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Foliar and soil applied silicon effects on Asian soybean rust (Phakopsora pachyrhizi) development in soybean under green...

Permanent Link: http://ufdc.ufl.edu/UFE0041351/00001

Material Information

Title: Foliar and soil applied silicon effects on Asian soybean rust (Phakopsora pachyrhizi) development in soybean under greenhouse and field conditions
Physical Description: 1 online resource (135 p.)
Language: english
Creator: Lemes, Ernane
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: asr, audpc, potassium, silicate, wollastonite
Plant Pathology -- Dissertations, Academic -- UF
Genre: Plant Pathology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Foliar and soil applied silicon effects on Asian soybean rust (Phakopsora pachyrhizi) development in soybean under greenhouse and field conditions By Ernane Miranda Lemes December 2009 Chair: Cheryl L. Mackowiak Cochair: Lawrence E. Datnoff Major: Plant Pathology Asian soybean rust (ASR), caused by Phakopsora pachyrhizi H. Sydow & Sydow is one of the most destructive fungal diseases of soybean production world-wide. The main effect of ASR is reduction of photosynthetic area, ensuing premature defoliation, early plant maturation and low seed quality. Great yield reductions are common to fields of soybean that were under severe ASR pressure and when no fungicide is applied for control. Fertilization with silicon (Si) has been studied as an alternative against ASR since this element has suppressed plant diseases in other host-pathogen systems. Greenhouse and field studies were conducted to evaluate the effects of foliar and soil applied Si sources on soybean development and ASR control. Greenhouse experiments including wollastonite (CaSiO3) rates ranging from 0 to 8 metric tons (MT) ha-1, two soil orders (Entisol, Ultisol) and two soybean cultivars (DP 5634RR, Hinson Long Juvenile) showed that soybean accumulated Si and the level of accumulation increased as the soil Si rate increased. However, under no noticeable abiotic or biotic stresses in the greenhouse, different Si rates did not consistently affect soybean stem diameter, trifoliate area, dry root mass or dry leaf mass. In general, low correlations existed between Si rates and plant development. The average plant development evaluations were greater for Ultisol treatments and for treatments including wollastonite sources with small granular size. In another set of greenhouse experiment, two soybeans cultivar receive applications of wollastonite (0, 960, 1920 MT Si ha-1) or potassium silicate (K2SiO3not) (0, 500, 1000, 2000 mg Si kg-1) and then were inoculated with P. pachyrhizi. The results showed that soil Si treatments had more soil Si and an average delay of three days in disease onset for both soils tested. The effects of Si treatments on the area under disease progress curve (AUDPC) of ASR showed that the different Si treatments (soil or foliar) were not significantly different from each other, or among Si rates, but were significantly lower than non-Si treatments. For the field experiments, wollastonite was applied to the soil (0, 480, 960, 1920 MT Si ha-1) and K2SiO3 was applied foliarly (0, 500, 1000, 2000 mg Si kg-1). Two soybean cultivars were planted on an Ultisol. An average delay of three days was observed for soil Si treatments. Up to 43% and 36% reduction in AUDPC were observed for soil and foliar Si treatments, respectively. No significant and consistent results were observed between Si and non-Si treatments for seed quality, 100 seeds weight or crop yield. These results suggest that soil Si amendment effects might be restricted to the early stages of P. pachyrhizi infection process, as exemplified by delaying the onset of ASR development. Although Si effects on ASR were limited, the use of Si amendments, such as wollastonite and potassium silicate may still be useful in sustainable soybean production. Combinations of Si amendments with other organic approved products might have great potential to maximize control of ASR. The use of Si amendments to manage plant disease in commercial soybean fields may reduce production costs by reducing the number of fungicide applications. The time delay observed by soil Si amendment use may lead to ASR control practices that can benefit both, organic and conventional soybean production systems.
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 Ernane Lemes.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Mackowiak, Cheryl L.
Local: Co-adviser: Datnoff, Lawrence E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0041351:00001

Permanent Link: http://ufdc.ufl.edu/UFE0041351/00001

Material Information

Title: Foliar and soil applied silicon effects on Asian soybean rust (Phakopsora pachyrhizi) development in soybean under greenhouse and field conditions
Physical Description: 1 online resource (135 p.)
Language: english
Creator: Lemes, Ernane
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: asr, audpc, potassium, silicate, wollastonite
Plant Pathology -- Dissertations, Academic -- UF
Genre: Plant Pathology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Foliar and soil applied silicon effects on Asian soybean rust (Phakopsora pachyrhizi) development in soybean under greenhouse and field conditions By Ernane Miranda Lemes December 2009 Chair: Cheryl L. Mackowiak Cochair: Lawrence E. Datnoff Major: Plant Pathology Asian soybean rust (ASR), caused by Phakopsora pachyrhizi H. Sydow & Sydow is one of the most destructive fungal diseases of soybean production world-wide. The main effect of ASR is reduction of photosynthetic area, ensuing premature defoliation, early plant maturation and low seed quality. Great yield reductions are common to fields of soybean that were under severe ASR pressure and when no fungicide is applied for control. Fertilization with silicon (Si) has been studied as an alternative against ASR since this element has suppressed plant diseases in other host-pathogen systems. Greenhouse and field studies were conducted to evaluate the effects of foliar and soil applied Si sources on soybean development and ASR control. Greenhouse experiments including wollastonite (CaSiO3) rates ranging from 0 to 8 metric tons (MT) ha-1, two soil orders (Entisol, Ultisol) and two soybean cultivars (DP 5634RR, Hinson Long Juvenile) showed that soybean accumulated Si and the level of accumulation increased as the soil Si rate increased. However, under no noticeable abiotic or biotic stresses in the greenhouse, different Si rates did not consistently affect soybean stem diameter, trifoliate area, dry root mass or dry leaf mass. In general, low correlations existed between Si rates and plant development. The average plant development evaluations were greater for Ultisol treatments and for treatments including wollastonite sources with small granular size. In another set of greenhouse experiment, two soybeans cultivar receive applications of wollastonite (0, 960, 1920 MT Si ha-1) or potassium silicate (K2SiO3not) (0, 500, 1000, 2000 mg Si kg-1) and then were inoculated with P. pachyrhizi. The results showed that soil Si treatments had more soil Si and an average delay of three days in disease onset for both soils tested. The effects of Si treatments on the area under disease progress curve (AUDPC) of ASR showed that the different Si treatments (soil or foliar) were not significantly different from each other, or among Si rates, but were significantly lower than non-Si treatments. For the field experiments, wollastonite was applied to the soil (0, 480, 960, 1920 MT Si ha-1) and K2SiO3 was applied foliarly (0, 500, 1000, 2000 mg Si kg-1). Two soybean cultivars were planted on an Ultisol. An average delay of three days was observed for soil Si treatments. Up to 43% and 36% reduction in AUDPC were observed for soil and foliar Si treatments, respectively. No significant and consistent results were observed between Si and non-Si treatments for seed quality, 100 seeds weight or crop yield. These results suggest that soil Si amendment effects might be restricted to the early stages of P. pachyrhizi infection process, as exemplified by delaying the onset of ASR development. Although Si effects on ASR were limited, the use of Si amendments, such as wollastonite and potassium silicate may still be useful in sustainable soybean production. Combinations of Si amendments with other organic approved products might have great potential to maximize control of ASR. The use of Si amendments to manage plant disease in commercial soybean fields may reduce production costs by reducing the number of fungicide applications. The time delay observed by soil Si amendment use may lead to ASR control practices that can benefit both, organic and conventional soybean production systems.
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 Ernane Lemes.
Thesis: Thesis (M.S.)--University of Florida, 2009.
Local: Adviser: Mackowiak, Cheryl L.
Local: Co-adviser: Datnoff, Lawrence E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0041351:00001


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1 FOLIAR AND SOIL APPLIED SILICON EFFECTS ON ASIAN SOYBEAN RUST ( Phakopsora pachyrhizi ) DEVELOPMENT IN SOYBEAN UNDER GREENHOUSE AND FIELD CONDITIONS By ERNANE MIRANDA LEMES A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER IN SCIENCE UNIVERSITY OF FLORIDA 2009

