than crossbred cows. During the natural service period, Holsteins were also less likely ( P < 0.01) to become pregnant than Jersey and crossbreds. Altogether, these di fferences resulted in a slower ( P < 0.01) rate of pregnancy (Table 5 2 ; Figure 5 4A ) and a smaller proportion of cows pregnant at the end of the study for Holsteins compared with Jersey or crossbreds. Ovarian Status at First GnRH on Study Day 8 Cows initi P < 0.01) P/AI at first AI (54.7 vs. 31.1%) and were more likely ( P = 0.01) to be reinseminated in estrus than cows with progesterone < 1 ng/mL (75.7 vs. 59.2%). The

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158 P/AI during reinsemin ation, however, was not influenced by ovarian status on d 8, and it averaged 46.3%. Despite lack of statistical effect ( P = 0.11) on the proportion of cows ng/mL = 45.0%), th P < 0.01) pregnancy rate (Table 5 2; Figure 5 4B), resulting in a greater ( P < 0.01) proportion of them pregnant at the end of the study (86.1 vs. 69.9%). Body Condition Score and D ays in Milk at First AI Cows w ith BCS < 2.75 were less likely ( P on d 8 than those with BCS of 2.75 to 3.00 and BCS > 3.00 (59.8, 81.7, and 83.7%, respectively). Furthermore, cows with BCS < 2.75 had less ( P < 0.01) expression of estrus at timed AI (20.3 vs. 37.0 vs. 47.0%) and P/AI after timed AI (34.3 vs. 51.3 vs. 55.9%). Also, they were less likely ( P < 0.01) to be reinseminated after the first AI (55.0 vs. 74.0 vs. 80.2%). Despite lack of statistical effect ( P = 0.24) on P/AI during reinsemina tion (41.3 vs. 44.4 vs. 52.2%), a smaller ( P = 0.01) proportion of cows with low BCS became pregnant to natural service (44.5 vs. 60.1 vs. 57.1%). Collectively, these differences resulted in a slower pregnancy rate and extended interval to pregnancy for co ws with BCS < 2.75 (Table 5 2). Cows classified as low DIM at timed AI were less likely ( P = 0.02) to have 8 (71.7 vs. 80.4 vs. 82.2%), and tended ( P = 0.09) to have less P/AI at timed AI (46.7 vs. 53.8 vs. 47.9%) than those c lassified as medium and high. Proportions of reinseminated cows (65.5 vs. 66.8 vs. 74.7%) and P/AI after re insemination (44.8 vs. 45.3 vs. 48.6%) were not affected ( P > 0.10) by DIM, but cows classified as low DIM were reinseminated later ( P < 0.01) than medium and high (25.0 vs. 23.3 vs. 23.3 d after AI). Pregnancy to natural service did not differ ( P = 0.21) among

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159 the three categories of DIM (48.3 vs. 62.3 vs. 55.7 %). In general, cows classified as medium DIM at the first AI had the best pregnancy rate (Table 5 2), and a greater ( P = 0.04) proportion of them were pregnant by 100 d of breeding (77.5 vs. 86.5 vs. 83.4%). Discussion This study evaluated strategies to optimize pregnancy at the first and resynchronized AI in grazing dairy cows under a defined breeding period. Timed AI was used to ensure that all cows would be inseminated on the first day of the breeding season and also had an additional opportunity of AI on return to estrus before being exposed to natural service. Overall, 49.5% of the cows be came pregnant at the first AI, but because of subsequent pregnancy loss, 44% established a pregnancy on d 65 of the study. Upon resynchronization, 67.1% of the cows became pregnant to insemination. These cows produce calves sired by AI and are therefore of higher genetic and economic value than those sired by natural service (McDougall and Compton, 2006). Presynch is commonly used to improve fertility of estrous cyclic cows subjected to timed AI programs, whereas G6G was expected to target anovular cows. T he former is commonly used in confinement dairy farms in the US and has been shown to improve P/AI of estrous cyclic cows (Moreira et al., 2001; Galvo et al., 2007a); however, the high prevalence of noncycling cows in seasonally calving dairy herds, 13 to 48% (Rhodes et al., 2003), might limit its efficacy. On the other hand, the incorporation of GnRH treatment as in the G6G was expected to induce estrous cyclicity and benefit anovular cows. GnRH is capable of inducing ovulation in 88% of anovular cows (G men et al., 2003), and G6G was highly effective to improve the responses to the hormonal treatments during the Ovsynch protocol (Bello et al., 2006). In fact, G6G resulted in a

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160 timed AI protocol in the present study Initiating the timed AI in early diestrus was expected to improve fertility of dairy cows (Bisinotto et al., 2010). Nevertheless, presynchronization method did not influence P/AI, although cows receiving G6G had gre ater pregnancy loss between 30 and 65 d of gestation after the first AI. The difference in pregnancy loss might suggest a benefit of the two sequential PGF treatments on the ability of cows to maintain pregnancy, although it had a minor impact on the reproductive performance throughout the entire study. The sequential injections of PGF in Presynch increase the opportunities for luteolysis and estrus. Stu dies have suggested a positive effect of PGF on reproduction of dairy cows presumably by improving uterine health (Kasimanickam et al., 2005; Galvo et al., 2009), although the impact of PGF on uterine health of dairy cows has not been consistent (Dubu c et al., 2011). It is interesting to note, however, that for cows with progesterone < 1 ng/mL at the initiation of the timed AI protocol, G6G resulted in greater P/AI than Presynch, but the idering the high efficiency of Presynch to synchronize the estrous cycle of cyclic cows, it is very likely that those with progesterone < 1 ng/mL were all anovular. On the other hand, a portion of the G6G cows with progesterone < 1 ng/mL was potentially es trous cyclic not in diestrus, with a CL in development because of delayed ovulation. In fact, progesterone concentration in this group of cows was greater for G6G than Presynch. It is possible that for estrous cyclic cows the Presynch is either a more effi cacious method than G6G to presynchronize the estrous cycle or that the 2 sequential PGF treatments benefit

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161 P/AI (Galvo et al., 2009) by influencing uterine health. On the other hand, the GnRH injection of G6G would result in high ovulation and formatio n of new CL as it has been demonstrated in anovular cows under confinement (Gmen et al., 2003; Galvo et al., 2007a). These cows would develop the ovulatory follicle under greater concentrations of progesterone than anovular cows in Presynch, which is imp ortant to improve P/AI (Bisinotto et al., 2010). Others have evaluated variations in presynchronization methods combining GnRH with PGF compared with the Presynch (Galvo et al., 2007a). Adding an injection of GnRH to the presynchronization program did not benefit P/AI in lactating dairy cows under confinement. When compared with no presynchronization, a combination of PGF and GnRH di d not increase P/AI in lactating dairy cows (Peters and Pursley, 2002). Recent work by our group demonstrated that presynchron ization of the estrous cycle benefited P/AI of grazing cows compared with no presynchronization or supplemental progesterone durin g the timed AI (Ribeiro et al., 2010). Collectively, these results indicate that either the Presynch or G6G methods of presynchronization were effective for improving fertility to a timed AI program in grazing dairy cows; although Presynch was superior in estrous cyclic cows, G6G constitute an alternative to shorten the length of the timed AI program (17 vs. 33 d), particularly in herds with high prevalence of anovular cows. Reinsemination of nonpregnant cows is another important component of a program to o ptimize reproductive efficiency in grazing dairy farms. The programs selected had a pre defined period of detection of estrus to restrict labor requirements with resynchronization between d 19 and 35. The use of the CIDR was expected to

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162 improve the synchro ny of return to estrus, and day 19 was selected for its removal to minimize the risk of depressing fertility of the resynchronized AI (Galvo et al., 2007b). As observed by others (El Zarkouny and Stevenson, 2004; Chebel et al., 2006; Galvo et al., 2007b) the CIDR altered the pattern of return to estrus. It concentrated estruses on d 2 to 4 d after insert removal, but it did not improve the proportion of nonpregnant cows reinseminated. In some cases, use of CIDR to resynchronize estrus has improved reinse mination of nonpregnant cows (Chenault et al., 2003), but this response has not been consistent. In fact, as observed in the current experiment, most studies have shown no benefit of the use of the CIDR to improve insemination of nonpregnant cows (Chebel e t al., 2006; Galvo et al., 2007b). Despite similar proportions of nonpregnant cows reinseminated, RCIDR cows detected in estrus between d 21 and 24 had reduced fertility compared with RCON cows in the same period. Chenault et al. (2003) also observed a d etrimental effect of the CIDR during resynchronization on P/AI which the authors associated with vaginitis reducing fertility (Chenault et al., 2003). Mucus score was not evaluated in the current study because several other authors were not able to associa te the appearance of the vaginal mucus with fertility in dairy cows following the use of intravaginal inserts (Galvo et al., 2004; Chebel et al., 2006; Galvo et al., 2007b). By design, RCON cows that were in estrus before d 19 were not inseminated; howev er, in RCIDR, progesterone from the insert likely prevented estrous expression and forced them to display estrus after d 19. For cows not bearing a CL, the CIDR would maintain subluteal concentrations of progesterone that extends the period of follicle dom inance and exposes the oocyte to increased LH pulsatility. Extending dominance is often