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2 2009 Ernane Miranda Lemes

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3 ACKNOWLEDGMENTS I would like thank to Cheryl Mackow iak, my advisor, and Dr. Dr. Lawrence Datnoff, my co-advisor, for their support, guidance, help and most of all for their belief in me throughout my Masters degree program. I am thankful to Drs. James Marois and Ann Blount, members of my advisory committee, for their useful counsel, critique and instruction. I am also very grateful to Dr. Dario Narvaes, Heather Young, Hua Kang and Shelby Carlin for their help with th e greenhouse and field experiment s and lab analyses. I am also thankful to Brenda Rutherford for her friendship and help with countless lab and greenhouse experiment issues, and to Eldon Philman and He rman Brown for their assistance with my greenhouses experiments. I would like to extend my admiration to th e students and faculty of North Florida Research and Education Center UF-IFAS in Quincy, FL and to the Plant Pathology Department at the University of Florida in Gain esville, FL for their camaraderie, inspiration and support, which were very important to help me improve my scientific sk ills and maturity. In recognition of all their help and support, I w ould like to mention Dr. Jeffrey Jones and Gail Harris from the Plant Pathology Department and Davis Scott from the Un iversity of Florida International Center. I also want to express my gr atitude to Drs. Gaspar H. Korndrfer and Lsias Coelho for their assistance and belief in me and he lp during the course of my Masters education. For those not mentioned, who had contributed to my success; I offer my sincere gratitude. I want to thank Dr. W. Klassen (Center of Tropical Agriculture), USDA-CSREES and Iowa State University (Organic Fungicide Proj ect) for their financia l and operational support without their assistance this resear ch would not have been possible. Finally, I thank my parents, Arlindo Lemes Coelho and Nilza Maria Miranda Coelho, for their love, encouragement and support.

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4 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 3LIST OF TABLES ...........................................................................................................................6LIST OF FIGURES .........................................................................................................................9ABSTRACT ...................................................................................................................... .............11 CHAP TER 1 LITERATURE REVIEW .......................................................................................................13Soybean ....................................................................................................................... ............13Phakopsora spp. Taxonomy ................................................................................................ 14Phakopsora spp. Morphology .............................................................................................14Asian soybean rust Disease and Symptomatology .............................................................. 16Asian soybean rust Disease control .....................................................................................18Silicon Geochemistry ........................................................................................................ ...20Plant Available Silicon Sources .............................................................................................. 21Silicon Uptake in Plants ...................................................................................................... ....22Silicon Benefits .............................................................................................................. .........24Siliconmediated Disease Resistance ..................................................................................... 25Hypothesis ..............................................................................................................................27Objectives .................................................................................................................... ...........272 SOYBEAN RESPONSE TO SILICON TREA TM ENTS USING TWO SOIL TYPES UNDER GREENHOUSE CONDITIONS ............................................................................. 28Introduction .................................................................................................................. ...........28Materials and Methods ...........................................................................................................29Treatments .................................................................................................................... ...29Measurements and Sampling ...........................................................................................31Statistical Analyses .......................................................................................................... 32Results and Discussion ........................................................................................................ ...32Plant Biometric Measurements ........................................................................................ 32Silicon Composition ........................................................................................................ 33Other Soil Characteristics ................................................................................................ 35Soil Drench ......................................................................................................................36Conclusions .....................................................................................................................373 EFFECTS OF SOIL AND FOLIAR A PPLIE D SILICON ON ASIAN SOYBEAN RUST DEVELOPMENT UNDER GREENHOUSE CONDITIONS ....................................46

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5 Introduction .................................................................................................................. ...........46Materials and Methods ...........................................................................................................48Treatments .................................................................................................................... ...48Inoculum Production .......................................................................................................50Measurements and Sampling ...........................................................................................51Statistical Analyses .......................................................................................................... 52Results and Discussion ........................................................................................................ ...52Leaf Mass ........................................................................................................................52Soil pH, Ca and Mg .........................................................................................................53Silicon composition ......................................................................................................... 53ASR disease .....................................................................................................................54Conclusions .....................................................................................................................574 EFFECTS OF SOIL AND FOLIAR A PPLIE D SILICON ON ASIAN SOYBEAN RUST DEVELOPMENT UNDER FIELD CONDITIONS ...................................................66Introduction .................................................................................................................. ...........66Materials and Methods ...........................................................................................................68Treatments .................................................................................................................... ...68Inoculum Production .......................................................................................................70Measurements and Sampling ...........................................................................................71Statistical Analyses .......................................................................................................... 72Results and Discussion ........................................................................................................ ...72Soil and Tissue Composition ........................................................................................... 72Soybean Dry Biomass Measurements ............................................................................. 73ASR disease progression .................................................................................................75Soybean yield ..................................................................................................................77Conclusions .....................................................................................................................78APPENDIX A SUMMARY TABLE OF THE STATISTICA L ANALYS IS OF SILICON EFFECTS ON PLANT BIOMETRIC MEASUREMENTS AND SOIL ANALYSIS (CHAPTER 2) ... 85B SOIL ANALYSIS OF SILICON DRENCH TREATMENT ................................................. 96C SUMMARY TABLE OF THE STATISTI CAL ANALYSIS OF GH STUDIES ................. 97D RAINFALL AND AIR TEMPERATURE of FIELD EXPERIMENTS .............................. 113E SOYBEAN SEED QUALITY VISUAL SCALE ................................................................ 114F SUMMARY TABLE OF THE STATISTI CAL ANALYS IS FOR BIOMASS AMONG TREATMENTS FOR FIELD EXPERIMENTS IN 2007 AND 2008 ................................. 115REFERENCES .................................................................................................................... ........120BIOGRAPHICAL SKETCH .......................................................................................................135

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6 LIST OF TABLES Table page 3-1 Substrate pH values and extractable Ca a nd Mg in treatm ents of the first experiment at 69 DAP. ..........................................................................................................................643-2 Soil pH extractable Ca and Mg in treatm ents of the second experiment at 34 DAP. ........643-3 Integrated area under disease progress curve (AUDPC) for treatments of the first experiment during 20 days of disease evaluation. .............................................................653-4 Area under disease progress curve (AUD PC) values and rate parameter from Gompertz model for treatments of the second experiment. ...............................................654-1 Final soil pH and Si concentration at 80 and 84 DAP for year 1 and year 2, respectively. ................................................................................................................. ......824-2 Final soil Ca and Mg at 80 and 84 DAP for year 1 and year 2, respectively. ....................824-3 Logistic and Gompertz model parameters of Asian soybean rust for the 0, 1.92 MT of Si ha-1, 0 and 2000 mg Si kg-1 for the field experiments. ..............................................834-4 Area under disease progress curve ( AUDPC) values and rate parameter ( r ) from Gompertz model for both experiments. .............................................................................844-5 Seed quality, crop yield, and weight of 100 seeds for year 1 and year 2. ..........................84A-1 Stem diameter, first experiment. ........................................................................................85A-2 Leaf area, first experiment. .............................................................................................. ..86A-3 Dry root mass, first experiment. ........................................................................................87A-4 Dry leaf mass, first experiment. .........................................................................................8 8A-5 Dry root mass, second experiment. ....................................................................................89A-6 Dry leaf mass, second experiment. ....................................................................................90A-7 Leaf silicon concentration, second experiment. .................................................................91A-8 Soil water pH, second experiment. ....................................................................................92A-9 Soil Ca concentration, second experiment. ........................................................................93A-10 Soil Mg concentration, second experiment. .......................................................................94A-11 Soil silicon concentrat ion, second experiment. ..................................................................95

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7 B-1 Soil pH, extractable Ca and Mg, soil Si c oncentrations and leaf Si concentration for two soil orders with two wolla stonite sources at six rates and a drench treatm ent. ..........96C-1 AUDPC, first experiment...................................................................................................97C-2 r parameter, first experiment. .............................................................................................98C-3 MSE (low value) and R-square (high valu e) check for disease progression model, in experiment 1 (Chapter 3). ..................................................................................................99C-4 r parameter determinatio n, first experiment. ................................................................... 100C-5 Leaf mass, first experiment. .............................................................................................1 01C-6 Leaf mass, second experiment. ........................................................................................102C-7 Soil Ca concentration, first experiment. ..........................................................................103C-8 Soil Ca concentration, second experiment. ......................................................................104C-9 Soil Mg concentration, first experiment. .........................................................................105C-10 Soil Mg concentration, second experiment. .....................................................................106C-11 Soil water pH concentration, first experiment. ............................................................ 10707C-12 Soil water pH concentration, second experiment. ....................................................... 10808C-13 Soil Si concentration, first experiment......................................................................... 10909C-14 Soil Si concentration, second experiment. ................................................................... 11010C-15 Leaf Si concentration, first experiment. ........................................................................... 111C-16 Leaf Si concentration, second experiment. ...................................................................... 112F-1 Dry leaf mass, 2007. ......................................................................................................1155F-2 Dry leaf mass, 2008. ......................................................................................................1166F-3 Dry pod mass, 2007. .................................................................................................... 11616F-4 Dry pod mass, 2008. .................................................................................................... 11717F-5 Dry stem mass, 2007. ...................................................................................................11717F-6 Dry stem mass, 2008. ...................................................................................................11818

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8 F-7 Dry root mass, 2007. .................................................................................................... 11818F-8 Dry root mass, 2008. ...................................................................................................... ..119

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9 LIST OF FIGURES Figure page 2-1 Effect of silicon sources and rates on pl ant b iometric characteristics at 35 DAP in Entisol (Ent) and Ultisol (Ult)............................................................................................392-2 Effect of silicon sources and rates on dr y root and leaf mass at 35 DAP in Entisol (Ent) and Ultisol (Ult). ...................................................................................................... .402-3 Effect of silicon sources and rates on soil and leaf silicon concentrations at 35 DAP in Entisol (Ent) and Ultisol (Ult). ......................................................................................412-4 Correlation between soil silicon c oncentration (0.5 N acetic acid (CH3COOH) extractant solution) and leaf silicon concentration (Elliot and Snyder, 1991). ..................422-5 Effect of silicon sources and rates on soil and leaf silicon concentrations at 35 DAP in Entisol (Ent) and Ultisol (Ult). ......................................................................................432-6 Correlation between soil silicon c oncentration (0.5 N acetic acid (CH3COOH) extractant solution) and leaf silicon concentration (Elliot and Snyder, 1991). ..................442-7 Effect of silicon source and rate on soil properties at 35 DAP in Entisol (Ent) and Ultisol (Ult), in the first experiment. .................................................................................452-8 Effects of silicon sources and rates on soil properties at 35 DAP with the standard deviation mean bars, in the second experiment. ................................................................463-1 Effects of soil and foliar applied Si on Roundup Ready and forage soybean cultivar leaf mass, with standard deviation of mean bars. ..............................................................603-2 Soil Si concentration and leaf Si con centration at 69 DAP fo r the roundup-ready and forage soybean cultivar in the first experi ment, with standard error of mean bars. ..........613-3 Soil Si concentration and leaf Si concentration at 34 DAP in the second experiment, with standard deviation of mean bars. ...............................................................................623-4 Disease progress of Asian soybean rust with standard deviation of mean bars, in the first experiment. ............................................................................................................. ....633-5 Disease progress of Asian soybean rust with standard deviation of mean bars, in the second experiment. ............................................................................................................ 644-1 Leaf Si concentration at the R7 (beg inning maturity) soybean physiological stage, with standard deviation of mean bars. ...............................................................................804-2 Disease progress of Asian soybean rust with standard deviation of mean bars, in year 1. .................................................................................................................................81

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10 4-3 Disease progress of Asian soybean rust with standard deviation of m ean bars, in year 2. .................................................................................................................................82D-1 Daily average of total ra infall and air temperature. ....................................................... 1133E-1 Visual scale used for field experiments to evaluate seed quality. equated to undamaged seeds, and equated to the most damaged seeds. .................................... 1144

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11 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science FOLIAR AND SOIL APPLIED SILICON EFFECTS ON ASIAN SOYBEAN RUST ( Phakopsora pachyrhizi ) DEVELOPMENT IN SOYBEAN UNDER GREENHOUSE AND FIELD CONDITIONS By Ernane Miranda Lemes December 2009 Chair: Cheryl L. Mackowiak Cochair: Lawrence E. Datnoff Major: Plant Pathology Asian soybean rust (ASR), caused by Phakopsora pachyrhizi H. Sydow & Sydow is one of the most destructive fungal diseases of soybean production world-wide. The main effect of ASR is reduction of photosynthetic area, ensui ng premature defoliation, early plant maturation and low seed quality. Great yield reductions are common to fiel ds of soybean that were under severe ASR pressure and when no fungicide is applied for control. Fertilization with silicon (Si) has been studied as an alterna tive against ASR since this element has suppressed plant diseases in other host-pathogen systems. Greenhouse and fi eld studies were conducted to evaluate the effects of foliar and soil a pplied Si sources on soybean development and ASR control. Greenhouse experiments incl uding wollastonite (CaSiO3) rates ranging from 0 to 8 metric tons (MT) ha-1, two soil orders (Entisol, Ultisol) a nd two soybean cultivars (DP 5634RR, Hinson Long Juvenile) showed that soybean accumulated Si and the level of accumulation increased as the soil Si rate increased. However, under no noticeable abiotic or biotic stresses in the greenhouse, different Si rates did not consistently affect soybean stem diameter, trifoliate area, dry root mass or dry leaf mass. In general, low correlations existed betw een Si rates and plant

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12 development. The average plant development evaluations were greater for Ultisol treatments and for treatments including wollastonite sources w ith small granular size. In another set of greenhouse experiment, two soybeans cultivar re ceive applications of wollastonite (0, 960, 1920 MT Si ha-1) or potassium silicate (K2SiO3) (0, 500, 1000, 2000 mg Si kg-1) and then were inoculated with P. pachyrhizi The results showed that soil Si tr eatments had more soil Si and an average delay of three days in disease onset for bo th soils tested. The eff ects of Si treatments on the area under disease progress cu rve (AUDPC) of ASR showed that the different Si treatments (soil or foliar) were not significantly different from each other, or among Si rates, but were significantly lower than non-Si treat ments. For the field experiments, wollastonite was applied to the soil (0, 480, 960, 1920 MT Si ha-1) and K2SiO3 was applied foliarly (0, 500, 1000, 2000 mg Si kg-1). Two soybean cultivars were planted on an Ultisol. An average delay of three days was observed for soil Si treatments. Up to 43% a nd 36% reduction in AUDPC were observed for soil and foliar Si treatments, respectively. No signi ficant and consistent results were observed between Si and non-Si treatments for seed quality 100 seeds weight or crop yield. These results suggest that soil Si amendment effects might be restricted to the early stages of P. pachyrhizi infection process, as exemplified by de laying the onset of ASR development. Although Si effects on ASR were limited, the use of Si amendments, such as wollastonite and potassium silicate may still be useful in su stainable soybean production. Combinations of Si amendments with other organic approved produc ts might have great potential to maximize control of ASR. The use of Si amendments to ma nage plant disease in co mmercial soybean fields may reduce production costs by reducing the number of fungicide applications. The time delay observed by soil Si amendment use may lead to ASR control practices that can benefit both, organic and conventional s oybean production systems.