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163 detrimental to subsequent fertility (Inskeep et al., 2004). These results do not support the use of CIDR to optimize reinsemination of nonpregnant cows in grazing farms as used in the current study. Holsteins, Jerseys and Holstein x Jersey crossbreds were enrolled in the study, and these genetic groups had distinct milk production and reproductive performance under the nutritional and management methods used. Holsteins r eceived their first AI sooner postpartum than crossbred and Jerseys, and DIM at first AI influenced fertility of dairy cows. This difference in DIM might have contributed to the reduced pregnancy rate of Holsteins compared with the other genetic groups, al though we accounted for the differences in DIM among genetic groups by including it in all statistical models. Limited nutrition usually has more negative effects on fertility of animals that partition more nutrients toward milk than body reserves (Macdona ld et al., 2008) Holstein cows had less BCS than crossbreds at the beginning of the study, although it did not differ from that of Jerseys. However, Holsteins have greater requirements for maintenance and production because of larger body weight and incre ased production of milk. Therefore, when nutrient intake is limiting, cows of greater genetic potential for milk yield experience greater losses of body weight and body condition (Macdonald et al., 2008), which can compromise reproduction (Santos et al., 2 009). Others studies have also reported advantages in reproductive parameters of Jerseys and crossbreds compared with Holsteins, such as a shorter interval to first ovulation, fewer days open, greater estrous detection, and increased P/AI (Washburn et al., 2002; Freyer et al., 2008; Heins et al., 2008). In the current study, the estimated proportions of anovular cows, based on those with progesterone < 1 ng/mL from the Presynch treatment were

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164 32.0, 11.6 and 12.6% for Holstein, Jersey and crossbred cows, res pectively. Delayed estrous cyclicity has a depressive impact on fertility (Rhodes et al., 2003; Santos et al., 2009). It is possible that the observed differences among the genetic breeds might have been mediated by differences in nutrient balance in early lactation. Another possibility is a potential genetic difference among the groups, as Holsteins and Jerseys have suffered different changes in reproductive efficiency over time, and crossbred cows have the advantage of hybrid vigor and less inbreeding. Th erefore, in a production system that limits nutrient intake, the combination of different nutrient needs for maintenance and production, BCS, estrous cyclicity, and genetics for fertility might explain the worse reproductive efficiency of Holsteins compare d with Jersey and crossbred cows. Summary Presynchronization with PGF /GnRH as in the G6G increased the proportion of Presynch, but it did not influence P/AI and increase d risk of pregnancy loss after timed AI. At first AI, Presynch was generally more beneficial to cows starting the timed AI with AI with progesterone < 1 ng/mL. Resynchroniza tion with CIDR did not increase the rate of reinsemination of nonpregnant cows after the first AI, and resulted in a smaller proportion of cows pregnant at the end of the breeding season. Finally, combining the proper genetics and management to the type of production system is expected to optimize reproductive efficiency of the herd. The reproduction of crossbred and Jersey cows were generally superior to that of Holsteins. Finally, cows with a minimum BCS of

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165 2.75, starting the timed AI program with progest 60 DIM were all important factors that benefited reproduction.

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166 Table 5 1. Effect of presynchronization treatments on reproductive outcomes of grazing dairy cows Presynchronization treatment 1 G6G Presynch AO R (95% CI) 2 P d 8 3 82.0 (506/617) 74.3 (460/619) 0.57 (0.43 0.77) <0.01 Timed AI Detected in estrus 34.5 (217/629) 36.1 (229/634) 1.02 (0.80 1.30) 0.84 Pregnant, d 30 49.9 (312/625) 49.1 (310/632) 1.10 (0.86 1.36) 0.60 Pregnant, d 65 43.3 (269/622) 45.1 (285/632) 1.10 (0.87 1.38) 0.62 Pregnancy loss 4 12.9 (40/309) 8.1 (25/310) 0.59 (0.34 0.99) 0.05 Reinsemination in estrus Reinseminated 5 68.7 (215/313) 70.5 (227/322) 0.92 (0.65 1.31) 0.66 Day of AI (LSM SEM) 24.1 0.5 24.0 0.5 ---------0.75 Pregnant, d 30 48.6 (104/214) 53.2 (117/220) 1.19 (0.80 1.76) 0.39 Pregnant, d 65 45.8 (98/214) 49.6 (109/220) 1.16 (0.79 1.72) 0.44 Pregnancy loss 6 5.8 (6/104) 6.8 ( 8/117) 1.18 (0.37 3.76) 0.78 Pregnant to natural service 7 58.3 (147/252) 51.5 (122/237) 0.87 (0.59 1.28) 0.48 Pregnant end of the study 8 83.2 (520/625) 81.8 (517/632) 0.90 (0.66 1.24) 0.54 1 Presynch = two injections of PGF given 14 d apart and starting the timed AI protocol 11 d later; G6G = PGF injection followed 3 d later by GnRH injection and starting the timed AI protocol 6 d later. 2 AOR = adjusted odds ratio; CI = confidence interval; G6G is the reference for comparison. 3 Blood was not sampled from twelve G6G and fifteen Presynch cows. 4 Number of pregnant cows on d 30 that were not pregnant on d 65 divided by the number of pregnant cows on d 30. Three G6G cows left the study before pregnancy reconfirmation on d 65 after AI. 5 Proportion of nonpregnant cows reinseminated by AI after detection of estrus between d 19 and 35 after timed AI. 6 Number of pregnant cows on d 30 that were not pregnant on d 65 divided by the number of pregnant cows on d 30 after reinsemination. 7 Proportion of non pregnant cows to AI that became pregnant to natural service. 8 Proportion of cows pregnant at the end of 100 d study.

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167 Table 5 2. cows Item Median day to pregnancy (95% CI) 1 Adjus ted hazard ratio 95% CI P Presynchronization 2 Presynch 22 (21 24) Referent --------G6G 22 (20 23) 0.96 0.85 1.08 0.50 Resynchronization 3 RCON 22 (20 23) Referent --------RCIDR 22 (20 24) 0.93 0.82 1.05 0.24 Breed Holstein 33 (24 43) Referent --------Jersey 21 (0 23) 1.65 1.36 1.99 < 0.01 Crossbred 0 (0 21) 1.52 1.31 1.77 < 0.01 Progesterone at 1 st GnRH of timed AI < 1 ng/mL 43 (30 58) Referent --------1 ng/mL 20 (0 21) 1.46 1.23 1.73 < 0.01 BCS on d 0 < 2.75 44 (35 61) Referent --------2.75 to 3.0 21 (20 23) 1.48 1.22 1.78 < 0.01 > 3.0 0 (0 21) 1.75 1.44 2.14 < 0.01 Days in milk on study d 0 < 60 23 (22 29) Referent --------60 to 120 20 (0 22) 1.20 1.03 1.40 0.02 > 120 22 (20 24) 1.07 0.91 1.25 0.43 1 CI = confidence interval. 2 later; G6G = PGF injection followed 3 d later by GnRH injection and starting the timed AI protocol 6 d later. 3 All cows were observed daily for signs of estrus f rom d 19 to 35. RCON = cows received no further treatment; RCIDR = cows received a controlled internal drug release containing progesterone between d 12 and 19.

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168 Table 5 3. Effect of resynchronization treatment on reproductive responses of grazing dairy co ws Resynchronization treatment 1 RCON RCIDR AOR (95%CI) 2 P 8 3 78.0 (490/628) 78.3 (476/608) 0.96 (0.72 1.28) 0.77 Timed AI Detected in estrus 36.5 (233/638) 34.1 (213/625) 0.89 (0.70 1.13) 0.32 Pregnant, d 30 48.6 (308/634) 50.4 (314/623) 1.10 (0.86 1.36) 0.50 Pregnant, d 65 43.1 (273/633) 45.3 (281/621) 1.09 (0.87 1.38) 0.44 Pregnancy loss 4 11.1 (34/307) 9.9 (31/312) 0.59 (0.53 1.49) 0.66 Reinsemination in estrus Reinseminated 5 69.3 (226/326) 69.9 (216/309) 0.99 (0.70 1.41) 0.97 Day o f AI (LSM SEM) 23.5 0.5 24.6 0.5 -------0.04 Pregnant, d 30 54.3 (121/223) 47.4 (100/211) 0.78 (0.53 1.14) 0.20 Pregnant, d 65 51.6 (115/223) 43.6 (92/211) 0.74 (0.51 1.09) 0.13 Pregnancy loss 6 5.0 (6/121) 8.0 (8/100) 1.92 (0.61 6.09) 0.27 Pregnant to natural service 7 59.1 (143/242) 51.0 (126/247) 0.71 (0.48 1.04) 0.08 Pregnant end of the study 8 84.4 (535/634) 80.6 (502/623) 0.73 (0.53 0.99) 0.04 1 All cows were observed daily for signs of estrus from d 19 to 35. RCON = c ows received no further treatment; RCIDR = cows received a controlled internal drug release containing progesterone between d 12 and 19. 2 AOR = adjusted odds ratio; CI = confidence interval; RCON is the reference for comparison. 3 Blood was not sampled fr om ten RCON and seventeen RCIDR cows. 4 Number of pregnant cows on d 30 that were not pregnant on d 65 divided by the number of pregnant cows on d 30. One RCON and two RCIDR cows left the study before pregnancy reconfirmation on d 65 after AI. 5 Proportion of nonpregnant cows reinseminated by AI after detection of estrus between d 19 and 35. 6 Number of pregnant cows on d 30 that were not pregnant on d 65 divided by the number of pregnant cows on d 30 after reinsemination. 7 Proportion of nonpregnant cows t o AI that became pregnant to natural service. 8 Proportion of cows pregnant at the end of 100 d study.