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13 CHAPTER 1 LITERATURE REVIEW Soybean Soybean, Glycine max L (Merr.) is an annual legume domesticated by farmers in northeastern China, during the Shang dynasty (1550-1027 B.C.), where its seeds were used as human and livestock food, and for medicinal pur poses. By 1765, soybean was introduced into the United States, where it eventually became a major oil and feed crop (59). Soybean typically grows to a height of 75 to 125 cm, and may be sparsely or densely branched, depending upon the cultivar and growing conditions (160). Its diffuse root system consists of a taproot that can reach up to 200 cm deep, and a large amount of secondary roots, which support several orders of smaller roots, covering a horizontal ra dius of 250 cm (41). The soybean plant has simple compound (trifoliate) leaves arrange d alternately (173). Soybeans growth habit is classified as either in determinate, in which the terminal bud continues to be active during most of the growing season, or determinate, in which the terminal bud ceases growth with the onset of re productive development (41,56,185). Soybean has a typical papilionaceous flower with a high percentage of self-pollination (185). Its seed has a high protei n (38-45%) and oil (20 %) content. Warm mean temperatures of 20 C to 30 C favor seed production. Soybean is impor tant globally, with an estimated global production of 218 million metric ton (MMT) fo r the 2007/08 season with 81, 61, and 47 MMT coming from the U.S.A, Brazil, and Argentin a, respectively (189,190). In the United States, soybean is the second largest crop in cash sales. Additionally, it is the number one export crop, with an annual cash value of approximately $28 billion in 2007 (170). Th erefore, this crop is essential to the US farm economy.

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14 Phakopsora spp. Tax onomy Among soybean foliar diseases, rusts are the mo st destructive to crop development, yield, and profits. Most soybean rusts are autoecious (absence of alternate hosts) and microcyclic (having uredinial and telial s pore stages) fungal diseases ca used by two different obligate filamentous fungi of the same genus, Phakopsora (Uredinales: Phakopsoraceae) (134). The less virulent soybean rust commonly found in the Western Hemisphere (122,191) is referred to as Phakopsora meibomiae (Arthur) Arthur 1917 (anamorphic: Malupa vignae (Bresadola) Y. Ono, Buritic & J.F. Hennen), while Phakopsora pachyrhizi H. Sydow & Sydow 1914 (anamorphic: Malupa sojae (Hennings) Ono, Buritica & Hennen), causi ng Asian Soybean Rust (ASR), was determined to be the more aggressive of the two species, but its occurrence was limited to Australasia until the early nineties (134). The two soybean rust species share a high degree of mor phological similarity, making discrimination between the species difficult, ev en under the microscope. Eventually, real-time polymerase chain reaction (PCR) confirmed species differences (2,53). Even so, a single common name is often used to describe both pathogens. Other complications often precluding an accu rate ASR diagnosis is that it may be confused with other diseas es, such as brown spot ( Septoria glycines Hemmi), downy mildew ( Peronospora manshurica Naumov), frogeye leafspot ( Cercospora sojina Hara), bacterial blight ( Pseudomonas syringae van Hall), and bacterial pustules ( Xanthomonas axonopodis pv. Glycines Nakano), especially at the very early stag es of disease onset and development (59,163,182). Phakopsora spp. Morphology Phakopsora pachyrhizi and P. meibomiae identif ication is usually limited to the uredinial or telial stages, because spermagonial and aecial stages have not been described (55). Under

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15 laboratory conditions, teliospores germinate into basidiospores, whic h apparently serve no known purpose in the soybean ru st cycle at present (151). The uredinia are typically hypophyllous (growt h on the abaxial leaf side), not often amphigenous (growth on both leaf sides), and spatially sprinkled, or found in clusters on yellowish lesions. Each uredinium is 50 to 150 micr ons in diameter. It has a subepidermal origin surrounded by hymenal paraphyses that arise fr om a peridioid pseudoparenchyma. Paraphyses are usually cylindric to clavate, 25 to 50 6 to 14 m, slightly th ickened at the apices and pale yellowish-brown to colorless. Microscopic obser vation reveals a volcano shape uredinia with a central ostiole and pulverulent a ppearance. Uredinia are pale to cinnamon-brown in color (134). Urediniospores are sessile, obovoid to broadl y ellipsoid, 18 to 34 15 to 24 m, with a minute and dense echinulate surface (spiny spores). The walls are approximately 1 m thick. The color of urediniospores ranges from pale ye llowish-brown to colorles s. An average of six germ pores is found at the uredin iospore equatorial zone (134). The subepidermal telia often occur mixe d with the uredinia and are equally hypophyllous and crustose. The telia have a chestnut-brown to dark brown color (134). The teliospores are single-celled and irregularl y arranged in 2 to 7 spore layers in P. pachyrhizi or 1 to 5 spore layers in P. meibomiae. The teliospore shape varies from oblong to ellipsoid and they are 15 to 26 6 to 12 m. The teliospore walls are approximately 1 m thick (P. pachyrhizi ) or 1.5 to 2 m thick (P. meibomiae ); however, in the outermost walls of the teliospores are thick ~ 3 m ( P. pachyrhizi ) or 6 m ( P. meibomiae ). Teliospore color varies from pale yellowishbrown to colorless ( P. pachyrhizi ) or cinnamon-brown to light chestnut-brown ( P. meibomiae ) (19,134,194).

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16 Asian soybean rust Disease and Symptomatology Phakopsora pachyrhizi or ASR was first reported in 1902 in Japan (66), and was m ainly confined the neighboring countries of China, I ndia, Thailand (5,6) and the Oceania countries (163). On May 1994, ASR was first observed on the Hawaiian Islands (82). Soon after, P. pachyrhizi was reported in many central and southe rn African countries (91,92). By 2001, the disease had spread to South America, where it was reported in Paraguay (127). Brazil (195) and Argentina (148) confirmed the presence of P. pachyrhizi in 2002, Bolivia and Colombia in 2003, and Uruguay in 2004 (122,195). More than 10 years later (November, 2004), ASR was reported in Baton Rougue, LA, USA (154). The fast global urediniospores spread and its severe pathology ma kes ASR an important soybean disease (59,73,129). Yield loses can reach 100% (14,17,18,37,60,90,175). Direct losses caused by ASR in Brazil in 2003 were approximately $2.0 billion (US dollars) (195), with heavily infected plants having fewer pods, very p oor seed quality (18) and lower protein values (133). Unlike other rusts, P. pachyrhizi and P. meibomiae infect an unusually wide range of legume species. Phakopsora hosts are restricted to the Fabaceae family (18,134), but the host range within the family is not fully define d. Under controlled condi tions, 158 species in 54 genera of the subfamily Papilionoideae can host P. pachyrhizi (99,134,149,155,163,167), where as 60 species in 31 genera can host P. meibomiae (163). Important hosts include kudzu ( Pueraria lobata Willd.), yam bean ( Pachyrhizus erosus (L.) Urban), bean ( Phaseolus vulgaris L.), and cowpea (Vigna unguiculata (L.) Walp.). A large host range refl ects the diversity and complexity of the virulence patterns of P. pachyrhizi which has helped its su rvival and overwintering on green bridges, such as kudzu, a weed pest of the southern United States. The ability of P.

PAGE 17

17 pachyrhizi to infect many different hosts is, in part, due to its capability of directly penetrating the host leaf surface without being limited to natural openings, such as stomates (86). Urediniospore germination begins the ASR infe ction process. The germ tube grows from 5 to 400 m long along the leaf surface until making contact with an anticlinal wall or the center of a leaf cell to form an appressorium. An a ppressorium is a thickened hyphae tip that works under turgor pressure to puncture against the hos t epidermis. When urediniospore germinates on stomata, the appressorium penetr ates one of the guard cells and avoids entering the leaf through the stomatal cavity (14,98,115). Once the appressori um is in place, an appressorial peg makes direct penetration into epidermal cells, reach ing the intercellular space of the mesophyll. Subsequently, growth and development of a ha ustorium begins between 24 and 48 hours after penetration (85,86). Approximately seven days af ter appressorium penetration, uredinia are formed in the spongy mesophyll. Approximately nine days after infection, the first urediniospores are produced and released in clumps (85,162). Each uredinium is prolific for about three to six weeks, producing more th an 12,000 urediniospores on average (19,37,85,109). Secondary uredinia will infect along the margins of the initial uredinia for the following eight weeks, depending on moisture availability (85). From an initial uredinium, inoculum can be produced for more than 15 weeks (85). An important factor controlling ASR establishment is temperature, where the optimum range is 15 to 29C (91,108,118). With temperatures at or above 9 C, the ASR urediniospores stay viable for up to 27 days (180). Afte r being dispersed by wind or windblown rain, urediniospores require 6 to 12 hours of moisture on a l eaf surface for germination (33,60,108,118). Humid conditions prom ote faster pathogen spread once infection has taken

PAGE 18

18 place. Under favorable conditions, soybean rust ca n progress fast, reaching high disease severity in less than 20 days (48,75). Soybean susceptibility to ASR may occur at any growth stage (40) but the symptoms most often occur at late vegeta tive to early reproductive stages (37,86,115). Tan to reddish, dark brown polygonal lesions or pustules (2-5 mm2) are the most common visual symptoms of ASR infection in soybean. Typically, the symptoms take place initially on older leaves at lower portions of the canopy. Lesions can be found on petio les, pods, and small stems but pustules are most abundant on leaves (162). Seve re cases lead to plant defolia tion, which is, by far, the most important cause of yield loss. Consequently, plants infected early are more prone to yield losses (181). Three types of lesion may be observed on soybean: 1) tan lesions (TAN) having a shorter latent period and many uredinia and abundant sp orulation, resulting in hi gh plant susceptibility, 2) reddish-brown lesions (RB) having a longer latent period and fewer uredinia and lower sporulation, resulting low plan t susceptibility, and 3) no visi ble symptoms, due to a plant immune reaction (18,19). Partial or rate-reducing resistance to rusts has been reporte d (183). Additionally, specific resistance to a restricted number of P. pachyrhizi isolates has been identif ied for six single genes, such as Rpp1 (116), Rpp2 (19), Rpp3 (19,62), Rpp4 (61), Rpp5 (54), and Rpp?(Hyuuga) (126). Unfortunately, single gene resistan ce has not been long-lasting, wher e the resistance effect is lost soon after the source is identified (87). Asian soybean rust Disease control There are th ree general methods for controlli ng ASR: 1) cultural, i.e. crop rotation, population stand, and row spacing, 2) genetic thr ough breeding for resistance, and 3) chemical through the use of fungicides. Cultural and gene tic methods have had limited success, while

PAGE 19

19 chemical controls have been successful in contro lling ASR epidemics. However, in years of high ASR pressure in China, yield reductions have approached 50%, even with the use of fungicides (198). Classes of fungicides used to manage ASR are either protective/contact (pre-infection) or as curative/systemic (early post-infection). Protective fungicides interrupt fungal energy production and are applied to successfully prev ent spore germination and pathogen penetration on the host. The most common fungicides in th is category are chlorothalonil (e.g. Echo 720, Bravo). In the curative/systemic category are tr iazoles (e.g. Alto, Folicu r) and strobirulin (e.g. Quadris, Headline) fungicides. The mode of action of triazoles is th rough the inhibition of sterol biosynthesis, which disrupts cell membrane produc tion. Strobirulin fungicide s act interfering the with energy production in the fungal cell. The high application costs, lower efficacy under high ASR pressure and potential environmental risks of fungicide sprays, leaves room for investigati ng other options, including organically-approved options for controlling ASR. Minimal use of off-farm inputs and management practices that restore, maintain, and enhance ecological harmony exemplify organic production systems (OPS). Consequently, organi c producers can not use synthetic chemicals (i.e., fertilizers, pestic ides, antibiotics, etc). Few choices are available for suppressing di sease development in OPS. Sulphur and copper compounds are among the accepted treatm ents for suppressing plant disease (25,34,64). Sulphur-based compounds are among the oldest known fungicidal treatment, which was first recommended for fruit tree diseases (49). Copper compounds, such as the Bordeaux mixture (1:1:100, CuSO4:Ca(OH)2:water), can be effectively used agai nst diseases such as leaf spots, caused by bacteria or fungi, powdery mild ew, downy mildew and various anthracnose

PAGE 20

20 pathogens. Although copper sulfate r eceived organic approval, the long -term use of copper as a pesticide can increase soil copper concentrations to levels harmful to plant growth (3,88,121). Biofungicides, such as Ballad Plus are available to suppress ASR in OPS (117). Ballad Plus is an aqueous suspension based on the bacterial strain Bacillus pumilus (QST 2808 strain). However, treatments including Ballad Plus have not shown si gnificant reductions in ASR severity when compared to chemical treatments (161). In addition, for effective protection, Ballad Plus needs to be applied every 14 days from flowering stage to pod fill. Another approach for controlling ASR may be through plant mineral nutrition. Many studies have reported examples of amendments containing silicon (Si) for enhancing plant resistance to diseases, such as stem canker ( Diaporthe phaseolorum f. sp. Meridionalis MorganJones) in soybeans (79), Pythium ultimum (Trow) in cucumber (23), brown spot ( Cochliobolus miyabeanus Ito & Kurib.) and blast ( Magnaporthe grisea Hebert) in rice ( Oryza sativum L.), along with several other host-pathogen systems (f or reviews see: 26,30,100). Silicon Geochemistry Over one quarter of Earths crust m ass is comprised of Si (184,187). The total soil Si composition varies greatly among soil orders, ranging from 5 to 831 g kg-1 (20). Histosols contain less than 1% Si on a dry weight basis (10,89,172,172) while very old Podzols developed in quartzitic sands have up to 45% Si on a dry weight basis (166). Soils of mineral origin, such as the Entisols, Ultisols and Spodosols of the subtropics have high total soil Si concentrations (20), but low soluble Si c oncentrations (28,52). Soil Si pools are derived from primary and secondary (clay) minerals, as well as secondary microcrystalline minerals (e .g. authigenic quartz) and biogenic Si (13,22,39,81,113,125). Environmental conditions (temperatu re and rainfall) and soil conditions (parent material, texture, soil pH, and organic composition) influence soil Si chemistry. Mineral

PAGE 21

21 weathering results in the slow re lease of Si and other nutrients into solution and an accumulation of refractory silica, namely quartz (39,51). Sili con primarily exists in the soil solution as orthosilicic acid or silicic acid (H4SiO4), which can be taken up by plants, lost by leaching, runoff, or precipitated as amorphous silica (nSiO2) on the surface of Fe and Al oxides (38,39,71). Soil pH has a major influence on Si concentrat ions in soil solution, where Si solubility increases with an increase in soil pH (>9.0) as a result of the formation of silicate ions from silicic acid (Equation 1-1) (78). H4SiO4 + 4OH[SiO4]4+ 4H2O (1-1) Under strongly acid conditions, orthosilicic aci d can be converted into polymeric silicic acid which is commonly found in chains, bran ched or clustered (35,36,188). Complex bonds between Si and organic compounds in soil solution (114) and the presence of Al (pH=6) seems to stabilize Si against depolymerization (36,188). Soil solution Si concentrations are typi cally between 0.1 and 0.6 mM within the physiological range of soil pH (39,44). Values gr eater than 2.3 mM ( 65 mg Si L-1) at 25 C, resulted in polymerization of Si into a silica gel (SiO2.H2O), and consequently, precipitation may occur (78,112). On continuous cultivated fields and highl y weathered soils, the concentration of bioavailable Si is low (42,153) and amendments containing Si are necess ary for crops known as Si accumulators (e.g. rice, sugarcane ( Sacharum spp. hybrid)). In Brazil, Florida and Hawaii, fertilization with Si has become a routin e practice for nutrient management and yield improvement in rice and sugarcane production (31,138,153). Plant Available Silicon Sources In cases where silicates are depleted, plant-available Si can be resupplied through soil am endments (4). Among silicate fertilizers, the most commonly available are calcium and