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169 Table 5 4. Effect of breed on reproductive responses of grazing dairy cows Breed Item Holstein Jersey Crossbred AOR Jersey (95% CI) 1 AOR crossbred (95% CI) P 8 2 68.3 (308/451) 82.5 (151/183) 84.2 (507/602) 1.94 (1.24 3.05) 1.94 (1.40 2.70) < 0.01 Detected in estrus 25.6 (117/457) 43.8 (81/185) 39.9 (248/621) 1.92 (1.32 2.79) 1.33 (1.00 1.78) < 0.01 Timed AI Pre gnant, d 30 40.0 (182/455) 51.1 (94/184) 56.0 (346/618) 1.68 (1.16 2.43) 1.79 (1.35 2.38) < 0.01 Pregnant, d 65 34.7 (157/453) 47.3 (87/184) 50.2 (310/617) 1.79 (1.23 2.60) 1.77 (1.32 2.36) < 0.01 Pregnancy loss 3 12.8 (23/180) 7.5 (7/94 ) 10.1 (35/345) 0.55 (0.22 1.34) 0.84 (0.47 1.50) 0.42 Reinsemination in estrus Reinseminated 4 62.2 (167/273) 80.0 (72/90) 74.6 (203/272) 2.47 (1.38 4.43) 1.46 (0.99 2.16) < 0.01 Pregnant, d 30 37.6 (65/161) 46.3 (36/72) 59.7 (120 /201) 1.46 (0.83 2.56) 2.16 (1.42 3.30) < 0.01 Pregnant, d 65 39.8 (64/161) 45.8 (33/72) 54.3 (110/201) 1.27 (0.72 2.23) 1.81 (1.19 2.76) 0.02 Pregnancy loss 5 1.5 (1/65) 8.3 (3/36) 8.3 (10/120) 5.91 (0.57 61.30) 7.73 (0.92 64.76) 0.17 Pregnant to natural service 6 44.0 (102/232) 69.8 (44/63) 63.4 (123/194) 3.48 (1.84 6.56) 1.51 (0.98 2.33) < 0.01 Pregnant end of the study 7 71.4 (325/455) 89.7 (165/184) 88.5 (547/618) 3.60 (2.10 6.19) 2.38 (1.67 3.40) < 0.01 1 AOR = adjusted o dds ratio; CI = confidence interval; Holstein is the reference for comparison. 2 Blood was not sampled from six Holstein, two Jersey and nineteen crossbred cows. 3 Number of pregnant cows on d 30 that were not pregnant on d 65 divided by the number of preg nant cows on d 30. Two Holstein and one crossbred cow left the study before pregnancy reconfirmation on d 65 after AI. 4 Proportion of nonpregnant cows reinseminated by AI after detection of estrus between d 19 and 35. 5 Number of pregnant cows on d 30 tha t were not pregnant on d 65 divided by the number of pregnant cows on d 30 after reinsemination. 6 Proportion of nonpregnant cows to AI that became pregnant to natural service. 7 Proportion of cows pregnant at the end of 100 d study.

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170 Figure 5 1. Diagram of activities for the presynchronization treatments and timed artificial insemination program. Presynch = two injections of PGF given 14 d apart and starting the timed AI protocol 11 d later. G6G = injection of PGF followed 3 d later by an injection of GnRH and starting the timed AI protocol 6 d later.

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171 Figure 5 2. Diagram of activities during the resynchronization and natura l service periods. CIDR = controlled internal drug release containing 1.38 g of progesterone; RCIDR = treatment with CIDR; RCON = no treatment with CIDR. Cows in both treatments were observed once daily for signs of estrus between d 19 and 35, with reinsem ination performed on the same morning as detected in estrus. On d 36, bulls were placed with the cows for the remaining of the study.

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172 Figure 5 3. Pregnancy on d 30 (A) and 65 (B) after the first AI according to presynchronization treatment and categor y of progesterone concentration in plasma at first GnRH of timed AI protocol. For pregnancy on d 30, effect of presynchronization ( P = 0.60), progesterone category ( P < 0.001), and interaction between presynchronization and progesterone category ( P < 0.001 ). For pregnancy on d 65, effect of presynchronization ( P = 0.62), progesterone category ( P < 0.001), and interaction between presynchronization and progesterone category ( P < 0.001).

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173 Figure 5 4. Survival curves for interval to pregnancy according to breed (panel A) and progesterone category at the first GnRH of the timed AI (panel B).

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174 CHAPTER 6 EFFECTS OF PRESYNCHR ONIZATION AND LENGTH OF PROESTRUS ON PREGNANCY PER A RTIFICIAL I NSEMINATION OF GRAZING DAIRY COW S SUBJECTED TO THE 5 D TIMED A RTIFICIAL I NS EMINATION PROTOCOL Objectives were to compare the effects of two methods of presynchronization and two lengths of proestrus on fertility of grazing dairy cows subjected to the 5 d timed artificial insemination (AI) protocol. Lactating dairy cows (n = 1,754 ) from three farms using seasonal grazing were blocked within farm by breed, parity, and d ays in milk (DIM). Within each block, cows were randomly assigned to 1 of 4 treatments in a 2 x 2 factorial arrangement, with two methods of presynchronization and tw o lengths of proestrus. Presynchronization treatments consisted of two injections of PGF given 14 d apart, on study d 32 and 18, and initiation of the timed AI prot ocol 10 d later (Presynch), or d ouble Ovsynch (DO) consisting of GnRH on d 25, PGF on d 18, GnRH on d 15, and starting the timed AI protocol 7 d later. The two lengths of proestrus within the 5 d timed AI protocol consisted of GnRH on d 8, PGF on d 3 and 2, and GnRH+AI either at 58 h (COS58) or 72 h (COS72) after the d 3 PGF injection. Ovaries were scanned by ultrasonography twice (10 days apart) before enrollment i n the study to determine estrous cyclic status. Blood was sampled and analyzed for concentrations of estradiol on the day of AI. The pregnancy per AI (P/AI) was determined 30 and 65 d after AI. Presynchronization did not affect the concentration of estradi ol at AI (DO = 6.4 vs. Presynch = 5.8 pg/mL), detection of estrus at AI (20.8 vs. 25.9%), P/AI on d 30 (56.8 vs. 59.1%) and 65 (52.5 vs. 52.4%) after first insemination. Cows receiving COS72 had increased concentration of estradiol (6.6 vs.5.5 pg/mL) and d etection of estrus at AI (28.5 vs. 10.8%) compared with cows receiving COS58. Length of proestrus did not affect P/AI on d 30 (58.7 vs. 56.1%) but, in Presynch cows, COS58

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175 was detrimental to fertility on d 65 (54.9 vs. 46.5%). Pregnancy loss was greater fo r Presynch than DO (7.6 vs. 11.3%), but length of proestrus had no impact on losses of pregnancy in the first 65 d of gestation. Estrous cyclic cows had greater P/AI than anovular cows on d 30 (61.7 vs. 35.1%) and 65 (56.1 vs. 30.7%), but no interaction be tween estrous cyclic status and treatments were detected. Crossbred Holstein/Jersey cows had sup erior fertility than their pure bred counterparts. Presynch and DO resulted in similar fertility, but limiting the length of proestrus to 58 h reduced P/AI in th e 5 d timed AI protocol when cows had their estrous cycle presynchronized with the Presynch, but not the DO. I ntroduct ory Remarks Timed artificial insemination (AI) protocols have been used to manage reproduction of grazing cows particularly in seasonally breeding herds at the first postpartum AI in order to maximize the proportion of cows pregnant early in the breeding season. Timed AI results in high submission rate which is important to maintain a concentrated calving pattern and to maximize profitabilit y (McDougall, 2010). Therefore, the development of programs that improve fertility of first AI are important. It was demonstrated recently that presynchronization of the estrous cycle improves fertility of grazing dairy cows subjected to timed AI, and the benefit to pregnancy per AI (P/AI) was greater than that for incorporating progesterone during the synchronization pr ogram (Ribeiro et al., 2010). Presynchronization increased the proportion of cows in diestrus and ovulation to the first gonadotropin relea sing hormone ( GnRH ) injection when the timed AI protocol was initiated (Ribeiro et al., 2010). Inducing cows to be in diestrus and increasing follicle turnover when the timed AI program is initiate d usually improves P/AI (Moreira et al., 2001; Galvo et al ., 2007; Bisinotto et al., 2010a).

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176 Presynchronization programs based solely on prostaglandin ( PG ) F injections such as the Presynch protocol (Moreira et al., 2001) target estrous cyclic cows to initiate the timed AI in early diestrus. However, these pro grams ha ve limited or no benefits to fertility of anovular cows, as cows without a corpus luteum (CL) do not respond to PGF Based on this concept, presynchronization protocols including the use of GnRH injections (Bello et al., 2006; Galvo et al., 2007 ; Souza et al., 2008) or progesterone supplementation (Chebel et al., 2006; Stevenson, 2011) have been proposed to induce estrous cyclicity in anovular cows and better synchronize follicle development when the timed AI protocol is initiated When compared with the Presynch protocol, presynchronization that incorporates a single GnRH injection with PGF did not benefit fertility of dairy cows in confinement (Galvo et al., 2007) or grazing farms (Ribeiro et al., 2011). However, when cows were subjected to the double Ovsynch (DO) protocol, P/AI improved compared with that of cows subjected to the Presyn ch (Souza et al., 2008). The increment in fertility caused by the DO was observed only in primiparous cows. Another alternative to enhance fertility of dairy cows is to alter the length of proestrus and optimize the periovulatory concentrations of estrad iol. This approach might be particularly important in the 5 d timed AI protocol, which results in smaller ovulatory follicle diameter, reduced concentrations of estradiol during proestrus, and a smaller proportion of cows in estrus on the day of AI (Santos et al., 2010a). In beef cows subjected to the 5 d timed AI protocol, the benefits of reducing the interval from the first GnRH to the first PGF of the program were only observed when the proestrus was extended to 72 h (Bridges et al., 2008). When insemi nation was performed at 72 h

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177 after induction of CL regression, administration of GnRH at 56 or 72 h resulted in similar fertility in high producing dairy cows (Bisinotto et al., 2010b), but not in dairy heifers (Lima et al., 2011). The responses to alterin g the length of proestrus might vary with method of presynchronization. The DO is expected to better synchronize follicle development at the beginning of the 5 d timed AI protocol, which might make cows in this program less sensitive to changes in length o f proestrus. The objectives of the present study were to compare the impact of two methods of presynchronization and two lengths of proestrus on fertility responses of grazing dairy cows subjected to 5 d timed AI protocol. The hypotheses were that presync hronization using DO would improve P/AI of grazing dairy cows compared with Presynch, primarily because of a benefit in anovular cows. Furthermore, increasing the length of proestrus without altering the timing of insemination relative to GnRH would increa se estradiol concentrations during proestrus, increase estrous expression and improve P/AI in cows subjected to the 5 d timed AI program. Materials and Methods Cows, Pasture s and Management The study was conducted in three commercial grazing dairy farms (A : n = 563; B: n = 607; C: n = 585) located in Levy County, FL. All farms were fall calving herds and used similar genetics and management practices. The average milk production per cow was approximately 6,000 kg/lactation. A total of 1,754 lactating dairy cows (226 Holsteins, 424 Jerseys, and 1,104 crossbreds) were enrolled in the study. Crossbred cows population was mostly composed by F1 (50/50) and F2 (25/75) generation of crossbreeding between Holstein and Jersey genetics. Different genetic groups were m anaged together in a pasture based system in all farms. Cows were maintained under

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178 irrigated pasture paddocks of 2.7 ha and managed in a daily rotational program with a stocking rate of approximately 10 cows/ha. The pasture was composed of annual ryegrass ( Lolium multiflorum Bermudagrass ( Cynodon spp) during late spring and summer. Cows were offered variable amounts of concentrate (7 to 13 kg/cow/d) during and immediately after each milking according to forage availability and stage of lactation. The concentrate was based on soybean hulls, citrus pulp, whole cottonseed, cottonseed hulls, corn gluten feed, corn meal, soybean meal, molasses, and a mineral vitamin premix, and designed to contain approximatel y 15 % of crude protein 4.5% of fat, and 28% of neutral detergent fiber Cows were milked twice daily. Experimental Design and Treatments Within farm, cows were blocked by breed, parity (primiparous and multiparous), and d ays in milk ( DIM ). Within each blo ck, cows were randomly assigned to 1 of 2 presynchronization treatments. Study d 0 was considered the day of timed AI. Cows in the Presynch (n = 872) received two subcutaneous injections of PGF (Lutalyse sterile solution; 5 mg/mL of dinoprost tromethamine, Pfizer Animal Health, Madison, NJ) administered 14 d apart and starting the timed AI protocol 10 d later. Cows in DO (n = gonadorelin diacetate tetrahydrate, Intervet Schering Plough Animal Health, Summit, NJ) followed 7 d later by an injection of 25 mg of PGF and a second injection of GnRH 3 d after the PGF injection, and starting the timed AI protocol 7 d la ter (Figure 6 1). Within each of the two presynchronization treatments, cows were randomly assigned in blocks of 3 to the 5 d timed AI protocol, with 1 cow assigned to a proestrus of 58 h ( COS58, n = 510) and 2 cows to a proestrus of 72 h (COS72, n = 1,244 ). The 5

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179 d timed AI protocol consisted of an injection of GnRH on study d 8, followed by two injections of PGF on study d 3 and 2, and a second injection of GnRH concurrent with timed AI either 58 (COS58) or 72 h (COS72) after the PGF on study d 3 (Figure 6 1). This resulted in a 2 x 2 factorial arrangement of treatments with four treatment combinations: DO COS58 (n = 252); DO COS72 (n = 630); Presynch COS58 (n = 258); Presynch COS72 (n = 614). Ovarian Ultrasonography and Determination of Estrous Cyclicity The ovaries of all cows were examined by ultrasonography (Easy Scan, BCF Technology, Livingston, UK) us ing a 7.5 MHz linear transducer on study d 42 and 32. Presence of a corpus luteum ( CL ) in at least one of the two ultrasonographic examinations characterized an estrous cyclic cow, whereas lack of CL in both examinations characterized an anovular cow. Bl ood Samples and Estradiol Analysis Blood was sampled by puncture of the coccygeal vein or artery into evacuated tubes containing K 2 EDTA (Becton Dickinson, Franklin Lakes, NJ) from 79 multiparous crossbred cows in one farm immediately before the final GnRH and AI (DO COS58 = 20; DO COS72 = 19; Presynch COS58 = 21; Presynch COS72 = 19). Blood samples were immediately placed in ice and transported to the laboratory within 4 h of collection. Tubes were centrifuged at 2,000 g for 15 min for plasma separation. Plasma samples were frozen at 30 C and later analyzed for their concentrations of estradiol by RIA using a commercial kit (Estradiol Double Antibody, Siemens Healthcare Diagnostics, Los Angeles, CA), which was previously validated for use in bovine samp les (Siddiqui et al., 2009). Briefly, standards with concentrations of 0.39, 0.78, 1.56, 3.12, 6.25, 12.5, and 25.0 pg/mL were prepared by e stradiol, Sigma

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180 Aldrich, St. Louis, MO) in steroid free bovine plasma to create the standard curve. Plasma from a cow exhibiting spontaneous estrus and charcoal stripped plasma from a 3 w ee k s old male calf were used as positive (~15.6 pg/mL) and negative (~0.07 pg/mL) controls, respectively. In addition, prepared samples with concentrations of 2.5, 5.0 and 10.0 pg/mL were also incorporated into each assay to estimate the extraction efficiency. Duplicate standards (500 free plasma) had lipids extracted using 3.0 mL of diethyl ether. Samples were mixed in 13 mL borosilicate tubes using a vortex mixer, allowed to settle for 1 min at room temperature and th en incubated at 80 C for 30 min. The supernatant with the extract lipids in diethyl ether were then transferred to a 5.5 mL borosilicate tube. The ether was allowed to evaporate overnight. The next morning, 0.5 mL of diethyl ether was pipette into each t ube to dissolve lipids attached to the tube wall and sediment them to the bottom to increase extraction recovery of estradiol. From this point, instructions of the commercial kit and reference validation (Siddiqui et al., 2009) were followed. The sensitivi ty of the assay was 0.15 pg/mL calculated at 2 SD below the mean counts per minute at maximum binding. Samples were extracted and analyzed in duplicates and repeated when the CV between duplicates was > 15%. Samples were analyzed in three assays. The avera ge CV for all duplicates in the three assays was 9.0 %. For samples containing 2.5, 5.0 and 10.0 pg/mL that were repeated throughout each assay, the intra assay CV averaged 12.2%, and the inter assay CV was 15.3%. Detection of Estrus Body Condition Score and D ays in Milk On study d 2, tailheads were painted using paintsticks (All Weather Paintstick; LA CO Industries, Chicago, IL) and removal of tailpaint was used as indicator of estrus on the day of timed AI. Cows were scored for body condition using a 1 to 5 scale ( BCS :

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181 1= emaciated, 5= obese; Ferguson et al., 1994) at AI and 30 d later. For statistical were catego rized according to change in BCS from AI to pregnancy diagnosis as having lost body condition, no change in BCS, or having gained BCS. Cows were also categorized according to DIM at AI as low when DIM < 61, moderate when between 61 and 90, and high when > 90. Remaining Breeding Season After the first AI, cows in farm A were observed for estrus from d 19 to 29 after insemination and bulls were introduced on d 30 as previously described (Ribeiro et al., 2011). Briefly, the tailheads were painted with tailpai nt on d 18 after the first AI and cows were observed once daily, after the morning milking, for signs of estrus based on removal of tailpaint. Cows in estrus were inseminated in the same morning. Tailpaint was re applied as needed and in all cows. On d 30, Jersey bulls were placed with all cows for additional 70 d of natural service to complete the 100 d breeding season. Bulls between 18 and 24 months of age were used at a ratio of 1 bull for every 20 nonpregnant cows at the beginning of the natural service period. Subsequent inseminations for cows in farms B and C were not evaluated because either they were not re inseminated or pregnancy diagnoses were not performed by decision of the farm. Pregnancy Diagnoses and Calculation of Reproductive Responses Preg nancy was diagnosed in all cows despite reinsemination via ultrasonography of the uterus and its content on study d 30, and it was characterized by visualization of a live embryo. Cows diagnosed as pregnant on d 30 were reexamined by transrectal palpation 35 d later. In farm A, reinseminated cows were examined by transrectal

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182 palpation between 36 and 46 d after AI. Pregnancies from natural service were diagnosed each 35 d after introduction of bulls and age of pregnancy was estimated based on size of the amn iotic vesicle either by ultrasound (28 to 35 d of gestation) or by transrectal palpation (36 to 63 d of gestation). Pregnancy per AI for first insemination was calculated as the number of pregnant cows on d 30 and 65 divided by the total number of cows ins eminated. Pregnancy loss was calculated for first AI as the number of cows that lost pregnancy between gestation d 30 and 65 divided by the number of pregnant cows on d 30. Re insemination in farm A was calculated as the number of nonpregnant cows on d 30 after the first AI that was reinseminated before introduction of the bulls. Pregnancy per AI for second insemination was calculated as the number of pregnant cows on gestation d 41 5 divided by the total number of cows reinseminated. Pregnancy during nat ural service was calculated as the number of cows pregnant to bulls divided by the number of cows that did not become pregnant to AI. Finally, pregnancy at the end of the study was calculated as the number of pregnant cows on d 65 after a breeding (AI or n atural service) divided by the total number of cows enrolled in the study. For survival analysis, cows that were sold, died or remained as nonpregnant at the end of the 100 d breeding season were censored when the respective event occurred. Statistical Ana lyses Binary data were analyzed using the GLIMMIX procedure of SAS version 9.2 (SAS/STAT, SAS Institute Inc., Cary, NC, USA) fitting a binary distribution and a logit link. All statistical models included the fixed effects of method of presynchronization, length of proestrus, interaction between presynchronization and proestrus. Farm was a random effect all models. Univariable analyses were performed to select covariates