PAGE 22

22 magnesium silicate slags (by-pr oducts of metal smelters and electric-arc furnace phosphorus production). Other available Si fer tilizers include wollastonite (CaSiO3), potassium silicate (K2SiO3), and cement and rock dust (granite). Of thes e fertilizer sources the naturally occurring mineral, wollastonite and potassium silicate, may meet the U.S. organic certification criteria, although it is not currently certified. Fertilization with calcium silic ate slag (20% Si, 33% Ca) is a common practice used to increase the soil silicate concentrations of Histosols (less than 25 mg extractible Si L-1) and therefore improve rice production in Florida (28,29). Biogenic sources are also important for suppl ying plant-available Si. Through the process of plant residue decomposition and mineralizat ion (16,67,69,167), Si is taken up by the plant and is returned to the soil solution. For example, rice hulls (8% Si) are applie d to the soil to recycle Si back to the next rice crop ( 165). Another biogenic Si source is plant-derived, opal phytoliths that contain Si concentrations genera lly below 3% on a soil mass basis (39). Silicon Uptake in Plants W ith soil pH less than 9, plant Si uptake is primarily through diffusion and transpirationinduced root absorption (42,103,141). Plants r eadily absorb Si as silicic acid (H4SiO4), a monomeric uncharged molecule (44,178). Once in th e plant, Si transport to the shoots is influenced by the transpiration stream, where it is deposited mainly as amorphous silica gel (SiO2nH2O), or opal phytoliths when the silicic ac id concentration approaches 2 mM (42, 44,124,140). The major Si deposition sites are terminal sites of the transpiration stream, at leaf edges, in trichomes, and cell walls. Commonly in rice pl ants, Si accumulates in intercellular spaces beneath the cuticle layer (197). Th e partition of absorbed Si in pl ants is estimated to be about

PAGE 23

23 90% as silica gel, while only 0.5-8% of Si remain s in the form of silicic acid (150,197). There is no reported redistribution of Si in the plan t tissue (140). Across plant species, the Si concentration in leaves may range from less than 1 g kg-1 to more than 100 g kg-1, on a dry mass basis (42,44,45,103,164). The large variation in Si concentrations among plant species may be attributed to differenti al root uptake proficiencies. Based on Si content in plants and uptake rate of Si relative to water, three modes of Si uptake were suggested: 1) active (higher in take of Si than water), 2) pa ssive (similar intake of Si and water) and 3) rejective (lower inta ke of Si than water) (101,179). Plants with high Si content, such as thos e from the Gramineae and Cyperaceae families, Si tissue concentrations can not be expl ained by passive diffusi on alone (42,123,177). A study with rice, cucumber ( Cucumis sativus L.) and tomato ( Solanum lycopersicum L.) identified that a transporter ( Km = 0.15 mM) was involved in the radial tran sport of Si from th e external solution to the root cortical cells (123). Interestingly, the transporter was identified in all species studied, but at different concentrations, in the order of rice>cucumber>tom ato. A recently identified gene ( Lsi1 ) encodes for a Si influx transpor ter was identified in rice roots (104). This gene is restricted to the distal side of the exodermis and endodermis cells, where the Casparian strip is located. With no similarity to Lsi1 the gene Lsi2 was subsequently identified, which encodes a Si efflux transporter also localized in the exodermis and endodermis cells, but at the proximal side of the cells (105). For rice Si tran sport out of the xylem, a th ird gene is involved (Lsi6 ) (193). The Lsi6 is expressed in the xylem parenchym a cells in leaf sheaths and blad es, affecting Si distribution in shoots. This system of influx and efflux tran sporters on opposite sides of the cell membrane permits effective transcellular Si transport, thereby supporting high concentrations of Si in rice shoots.

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24 In contrast to the active Si uptake mode, ther e are the passive and rejective modes. Plants described as Si passive up takers, such as melon ( Cucumis melo L.), strawberry ( Fragaria spp. hybrid) and soybean are characterized by not significantly depleti ng the Si concentration from the uptake solution (101,179). Plants characterized as Si rejectiv e uptake, such as tomato and bean ( Phaseolus sp.) (78,179) tend to exclude Si from th eir tissues, and increas e Si concentration of the uptake solution. Silicon Benefits Although som e researchers have reported the quasi-essential ity of Si to higher plants (45,179); the role of Si in plant biology is still not well defined, and there is still a lack of direct evidence of Si being an essential nutrient in the plants physiology or plant constituents (44,45,93). However, early research result s have indicated the beneficial effects of Si amendments, especially for accumulator plants, such as rice (169), as well as for some dicotyledonous species (44). The beneficial effects of Si amendments increased as the Si accumulation in the shoots increased (100). Crop yield gains following Si amen dments is often a resu lt of increased growth, improved mineral nutrition balance, mechanical strength, and resi stance to various environmental or abiotic stre sses (30,100,153). Benefits includ e increased disease and pest (insects) resistance, improved phot osynthetic activity, improved to lerance to nutrient imbalances, drought (101), frost, salt (Na) (96,111) and radiation damage (30,100,176). Under conditions of low Si availability, Si accumulator plants have experienced signi ficant reductions in growth and consequently crop yields and higher suscepti bility to both biotic and abiotic stresses. Under Si-free growing conditions, soybean pl ants at the floweri ng physiological stage were markedly inferior and the newly-developed leaves (7th and 8th leaves) had leaf malformations, such as marginal curling. Necrotic leaf spotting was observed in severe cases and

PAGE 25

25 the pollen fertility of Si-free plants was lower (128). Silicon amendments alleviated Al and Mn toxicities in rice (24;101) and s oybean (7,84,95). This may be, in part, due to the lime effect of most Si sources (7) when plants are grown in acid soils. Additionally, Hodson and Evans (1995a) reported a co-deposition within the plant of Si complexes with the toxic elements. The ameliorating effect of Mn toxicity by Si amen dments in barley was a consequence of a more homogeneous distribution of Mn in the leaves (110,186). Siliconmediated Disease Resistance Rice fertilization with Si suppresse d the incidence of neck blast ( Magnaporthe grisea ), thereby reducing or elim inati ng the need for fungicides (28,1 56). Greenhouse studies have shown positive correlatio ns between cucumber ( Cucumis sativus ) resistance to powdery mildew ( Sphaerotheca fuliginea Schlecht.) and the amount of solubl e Si in soil amended with soluble potassium silicate (8,120). The effect of Si on plant disease resistance may be due to an accumulation of Si in the epidermal tissues and the stimulation of pathogene sis-induced host defense responses (45). It is hypothesized that the accumulation of absorbed Si in the epidermal tissu e forms a mechanical barrier (83). The major locations for polymerizati on of silica bodies found in leaf cell walls and in specific shoot cells (103,139). This corresponds to the primary in fection sites of various plant pathogens (46). Also, it is possi ble that Si forms lignin-carbohydr ate complexes in epidermal cell walls, thereby increasing ce ll resistance to degradati on by fungal enzymes (26,45). Cucumber plants fertilized with Si had mo re rigid and greener leaves (1). In rice, increased resistance to M. grisea has been associated with si licified long and short cells and bulliforms cells (65,74,174). Silicon amended rice plants produced a 2.5 m thick silica gel layer just beneath the cuticle of leav es and sheaths, which resulted in a double cuticular layer that protected and mechanically strengthened plants (196). However, the density of silicified cells in

PAGE 26

26 rice leaf epidermis is not always proportional to the degree of rice blas t disease (63), thereby suggesting that the mechanisms of plant resi stance are more complex than only a physical barrier. A second mechanism may be a result of quick inhibitory compound production and deposition. Polymerized Si acts as a biochemical ba rrier and the presence of soluble Si improves this resistance mechanism (50,120). Plant disease resistan ce may increase through the altera tion of the plant response to parasite attacks by increasing to xin synthesis (e.g. phytoalexins) (110). For example, rice plants amended with Si had empty M. grisea hyphae surrounded by a granular osmiophilic material (146) and 2 to 3 times more momilactone phytoale xins were detected in leaf extracts (147). Maekawa et al. (2002a, 2002b) observed an im pressive increase in superoxidase (O2 -) generation in rice leaves 15 minutes after M. grisea inoculation. In cucumbers, fungal infections triggered a systemic acquired resistance (SAR) that induced Si polymerization around the penetration site, disrupting the infection process (80,120,150). Silicon treatments for cucumber resulted in rapid chitinase, peroxidase and pol yphenoloxidase activation against Pythium ultimum (23). Si deposition within cell walls and Si-ac tivated compounds may enhance plant defense mechanisms against biotic and abio tic stresses. Intense Si depositi on beneath the cuticle of leaves can delay fungal penetration and disease pr ogression, providing enough time for plant host defenses to produce considerable amounts of phytoalexin compounds or proteins capable of causing fungitoxicity at the infection site and, as consequence, decrease disease severity. Recently, the results found by Pereira et al (2009) studying the pathosystem soybeanASR indicated that the foliar appl ication of Si reduced the ASR severity, but did not enhance the activity of soybean enzymes (e.g. quitinase, glucanas e, peroxidases) recognized as participant of