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183 (parity, breed of cow, DIM at first AI, BCS at AI, BCS change from AI to d 30) based o n significance ( P < 0.10) to build multivariate models. For analyses of P/AI on d 30 and 65 and pregnancy loss, the effects of sire, technician and estrous cyclicity were also evaluated by univariable analyses before inclusion in the final models. Multivar iable models were then created with covariates that were significant from univariable analyses. Individual covariates were removed from the multivariable models in a stepwise fashion if P > 0.10. Method of presynchronization, length of proestrus, and inter action between presynchronization and length of proestrus were forced in the final multivariable models. Model fitting was assessed using the fit statistics of GLIMMIX. Concentration of estradiol at AI and interval to reinsemination in cows rebred by AI i n Farm A were analyzed by ANOVA using the GLM procedure of SAS The statistical models included the effects of method of presynchronization, length of proestrus, interaction between presynchronization and length of proestrus, parity, breed of cow, estrous cyclic status, and interaction between method of presynchronization and parity and estrous cyclic status. model using the PHREG procedure of SAS The adjusted hazard ratio ( AH R ) and respective 95% CI were calculated. The time variable used in the model was the interval in days between study d 0 and pregnancy or when a cow was censored either because she was sold, died or remained nonpregnant on study d 100. Pregnancy was consid ered based on diagnoses performed 65 d after AI to account for pregnancy losses between 30 and 65 d of gestation. The statistical model included the effects of method of presynchronization, length of proestrus, interaction between

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184 presynchronization and le ngth of proestrus, parity, breed of cow, DIM at first AI, BCS at AI, BCS change from AI to d 30, estrous cyclic status, and interactions between presynchronization and parity, breed and estrous cyclic status. A stepwise backward elimination was used to rem ove covariates when P > 0.10. Method of presynchronization and length of proestrus were forced in the final models. Proportionality was assessed by evaluating the Kaplan Meier curves. The median and mean days to pregnancy were obtained from the LIFETEST pr ocedure of SAS Survival graphs were generated with the MedCalc version 9.2 (MedCalc Software, Mariakerke, Belgium). Differences with P P considered tendencies. Results The body condition of cows did not differ with treatments and the mean ( SD) and median BCS were, respectively, 2.97 0.34 and 3.00 at AI, and 3.10 0.41 and 3.0 0 on study d 30. The proportion of anovular cows in the study was 14.1%, ranging from 8.0 to 20.2% according to farm. The proportions of estrous cyclic cows did not differ with method of presynchronization (DO = 85.8 vs. Presynch = 85.9%; P = 0.64), length of proestrus (COS58 = 84.7 vs. COS72 = 86.3 % ; P = 0.46), or breed of cows (Holstein = 89.4 vs. Jersey = 77.4 vs. crossbred = 88.4%; P = 0.28). As expected, estrous cyclicity was influenced ( P < 0.01) by parity (multiparous = 91.3 vs. primiparous = 80.0%; P < 0.01), BCS at AI (thin = 66.3 vs. moderate = 84.9 vs. high = 96.3%), and DIM at AI (low = 57.3 vs. moderate = 81.6 vs. high = 92.1%)

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185 Estrus at AI and Estradiol Concentrations Method of presynchronization did not affect the concentration of estradiol at AI and the proportion of cows in estrus at AI (Table 6 1). Conversely, cows receiving the COS72 had increased estradiol concentration ( P = 0.04) and detection of estrus ( P < 0.001) at AI compared with cows in COS58 (Table 6 1). There was no interaction between method of presynchronization and length of proestrus on estradiol concentration and detection of estrus at AI. Estrous cyclic cows had greater ( P < 0.001) concentration of estradiol at AI than anovular cows, but the proportion of cows detected in e strus at AI was not influenced by estrous cyclic status (Table 6 2). No interaction between estrous cyclic status and method of presynchronization were detected for estradiol concentration and detection of estrus at AI. It is interesting to note that the c oncentrations of estradiol did not differ between cows observed or not in estrus at AI, but they were greater ( P < 0.01) in cows that became pregnant than those nonpregnant on d 30 after AI (8.2 0.5 vs. 5.5 0.6 pg/mL). Pregnancy per AI and Pregnancy Lo ss Presynchronization treatment did not affect P/AI on d 30 and 65 after insemination and, overall, 56.8 and 59.1% of the DO and Presynch cows were pregnant on d 30 (Table 6 1). Length of proestrus did not affect P/AI on d 30. However, a tendency for an in teraction ( P = 0.10) between presynchronization treatment and length of proestrus was detected for P/AI on d 65. For cows in DO, altering the length of proestrus had no effect on P/AI, but for Presynch, reducing the proestrus to 58 h compromised fertility. Pregnancy loss was greater ( P = 0.03) for Presynch than for DO, but no impact of length of proestrus or interaction between presynchronization treatment and length of proestrus were observed.

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186 Anovular cows had smaller ( P < 0.001) P/AI than estrous cyclic cows on d 30 and 65 after AI, but no interactions were detected between estrous cyclicity and presynchronization treatment (Table 6 2) or length of proestrus. The risk of pregnancy loss did not differ with estrous cyclicity status. Also, BCS of cows at AI and the change in BCS from AI to d 30 influenced ( P < 0.001) P/AI. On d 65 after AI, P/AI increased ( P < 0.001) with increasing BCS ( BCS 2.5 = 31.7 vs. BCS 2.75 to 3.0 = 51.6 vs. 3.25 = 63.3%). Similarly, cows that gained BCS in the first 30 d after insemination had greater P/AI than those that maintained or lost BCS (gained = 56.7 vs. no change = 48.6 vs. lost = 48.9%). Fertility r esponses of cows of different breeds were not influenced by method of presynchronization (Figure 6 2) or length of proestrus. Although P/AI did not differ among Jerseys, Holsteins, and crossbreds, pregnancy loss was less ( P = 0.02) for crossbreds than the other two breeds. Reproduction in the Entire Breeding Season in Farm A The proportion of nonpregnant cows on d 30 that had been detected in estrus and reinseminated was not influenced by method of presynchronization (Table 6 3). Breed of cows and estrous c yclic status influenced ( P < 0.001) the proportion of cows observed in estrus and reinseminated. Reinsemination did not differ between Holsteins and Jerseys, but crossbred cows had greater ( P = 0.05) detection of estrus and reinsemination than Holsteins, a nd tended ( P = 0.07) to be greater than Jerseys (crossbred = 68.2 vs. Jersey = 45.0 vs. Holstein = 35.7%). Similarly, estrous cyclic cows had greater ( P < 0.001) detection of estrus and reinsemination than anovular cows (68.6 vs. 34.5). The rate of pregna ncy throughout the 100 d breeding seaso n was not affected by treatment (Table 6 4). In fact, the median and mean intervals to pregnancy were similar

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187 between presynchronization treatments and between lengths of proestrus. Factors that influenced pregnancy r ate were breed of cow, BCS at AI, BCS change, and estrous cyclicity. Although pregnancy rate did not differ between Jerseys and Holsteins, the hazard of pregnancy was 51% greater ( P = 0.05) for crossbred cows than for Holstein cows. Cows with BCS at AI > 3 .00 had increased ( P < 0.01) hazard of pregnancy than had greater ( P < 0.01) hazard of pregnancy than cows that lost or maintained body condition. Finally, estrous cycl ic cows had 79% greater hazard of pregnancy than anovular cows, which reduced the median and mean d to pregnancy in 35 and 12 d, respectively. Discussion Presynchronization of the estrous cycle improves fertility of high producing dairy cows subjected to t imed AI protocols (Moreira et al., 2001), and this benefit has also been shown in lower producing cows in grazing dairy farms (Ribeiro et al., 2011). Similarly, altering the length of proestrus in timed AI protocols by manipulating the interval between ind uction of luteolysis with PGF and induction of the luteinizing hormone surge with GnRH can also affect fertility of dairy cows, particularly when the interval is too short and limit the growth and steroidogenesis of the ovulatory follicle during proestru s (Peters and Pursley et al., 2003). In the current study, two methods of presynchronization of the estrous cycle were evaluated combined with two lengths of proestrus in cows subjected to the 5 d timed AI program. The rational for the DO program was that GnRH is very efficacious at inducing ovulation in anovular cows (Gmen et al., 2003), and prevalence of anovular cows is usually high in dairy herds before the first postpartum insemination (Santos et al., 2009).

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188 On the other hand, Presynch is commonly us ed to benefit fertility of estrous cyclic cows subjected to timed AI programs (Moreira et al., 2001), and it has been shown to result in similar fertility when compared with cows receiving presynchronization with combinations of a single GnRH and PGF (Ga lvo et al., 2007; Ribeiro et al., 2011). Despite the potential benefits of the DO in more precisely synchronizing ovulation and inducing estrous cyclicity in anovular cows, estradiol concentrations at AI, detection of estrus at AI, and P/AI on d 30 and 65 did not differ between the two presynchronization treatments. Nevertheless, cows in the DO had less pregnancy loss than cows synchronized with the Presynch. Large epidemiological studies have reported that the proportion of anovular cows at the end of vo luntary waiting period range from 18 to 43% in different grazing and confinement dairy farms (Rhodes et al., 2003; Santos et al., 2009). A novular cows have reduced fertility at first AI (Santos et al., 2009) and increased risk or pregnancy loss (Santos et al., 2004), all of which result in reduced rate of pregnancy throughout the breeding period (Ribeiro et al., 2011). Primiparous cows are more likely to remain anovular at the end of the voluntary waiting period When the DO resulted in greater P/AI in high producing dairy cows, all the benefit originated from cows in first lactation (Souza et al., 2008). In that study, estrous cyclic status was not evaluated before enrollment in the timed AI protocols. It is plausible to suggest that some of the benefit of the DO compared with the Presynch in primiparous cows observed by Souza et al. (2008) could have been caused by the greater risk of anovulation in that category of cows, making them nonresponsive to the Presynch. Surprisingly, compared with the Presynch, t he DO did not influence P/AI of grazing cows and the lack benefit was

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189 observed regardless of parity and estrous cyclicity. Despite having fewer pregnancy losses between 30 and 65 d of gestation, cows in the DO did not have greater probability of pregnancy on d 65 after insemination. Perhaps, the limited number of anovular cows in the study (248 or 14.1%) restricted the benefit of DO in inducing estrous cyclicity and increasing the proportion of cows in diestrus when the 5 d timed AI initiated. Extending th e proestrus from 58 to 72 h in the 5 d timed AI resulted in greater estradiol concentrations and expression of estrus at AI, and the latter is often associated with fertility in cows in timed AI programs (Santos et al., 2010a). In fact, pregnant cows had g reater concentration of estradiol at AI than nonpregnant cows in the present study. Lengthening the proestrus did not influence fertility on d 30 after AI; however, on d 65, the restricted proestrus of 58 h reduced P/AI of cows presynchronized with PGF only. For cows enrolled in the DO, however, lengthening the proestrus resulted in similar fertility. When cows receive presynchronization with GnRH, more of them are in diestrus when the timed AI is initiated (Ribeiro et al., 2011) and ovulatory respons es during the timed AI are usually high (Bello et al., 2006). The increased precision of synchronization with the DO, as suggested by some (Souza et al., 2008), might result in dominant follicles that are more homogenous in development and less susceptible to restrictions in length of proestrus. In high producing cows, altering the timing of the final GnRH of the 5 d timed AI protocol relative to insemination did not influence P/AI (Bisinotto et al., 2010b); however, in dairy heifers, administering GnRH 56 after induction of luteolysis reduced P/AI compared with a longer proestrus of 72 h (Lima et al., 2011).

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190 Upon further evaluation, it was observed that most of the reduction in P/AI for Presynch cows with 58 h of proestrus was observed in those that did no t display signs of estrus at AI. In those cows, P/AI were 44.8 vs. 50.7% for COS58 and COS72, respectively, whereas for cows in estrus, the P/AI were, respectively, 60.7 and 63.6% for COS58 and COS72. It is possible that for cows in the Presynch, reducing proestrus limited exposure to estradiol and compromised fertility. Similar to these observations, Lima et al. (2011) also demonstrated that for heifers in estrus, altering the timing of the final GnRH of the 5 d timed AI did not influence P/AI, but for tho se not displaying estrus at AI, a proestrus of 72 h was better than 56 h. It is important to mention that heifers have low ovulation to the first GnRH injection of timed AI protocols and, consequently, the emergence of the ovulatory follicle is not precise ly synchronized. Most anovular cows respond to GnRH by ovulating a follicle (Gmen et al., 2003), suggesting that incorporation of GnRH for presynchronization was expected to induce estrous cyclicity and benefit fertility. A critical factor affecting ferti lity of anovular cows seems to be the low concentration of progesterone during the development of the ovulatory follicle (Bisinotto et al., 2010a). Therefore, induction of ovulation and, consequently, formation of a CL before enrolment in the timed AI prog ram would benefit fertility of anovular cows by increasing the proportion of cows in diestrus when the first GnRH of the timed AI is administered (Ribeiro et al., 2011). When estrous cyclic cows developed the ovulatory follicle under low concentrations of progesterone, P/AI and pregnancy loss were similar to those of anovular cows (Bisinotto et al., 2010a). Surprisingly, DO did not influence fertility of anovular cows when compared with Presynch. In previous studies by our group with high producing cows in confinement

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191 (G alvo et al., 2007) or with low producing cows on pasture (Ribeiro et al., 2011), use of PGF /GnRH combination for presynchronization was not superior to Presynch, despite a greater proportion of cows in diestrus at the beginning of the time d AI protocol when presynchronization used GnRH (Ribeiro et al., 2011). Collectively, these data suggest that simply inducing ovulation and formation of a CL in anovular cows before enrollment in the timed AI program does not seem to resolve the underlying problem of low fertility. Pregnancies per AI in the current study were generally high, and the results from the first AI were not influenced by breed. Approximately 63% of the cows in the study were crossbreds, and these cows had generally superior ferti lity than Holsteins or Jerseys. Improving fertility to AI programs assures that more cows will become pregnant to superior sires that allow selection not only for production, but also reproduction and health traits. This might be particularly important in grazing herds utilizing crossbreeding as AI permits selection of a specific breed of sire to be used in the cows to perpetuate a certain degree of hybrid vigor. Following the first 30 d of AI in farm A, 71.6% of the crossbred cows was pregnant compared wit h only 59% of the Jerseys and Holsteins. These cows that become pregnant early in the breeding season and to proven sires, as oppose to natural service, are likely to be more profitable to producers in grazing farms (McDougall and Compton, 2006). In New Ze aland, becoming pregnant early in the breeding season assures a longer lactation that has marked effects on production and profitability of the cow (McDougall and Compton, 2006). A similar response has been observed by Ribeiro et al. (2011) in which crossb red Holstein/Jersey cows had superior reproductive performance than either one of the two breeds in grazing farms Therefore, it is plausible to suggest that crossbred Holstein/Jersey cows have superior

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192 reproduct ive performance than their pure bred counterp arts in when subjected to grazing. Perhaps they are a better match to an environment that has more limitations to nutrition, or simply because crossbreeding reduces inbreeding and adds hybrid vigor, both of which have been suggested to improve health and r eproduction in cattle (Harris and Kolver, 2001). Summary Method of presynchronization with either only PGF in the Presynch or GnRH/ PGF in the DO resulted in similar fertility in grazing dairy cows at first AI, and similar rate of pregnancy throughout the 100 d breeding season. Extending the proestrus from 58 to 72 h in the 5 d timed AI protocol resulted in greater estradiol concentrations and expression of estrus at AI independently of presynchronization treatments. Nevertheless, restricting the proest rus to 58 h reduced fertility of cows enrolled in the Presynch protocol, but not in the DO. Anovular cows had reduced concentrations of estradiol at AI, P/AI at first AI, detection of estrus and reinsemination by AI, and pregnancy to natural service, all o f which resulted in a marked decrease in the rate of pregnancy and extension of days open. Interestingly, incorporating GnRH for presynchronization did not benefit reproductive performance of anovular cows. Fertility of cows was better when they had BCS at AI > 3.00 and/or gained body condition after AI. Finally, crossbred cows generally had better reproductive performance than Holsteins and Jerseys.

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193 Table 6 1. Effects of presynchronization and length of proestrus on reproductive outcomes of lactating grazi ng dairy cows after first insemination Synchronization protocol 1 DO Presynch P 2 Item COS58 COS72 COS58 COS72 Pre LP Pre x LP Estradiol at AI, pg/mL 5.53 0.55 7.33 0.68 5.54 0.55 6.00 0.61 0.35 0.04 0.22 Estrus at AI 10.7 (27/252) 24.8 (1 56/630) 10.9 (28/258) 32.3 (198/614) 0.24 < 0.001 0.20 Pregnant d 30 57.9 (146/252) 56.4 (355/630) 54.3 (140/258) 61.1 (375/614) 0.88 0.12 0.13 d 65 53.2 (134/252) 52.2 (329/630) 46.5 b (120/258) 54.9 a (337/614) 0.50 0.04 0.10 Pregnancy l oss 8.22 (12/146) 7.3 (26/355) 14.3 (20/140) 10.1 (38/375) 0.03 0.24 0.53 a,b Superscripts within a row differ (P < 0.05). 1 All cows were subjected to the 5 d timed AI protocol. Cows in the DO received an injection of GnRH followed 7 d later by PGF 3 d later GnRH, and the 5 d timed AI started 7 d later. Cows in Presynch received two injections of PGF administered 14 d apart and the 5 d timed AI protocol started 10 d after the second PGF Cows assigned to COS58 received the final GnRH injection con current with timed AI at 58 h after induction of luteolysis, whereas those assigned to COS72 received both GnRH and timed AI at 72 h. 2 Pre = effect of presynchronization (DO vs. Presynch); LP = effect of length of proestrus (COS58 vs. COS72); Pre x LP = interaction between Pre and LP.

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194 Table 6 2. Effects of method of presynchronization and estrous cyclic status on reproductive responses of grazing dairy cows Estrous cyclicity 1 Anovular Cyclic P 3 Item DO 2 Presynch 2 DO Presynch EC P EC x P Estradio l at AI, pg/mL 4.91 0.67 4.27 0.62 8.24 0.54 7.72 0.52 < 0.001 0.35 0.74 Estrus at AI 20.0 (25/125) 26.0 (32/123) 20.9 (158/757) 25.9 (194/749) 0.50 0.24 0.85 Pregnant d 30 36.8 (46/125) 33.3 (41/123) 60.1 (455/757) 63.3 (474/749) < 0 .001 0.88 0.54 d 65 32.8 (41/125) 28.5 (35/123) 55.8 (422/757) 56.3 (422/749) < 0.001 0.50 0.73 Pregnancy loss 10.9 (5/46) 14.6 (6/41) 7.3 (33/455) 11.0 (52/474) 0.73 0.03 0.94 1 Anovular = lack of CL in two sequential ultrasound exams 10 d apart; C yclic = presence of a CL in at least one of the two ultrasound exams. 2 All cows were subjected to the 5 d timed AI protocol. Cows in the DO received an injection of GnRH followed 7 d later by PGF 3 d later GnRH, and the 5 d timed AI started 7 d later. the 5 d timed AI protocol started 10 d after the second PGF 3 EC = effect of estrous cyclicity; Pre = effect of method of presynchronization; EC x Pre = interaction between E C and P.