PAGE 27

27 the plant defense system, suggesting that the e ffects of foliar applied Si on ASR development might be a consequence of the Si solution on l eaf surface affecting urediniospore germination and/or penetration. As mentioned previously, ASR is a serious disease of soybeans. Allied with severe host damage and easy urediniospores spread, are the high costs to control ASR for commercial production systems. There are even fewer options to control this disease in OPS. Silicon amendments may improve plant to lerance to various stresses in various crop production systems. Additionally, the scarce number of reports on Si use in soybean against ASR requires further study. Hypothesis Soil application of wollastonite (CaS iO3) or foliar application of potassium silicate (K2SiO3) will improve soybean growth and developmen t, and reduce the incidence and severity of Phakopsora pachyrhizi Objectives 1) Determine a rate-response of soil applied wollastonite (CaSiO3) and foliar applied of K2SiO3 using two different North Florida soil orders (Entisol and Ultisol) on soybean Si accumulation and plant growth. 2) Determine rate-response of wollastonite so il applications as comp ared with foliar Si applications (K2SiO3) on the incidence and severity of Phakopsora pachyrhizi infection under greenhouse conditions. 3) Determine the effect of soil and foliar Si fertilization on Si com position and the incidence and severity of Phakopsora pachyrhizi infection under field conditions.

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28 CHAPTER 2 SOYBEAN RESPONSE TO SILICON TREATM ENTS USING T WO SOIL TYPES UNDER GREENHOUSE CONDITIONS Introduction Silicon (Si) is not consid ered to be essential to plants, but beneficial effects are frequently found. These include resistance to insect predation and dis ease development, enhanced photosynthetic activity, and reduced damage cau sed by mineral toxicity, drought and frost stresses (for review see 30,45,100). These effects are reported to va ry with Si concentration in the plant and stress intensity (100,101,103). Plant roots take up Si primarily as silicic acid or orthosilicic acid (H4SiO4) (178). Silicon absorption and transport in roots involves bot h, transporter-mediated movement and passive diffusion (42,104,105,123,193). Once in the vascular bundle silicic acid transport to the shoots is typically through evapotranspiration-driven pass ive diffusion. In rice, Si polymerizes in the epidermal cell surface beneath the cuticle layer, forming a silica-cuticle double layer (197). These Si depositions in leaves may mechanically protect plants against biotic and abiotic stresses (45,100). The Si concentration range found in plant dr y mass can range from less than 1 to more than 100 g kg-1 dry mass (42,44,45,103,164). The large Si con centration range may be attributed to differences in Si uptake mechanisms among plant species. Three modes of Si uptake are proposed: active, passive, and rejective uptak e (103,179). Plant Si uptake might also be influenced by application rate and plant physiological growth stag e (i.e., vegetative and reproductive). Savant et al. (1997) found that under contro lled conditions with no Si supplementation; soybean (passive uptake) did not accumulate more than 5 g kg-1 Si, on a leaf dry matter basis. However, physiological disord ers were observed. These were characterized by leaf curling and curving to th e outside, commonly at the 7th and 8th leaves in the beginning of the

PAGE 29

29 flowering stage, and reduced pollen fertility. In severe cases, necr otic leaf spotting has also was observed (128). Total Si is abundant in mineral soils; however the concentration of bioavailable Si can be quite low, particularly in soils that are under continuous cultivati on (42), and in highly weathered soils, such as Oxisols and Ultisols (153). Acid sandy soils, such as some Entisols, and organic soils, such as Histosols that are ommonly found in Florida, are also low in bioavailable Si (28). Due to inherently low soil bioavailable con centrations of Si, fert ilization with Si in Brazil, Florida and Hawaii has become a freque nt practice for nutrient management and yield improvement in rice ( Oriza sativa L.) and sugarcane ( Sacharum spp. L.) (29,138,153). The most common source of Si amendments, i.e., Ca a nd Mg slags, are common by-products of iron smeltering and phosphorus industries. Other Si sources include potassium silicate (K2SiO3), organically approved crop residues (165), and naturally occurring minerals, such as wollastonite (CaSiO3). The objective of this study wa s to determine if two different soybean cultivars would accumulate appreciable amounts of Si under gr eenhouse conditions using two Si sources at increasing rates in tw o different soils. Materials and Methods Treatments Two greenhouse experim ents were conducted; the first one during Fall 2006 (September to November) at the University of Florida, Ga inesville, FL, and the second experiment during Fall 2007 (August to October) at North Florida Res earch and Education Center, Quincy, FL. The greenhouse temperature and humidity averaged approximately 28 C and 70%, respectively. In the first experiment, a roundup-ready (RR) soybean cultivar (DP 5634RR, maturity group 5) commonly grown in the southeastern U.S. was used. The second experiment included a forage

PAGE 30

30 soybean (FS) cultivar (Hinson Long Juvenile, ma turity group 8). Three soybean seeds were sown per pot. Thinning to one plant per pot was performed ten days after planting (DAP). In both experiments, free-draining, 16-cm high 14-cm diameter plastic pots were filled with 1.5 kg of an Entisol (sandy, siliceous, thermi c Oxyaquic Alorthod, Hurricane series), or an Ultisol (fine-loamy, kaolinitic, thermic Plinthic Kandiudult, Tifton series), collected from north Florida. The initial soil water pH (1:2 v/v) va lues for the Entisol and Ultisol were 6.2 and 6.1; and 0.5 N HOAc-extractable Si (43) values were 18 and 28 mg Si kg-1, respectively, in the first experiment. In the second experiment, initial analysis of soil water pH was 5.6 and 5.9, and 0.5 N HOAc-extractable Si was 16 and 32 mg Si kg-1, respectively. Silicon was applied as CaSiO3 (wollastonite W-10 or DFSP) (Vansil, Vanderbilt Co., Norwalk, CT). Wollastonite W-10 is a fine grade material (median diameter: 15.6 m), while wollastonite DFSP is a crushed, coarse grade material ( 2 mm). Both wollastonite sources contain approximately 240 g Si kg-1 and 340 g Ca kg-1. In the first experiment, W-10 or DFSP was mixed with soil at 0 (control), 0.12, 0.24, 0.48, 0.96, and 1.92 MT Si ha-1 (0, 0.5, 1, 2, 4 and 8 MT ha-1 of wollastonite). This equated to 0, 0.06, 0.12, 0.24, 0.48, and 0.96 g Si pot-1 (0, 0.25, 0.5, 1, 2 and 4 g pot-1 of wollastonite). In the second experiment testing was limited to W-10 at 0, 0.48, 0.96, and 1.92 MT Si ha-1 (0, 2, 4 and 8 MT ha-1 of W-10). This equated to 0, 0.24, 0.48 and 0.96 g Si pot-1 (0, 1, 2 and 4 g pot-1 of wollastonite). After inco rporation, 300 mL of deionized (DI) water was applied to allow the wollastonite to react with the soil for three days prior to sowing. Additi onally, a Si soil drench treatment was included in the first experiment using potassium silicate (K2SiO3) supplied as AgSil 25 (PQ Corp. Valley Forge, PA). At sowing, 15 mL of the 1% AgSil 25 solution was