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195 Table 6 3. Effects of presynchronization on reproductive responses of the remaining breeding season of farm A Presynchronization treatments 1 Item DO Presynch P Reinseminated 2 68.4 (65/95) 57.8 (52/90) 0.28 Day of AI 3 (LSM SEM) 21.5 0. 8 21.1 0.8 0.47 Pregnant Reinsemination by AI 39.1 (25/64) 41.2 (21/51) 0.86 Natural service 76.8 (63/82) 65.4 (53/81) 0.09 End of 100 d breeding season 91.9 (260/283) 88.2 (247/280) 0.11 1 All cows were subjected to the 5 d timed AI protocol. Cows in the DO received an injection of GnRH followed 7 d later by PGF 3 d later GnRH, and the 5 d timed AI started 7 d later. Cows in Presynch received two injections of PGF administered 14 d apart and the 5 d timed AI protocol started 10 d after the second PGF 2 Proportion of nonpregnant cows reinseminated by AI after detection of estrus between study d 19 and 30. 3 Day of reinsemination for cows detected in estrus and rebred by AI.

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196 Table 6 4. ancy rate of grazing dairy cows in farm A Days to pregnancy Item Median (95% CI) Mean SEM AHR 1 (95% CI) P Presynchronization 2 Presynch 0 (0 0) 21.2 1.8 Referent ----DO 0 (0 0) 20.8 1.8 1.09 (0.91 1.30) 0.34 Length of proe strus 2 COS58 0 (0 0) 21.8 1.7 Referent ----COS72 0 (0 0) 20.8 2.0 1.00 (0.84 1.19) 0.98 Breed Holstein 22 (0 60) 31.0 6.0 Referent Jersey 0 (0 26) 25.0 4.2 1.25 (0.77 2.02) 0.36 Crossbred 0 (0 0) 2 0.2 1.4 1.51 (1.00 2.26) 0.05 BCS at AI 0 (0 21) 27.0 2.1 Referent > 3.00 0 (0 0) 16.2 1.6 1.27 (1.06 1.52) < 0.01 BCS change 3 Lost 0 (0 20) 24.0 2.6 Referent No change 0 (0 20) 24.8 2.4 1.03 (0. 82 1.29) 0.81 Gained 0 (0 0) 15.4 1.8 1.35 (1.08 1.68) < 0.01 Estrous cyclicity 4 Anovular 35 (22 45) 34.3 4.2 Referent Cyclic 0 (0 0) 22.1 1.4 1.79 (1.25 2.55) < 0.0 1 1 AHR = adjusted hazard ratio. 2 All cows were su bjected to the 5 d timed AI protocol. Cows in the DO received an injection of GnRH followed 7 d later by PGF 3 d later GnRH, and the 5 d timed AI started 7 d later. Cows in Presynch received two injections of PGF administered 14 d apart and the 5 d timed AI protocol started 10 d after the second PGF Cows assigned to COS58 received the final GnRH injectio n concurrent with timed AI at 58 h after induction of luteolysis, whereas those assigned to COS72 received both GnRH and timed AI at 72 h. 3 Change in BCS from study d 0 to 30, which corresponded to the d of AI and pregnancy diagnosis. 4 Anovular = lack of CL in two sequential ultrasound exams 10 d apart; Cyclic = presence of a CL in at least one of the two ultrasound exams.

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197 Figure 6 1. Diagram of activities in the study. Double Ovsynch = presynchronization with the Ovsynch protocol; Presynch = presyn chronization with 2 injections of prostaglandin F administered 14 d apart. COS58 = 58 h of proestrus; COS72 = 72 h of proestrus. GnRH = injection of 100 g of gonadorelin; PGF = injection of 25 mg of prostaglandin F

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198 Figure 6 2. Fertility respons es of grazing dairy cows at first insemination according breeds and presynchronization treatments in three seasonal grazing farms. All cows were subjected to the 5 d timed AI protocol. Cows in the DO received an injection of GnRH followed 7 d later by PGF 2 3 d later GnRH, and the 5 d timed AI started 7 d later. Cows in Presynch received two injections of PGF administered 14 d apart and the 5 d timed AI protocol started 10 d after the second PGF Jersey, n = 424; Holstein, n = 226; crossbred, n = 1,10 4. a,b Different superscripts indicate different among breeds ( P < 0.05).

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199 CHAPTER 7 GENERAL DISCUSSION, CONCLUSIONS AND IMPL ICATIONS Reproduction efficiency is critical for the sustainability of seasonal grazing dairy farms To maintain the ideal 365 d cal ving interval, cows need to conceive on average at 80 d postpartum. High submission rates and adequate pregnancy per artificial insemination (P/AI) are then required to maintain a concentrated calving pattern on a yearly basis (Morton, 2010). When the bree ding program relies on i nsemination after detection of estrus, reproductive performance might be compromise d because of reduced submission rates in herds with a high proportion of anovular cows after the end of the voluntary waiting period or because of po or detection of estrus. Timed artificial insemination ( AI ) maximizes submission rates and has demonstrated to economically benefit dairy producers when used in anovular and estrous cyclic cows at the beginning of breeding season in grazing farms in New Zea land (McDougall, 2010). In this thesis, we proposed a reproductive program consisting of timed AI for all cows in the first day of the breeding season, detection of estrus and reinsemination in cows that return to estrus and a final breeding clean up of na tural service completing the 100 d breeding season. This program resulted in 100% submission rate and 50% P/AI on the first day of breeding, 65 to 70% of the cows pregnant by d 30 and 80 to 90% by the end of 100 d breeding season. These are considered exce llent reproductive results and comparable to results used as goals for grazing farms in Australian and New Zealand seasonal herds (Burke and Verkerk, 2010). Surprisingly, such results were obtained in farms with 30 to 50% higher milk production per cow tha n that typically observed in New Zealand. Furthermore, these results were obtained with North American genetics, often considered subfertile compared with New Zealand genetics (Harris and Kolver, 2001).

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200 Cows that become pregnant early in the breeding seas on also calve early in the following calving season, assuring longer lactation and more time for resumption of positive energy balance and estrous cyclicity until initiation of the following breeding season, thus improving subsequent reproductive performan ce (McDougall and Compton, 2006; Chapter s 4, 5, and 6). Moreover, the high proportion of cows pregnant by d 30 will produce calves sired by AI that are of higher genetic and economic value than those sired by natural service (McDougall and Compton, 2006). The se calves represent the pool of animals from which replacement heifers should be selected. With 70% of cows conceiving to AI, it is expected that 35% of calves born will be female offsprings of AI sires, which is typically more than the average herd rep lacement rate of approximately 20% per year for grazing herds. The increase in AI sired replacements allows more intensive selection pressure for the he rd, herd expansion, and sale of higher value heifers. Heifers born early in the breeding season are more likely to reach puberty and become pregnant within the time frame to enter in a seasonal reproductive program. Similar to cows, replacement heifers tha t become pregnant late in the breeding season will calve late in the calving season, resulting in the same problems aforementioned, which are likely to be worsened in primiparous which typically have an extended anovular period compared with multiparous co ws (Santos et al., 2009). Although timed AI allows maximal submission rates, several factors were identified as affecting P/AI and pregnancy loss, which consequently compromise the rate of pregnancy and the overall reproductive efficiency of the herd. The se factors included health problems ( Chapter 3), low body condition score (BCS; Chapter s 3, 4, 5, and 6), loss of BCS ( Chapters 3, 4, 5, 6), genetics of the cow ( Chapter s 4, 5, and 6),

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201 inadequate timed AI program ( Chapter 3), and anovulation ( Chapter s 3, 4 5, and 6). All those factors are typically dependent on managerial decisions and should be addressed to minimize their negative impact on fertility of dairy cows. Cows experiencing extensive loss of BCS, diseases or metabolic problems in early lactation are more likely to have extended periods of anovulation and impaired reproduction (Rhodes et al., 2003; Chagas et al., 2007; Santos et al., 2009; Santos et al., 2010b). These events are all associated with negative nutrient balance, often expre ssed as neg ative energy balance Energy balance is determined primarily by energy intake (Santos et al., 2010b) and, therefore, constitutes a great challenge when feed availability and nutrient supply are limited especially when the genetic makeup of the cow favor s increased partition of nutrients for production at the cost of body reserves (Bauman and Currie, 1980). Moreover, incidence of health problems are normally associated with reduced appetite and thus further compromise energy balance, forming a vicious cycle that impairs lactation and reproductive performance (Drackley, 1999; Santos et al., 2010). On the other hand, it is generally suggested that health programs are not common in grazing farms. Nonetheless, in Chapter 3, it was clearly demonstrated that periparturient clinical and subclinical diseases are highly prevalent in grazing dairy cows in the two herds studied and, as observed in high producing cows in confinement, the se health problems delay estrous cyclicity, reduce P/AI and increase the risk of pregnancy loss. Additionally, in all studies of this thesis, cows with low BCS at AI or that lost BCS had reduced P/AI and, in one study ( Chapter 6), increased risk of pregnancy loss. Thus, management of grazing cows to optimize

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202 fertility should focus on reducing periparturient diseases, BCS loss and lipid mobilization, as well as improving Ca homeostasis. Crossbreed cows demonstrated better reproductive performance than Holstei n cows ( Chapter s 3, 4, 5, and 6) including faster resum ption of estrous cyclicity postpartum greater P/AI and faster pregnancy rates Although differences in reproductive efficiency were less evident crossbred s in general also performed better than Jers ey cows ( Chapter 6). Moreover, milk production of crossbred cows was intermediate compared with the two purebred genetic groups and close r to the higher produc ing Holstein s than to the lower produc ing Jersey s Collectively, t hese reproductive and producti ve responses demonstrate an advantage of crossbred cows over Jersey s and Holsteins. The better reproductive performance of crossbreds compared with Holsteins likely compensate s for the lower milk production when considered the long term sustainability of a seasonal grazing dairy farm. It is important to mention that no major differences in the incidence of diseases were detected among breed groups ( Chapter 3) and, therefore, improved reproductive efficiency by crossbred cows should be related to factors oth er than better postpartum health. Crossbred cows may be a better match to the environment and management of grazing dairy farms that has more limitations to nutrition Furthermore, they likely have differential nutrient partitioning, or reduced ovarian ste roid catabolism or simply because crossbreeding reduces inbreeding and adds hybrid vigor, which are all factors that have been suggested to improve reproducti ve efficiency of dairy cattle (Harris and Kolver, 2001 ; Wiltbank et al., 2006 ). P erpetuat ion of c ertain degree of hybrid vigor can be obtained and maximized by the establishment of a rotational breeding system using two or three

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203 distinct breeds and s election of sires within each breed should focus on production, reproduction and health traits (Hansen et al., 2005) The more suitable timed AI program should be used to maximize pregnancy on the first day of breeding season. In Chapter 4, results clearly demonstrate that presynchronization increases the proportion of cows with a corpus luteum (CL) at fir st gonadotropin releasing hormone ( GnRH ) of timed AI protocol, ovulation to the first GnRH of the protocol, and presence and number of CL at the prostaglandin ( PG ) F injection of the timed AI protocol All of these responses have been identified as criti cal to optimize fertility in synchronization programs (Vasconcelos et al., 1999; Chebel et al., 2006; Bisinotto et al., 2010a). In fact, presynchronization has been shown to improve fertility of high producing confined dairy cows (Moreira et al., 2001; El Zarkouny et al., 2004; Navanukraw et al., 2004). Nonetheless, it was clear that, except for Holstein s, Jersey and crossbred cows seemed to have adequate fertility with protocols that supplement progesterone without presynchronization. In fact, this type of protocol is the most extensively used in New Zealand, and has demonstrated economic benefits over the conventional Ovsynch protocol without progesterone supplementation (McDougall, 2010). The amounts of progesterone supplemented by a single insert are lik ely to be of greater benefit in small frame, low body weight cows of low production potential. These cows are expected to have greater concentrations of progesterone for the given amount released by the insert, particularly if steroid metabolism is reduced compared with a higher producing Holstein cows. In some cases, use of a single progesterone insert benefited fertility only in cows with a CL, suggesting that the progesterone released was

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204 not sufficient to benefit cows that most need progesterone, those without a CL (Bisinotto et al., 2010b). Reducing the interval from follicle emergence to ovulation improves early embryo quality (Cerri et al., 2009a) and P/AI of lactating dairy cows following insemination in synchronized ovulation (Santos et al., 2010a) or spontaneous estrus (Bleach et al., 2004). The 5 d timed AI program has been used to reduce the period of follicle dominance and improve P/AI in dairy cows and heifers (Rabaglino et al., 2010; Santos et al., 2010a). It was used as the base program in al l studies of this thesis, in which different variations or modifications were tested aiming to improve fertility and also facilitate implementation on dairy farms. The limiting factor to reduce the period of follicle dominance in timed AI programs is regre ssion of the newly formed CL from ovulation to the first GnRH injection of the protocol. The newly formed CL is refractory to luteolysis in the first 5 d of development because of distinct molecular responses to PGF compared with the mid cycle CL (Miyamo to et al., 2009). Thus, in order to assure adequate luteolysis, cows have to be handled an additional time to receive a second luteolytic dose of PGF 7 to 24 h after the first dose (Kasimanickam et al., 2009; Santos et al., 2010a). In Chapter 4 we hypot hesized that increasing the dose of PGF as a single injection would result in acceptable luteolysis and fertility. However, the results clearly indicate that twice the standard luteolytic dose of PGF did not change the refractoriness of the early CL to luteolysis. Although the second dose of PGF did not benefit fertility of non presynchronized cows, it was critical to improve fertility of presynchronized cows, which had increased ovulation to the first GnRH injection and,

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205 consequently, a greater preva lence of newly formed CL on the day of the PGF treatment. Thus, rate of ovulation at the beginning of the protocol determines the effectiveness of single administration of PGF on d 5 or the need for additional PGF injection. This idea explains the la ck of benefit of second PGF observed in some studies with dairy heifers (Rabaglino et al., 2010) and beef cows (Cruppe et al., 2010), in which ovulation is also expected to be low as in non presynchronized dairy cows ( Chapter 4). Moreover, fertility to t he different types of presynchr onizations (Presynch, G6G, and d ouble Ovsynch) were similar when cows received the 5 d timed AI protocol The 5 d timed AI protocol results in smaller ovulatory follicle diameter, reduced concentrations of estradiol during pr oestrus, and a smaller proportion of cows in estrus on the day of AI than 7 d programs (Santos et al., 2010a), which are all factors associated with fertility in timed AI programs in dairy (Vasconcellos et al., 2001; Lopes et al., 2007) and beef cows (Perr y et al., 2005). In addition to lower concentrations of estradiol at AI, ovulation of small follicles results in formation of small CL (Vasconcelos et al., 2001) Small CL result in a slower rate of increase in progesterone concentrations after AI (Perry 2 005), which is associated with altering the uterine receptiveness for a successful maintenance of pregnancy. Progesterone primes the uterus to influence conceptus development (Forde et al., 2009, 2010) and embryo survival (Stronge et al., 2005; Lopes et al ., 2007). In Chapter 6, it was demonstrated that extending the proestrus from 58 to 72 h in the 5 d timed AI protocol increased estradiol concentrations and expression of estrus at AI. Nevertheless, restricting the proestrus to 58 h reduced fertility only in cows presynchronized with the Presy nch protocol, but not with the d ouble Ovsynch. Moreover, this difference was observed on gestation d 65, but not on d 30,

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206 thus only after accounting for pregnancy losses. Perry et al. (2005) suggested that induction of ovulation of follicles that are physiologically immature has a negative impact on P/AI primarily because of embryonic loss. In fact, most of the reduction in P/AI for Presynch cows with 58 h of proestrus was observed in those that did not display signs of estrus at AI. The us e of GnRH in the d ouble Ovsynch protocol might result in better synchrony of follicle wave development and a less variable follicle diameter at 58 h of proestrus than Presynch which allows greater flexibility with time to induce ovula tion and inseminate dairy cow in 5 d timed AI protocols. Anovulation is a major problem for optimum reproductive success in dairy farms. Although the use of timed AI programs secures that anovular cows will be inseminated at the desired interval postpartu m these cows have reduced P/AI and increased risk of pregnancy loss, which compromises pregnancy rate and increases culling compared with their estrous cyclic counterparts (Rhodes et al., 2003; Santos et al., 2004; Santos et al., 2009). Poor synchronizati on of ovulation does not seem to be the reason for low fertility in anovular cows (Gmen et al. 2003). On the other hand, the low concentrations of progesterone during the development of the ovulatory follicle seem to be a major factor impairing fertility (Bisinotto et al., 2010a). The low concentration of progesterone during growth of the ovulatory follicle in anovular cows overexposes the follicle and oocyte to luteinizing hormone, which compromises oocyte maturation (Revah and Butler, 1996). Additional ly, low progesterone alters the composition of the follicular fluid (Cerri et al., 2011) and uterine physiology in the subsequent estrous cycle (Shaham Albalancy et al., 2001; Cerri et al., 2011), which might affect fertility. Embryo quality on d 7 after A I in cows ovulating

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207 follicles developed under low concentrations of progesterone is reduced, but reversed by progesterone supplementation (Rivera et al., 2011). We used presynchronization programs that included GnRH injections (G6G: Chapter 5; d ouble Ovsyn ch: Chapter 6) as method s to induce ovulation in anovular cows before enrolment in the timed AI program. The aim was to increase the proportion of cows in diestrus at the initiation of the timed AI program to assure the development of the ovulatory follicl e under high systemic concentrations of progesterone. Surprisingly, these protocols did not influence fertility of anovular cows when compared with Presynch, suggesting that simply inducing ovulation and formation of a CL in anovular cows before enrollment in the timed AI program does not seem to resolve the underlying problem of low fertility. Thus, new strategies to improve fertility of anovular cows are needed in grazing farms

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232 BIOGRAPHICAL SKETCH Eduardo de Souza Ribeiro was born in So Joaquim, Santa Catarina, Brazil. He grew up in a family farm that his parents own, where they have a mix of dairy and beef cattle. In March 2004, he began his studies in the School of Veterinary Medicine at the Center of Ag roveterinarian Sciences at Santa Catarina State University (CAV/UDESC). He was a student assistant in the Animal Reproduction Laboratory at the CAV/UDESC from June 2005 to December 2008 under supervision of Dr. Marcelo Bertolini and Dr. Alceu Mezzalira and sponsored by the National Council of Technological and Scientific Development (CNPq/Brazil). He was involved in research with in vivo and in vitro production of bovine embryos and their cryopreservation, including techniques such as cloning by somatic cel l nuclear transfer, in vitro fertilization and vitrification of bovine oocytes and embryos. He also participated in extension activities as student responsible for the program of control of reproductive efficiency of the dairy cattle herd at CAV/UDESC and partner dairies f rom October 2005 to August 2008, involv ing activities such as embryo transfer, ultrasonography, obstetrics, postpartum monitoring, and reproductive management in general. He graduated in Veterinary Medicine in December 2008. He spent his l ast semester of his studies in Veterinary Medicine in a supervised externship in the Department of Animal Sciences at the University of Florida, under the supervision of Dr. Jos E.P. Santos. After this period, he returned to the University of Florida to w ork under Dr. Santos on his Master of Science degree. He became a Research Assistant at the Animal Nutrition and Reproduction Laboratory in the spring of 2009, began his Master degree in Anim al Sciences in the fall of 2009 and graduated in the summer of 20 11.