PAGE 31

31 applied, followed by a reapplication once every week over five weeks, which equated to 1.8 mg Si per pot per application or 122 kg Si ha-1 each week. The drench solution pH was 10.4. All treatments were fertilized with 100 mL of Miracle-Gro 24-8-16 (Scotts Miracle-Gro Prod. Inc. Marysville, OH) stock solution (4 g L-1) at planting to provide 0.096 g N, 0.032 g P2O5 and 0.064 g K2O pot-1 (128 kg N, 43 kg P2O5 and 85 kg K2O ha-1). The pots were watered to field capacity at least once per day. Pots were placed in 15 cm diameter saucers to minimize leaching losses. Measurements and Sampling Plant and so il samples were collected at the beginning of soybean reproduction (35 DAP). In the first experiment, stem diameter was measured at two centimeters above the soil surface with a caliper, and trifoliate area of the most recently fully expanded leaf in each pot was estimated using a caliper to measure the longitudinal and transversal leaf axis. For both experiments, leaves and roots were co llected and washed with distilled water for approximately 10 seconds and oven-dried at 70 C for 48 h to determine dry mass. The samples were ground and sifted through a 2 mm2 stainless steel screen. Rep licate leaf and soil samples within treatments were bulked prior to analyses in the first experiment (one bulked sample per treatment), while all replicates were analyzed from the second study. Leaf Si analysis followed the methodology described by Elliott and Snyder ( 1991), using the autoclave-induced digestion procedure with subsequent automated colorime tric analysis at 670 nm. Concentrations of extractable soil calcium (Ca), magnesium (Mg) and Si were determined, using 0.5 N acetic acid extraction (10:25 v/v soil :extractant) followed by atomic ab sorption spectrophotometric analysis at 422.7, 285.2 and 650 nm, as described in Sanch ez (1990). These analyses were performed at

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32 the University of Florida, Belle Glade Everglad es Research and Educa tion Center soil test laboratory. Soil water pH (1:2 v/v) wa s determined on air-dried samples. Statistical Analyses The first experim ent was a 2 factorial design with 2 Si sources, 2 soils, 7 Si treatments, and 3 replications (n=84), while the second experiment was a 2 factorial design with 2 soybean cultivars, 2 soils, 4 Si treatments, and 3 replications (n=48). Analyses of variance (ANOVA) were determined using PROC ANO VA procedure (SAS Windows version 9.1. SAS Institute. Cary, NC). Means of significant treatment effects ( P 0.05) were compared using Fishers Protected LSD. SigmaPlot software (SigmaPlot version 10.0. Hearne Scientific Software. San Rafael, CA) was used to estimate regressions and to compare the effects of different Si rates on plant biometric measurements and soil analyses. Results and Discussion Plant Biometric Measurements The plant b iometric characteristics measured in the first experiment, stem diameter (mm), trifoliate area (mm2), root and leaf dry mass (g) are presen ted in Figure 2-1, while results for root and leaf dry mass from the second experiment ar e presented in Figure 2-2 (see also Appendix A, ANOVA tables). All plant biometric characteris tics evaluated in the first experiment were significantly different between soil types and there were soil type wollastonite source, as well as soil type Si treatment interactions for several of the measurements (Appendix A). Stem diameter, trifoliate area, dry root, and dry leaf mass from the Ultisol treatment were 10%, 62%, 85% and 72% greater than the Enti sol treatment, respectively (Figur e 2-1). Greater plant vigor in the Ultisol treatment is likely due to higher clay content and therefore greater base exchange and nutrient holding capacity as compared to the Entiso l treatment, which is a much sandier material.

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33 There was a soil Si source interaction, wher e the Entisol soil resulted in somewhat smaller stem diameter using the coarse (DFSP) Si source. There was an additional Si source Si treatment interaction where the W-10 product resulted in somewhat greater stem diameter with increasing Si rates (Figure 2-1 A). However, in both cases, the differences were minor. There was a 3-way interaction (soil source treatme nt) for leaf area in the first experiment. The Ultisol soil led to decreasing leaf area with incr easing Si rates when grown with the fine (W-10) Si source (Figure 2-1 C). There we re soil Si treatment and Si source Si treatment interactions for root dry mass and leaf dry mass, where plants growing in the En tisol appeared more responsive at the low Si concentrations, but growth declined, as Si concen trations increased. In comparison, Si concentration did not influence plan t growth as much as in the Ultisol (Figure 21). Results were more pronounced with the finer (W-10) material than the DFSP. The average root and leaf dry mass in W-10 wollastonite s ource was 21% and 30% greater than the DFSP wollastonite source. In the second experiment, dry root and dry leaf mass (Figure 2-2) we re not significantly different between cultivars or among treatmen ts. However, the response curve for the RR soybean grown in the Entisol showed the greatest root and leaf dry mass va lues at 0.5 MT of Si ha-1, similar to what was observed in the first ex periment (Figures 2.1 a nd 2-2). Other studies (84,128) reported that Si concentration had little effect on soybean growth during early physiological stages. Silicon Composition The soil Si c oncentration (mg kg-1) (Figures 2.3 A and Figure 25 A and B) and leaf Si concentration (dag kg-1) (Figures 2.5 B and Figure 2-7 C and D) in both experiments, generally had high correlations (r2) with Si application rates (MT Si ha-1). In the first experiment (Figure 25 A), for all soil Si rates (considering the same so il type), extractable Si concentration from the

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34 DFSP was lower than the W-10. The average rela tive Si availability ratio (W-10:DFSP) for plants grown in the Entisol was 1.72, compared to 1.45 for plants grown in the Ultisol. Therefore, the soil Si concentra tion using W-10 was about 72% and 45% greater than the soil Si concentration using DFSP for the Entisol and th e Ultisol, respectively. Differences in soil Si concentration between W-10 and D FSP were most likely due to diffe rences in average particle size, with the DFSP being a more coarse materi al. Similar results were found by Datnoff et al., (1992) where the soil and plant tissue Si concentration increa sed as the Si source grade decreased. Also, the author s reported that increased plant Si concentration resulted in greater grain yield and reduced seve rity of rice brown spot ( Bipolaris oryzae (Breda de Haan) Shoem.) and blast ( Pyricularia grisea (Cooke) Sacc.), when compared with controls. The Si leaf concentration increased as the soil Si rates increased, and it seems to maximize leaf Si concentration at the rate of 4 MT ha-1 of W-10 wollastonite (0.96 MT ha-1 of Si) in the first experiment (Figure 2.3 B), a nd for both cultivars on Ultisol in the second experiment (Figure 2.5 B and D). Similar resu lts were observed by Miyake and Takahashi (1985), where the soybean leaf Si co ncentration increased up to 18 mg kg-1 as the Si concentration in hydroponic solution increased too. Soybean plants accumulated relatively high amounts of Si in the leaves in both experiments (Figures 2-3 and 2-5) when compared with the control, suggesting that soybeans might freely transl ocate Si to the shoot from the soil solution. No significant differences between soil ty pes were observed for Si leaf and soil concentration in the second expe riment (Figure 2-5). The averag e leaf Si concentration of RR cultivar was about 30% greater than the average leaf Si concentration of FS cultivar. Plant Si uptake is linked to a transport mediate system and/or evapotrans piration (101,143,179), and both cultivars are likely to evapotranspiration mediated transport. With a ll else being equal, the results

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35 may suggest that RR had a greater rate of ev apotranspiration. In bot h experiments, high correlations (r2) were generally observed between leaf Si concentration and so il Si concentration (Figures 2-4 and 2-6), indicating that the wolla stonite sources (W-10 and DFSP, for the first experiment only) increased the leaf Si con centration as the application rates increased. Other Soil Characteristics The final results for soil pH, extractable Ca (kg ha-1) and extractable Mg (kg ha-1) are given (Figures 2.7 and 2-8) for the first and s econd experiments, resp ectively. In the first experiment, the Si dosing had a greater soil pH correlation with W-10 than with DFSP (Figure 2.7 A). Soil pH (Figure 2.7 A) at Si application rate s of 0.24 and 0.96 MT Si ha-1for W-10 and 0.12, 0.24 or 0.48 MT Si ha-1 for DFSP, were low when compared with the control (0 MT Si ha1). Also, the soil Si treatments resulted in lowe r soil Mg concentrations as compared with the control, for the Entisol treatment (Figure 2.7 C). It was expected that the Entisols would be more responsive than Ultisols to Si soil amendments due to relatively lower buffering capac ity and low initial soil Si, as compared to Ultisols that contain proportionally more clay minerals. The soil results from both experiments (Figures 2.7 and 2.8) showed that as the Si ra te increased the soil pH extractable Ca and extractable Mg concentrations decreased. In the second experiment, a more clear pi cture emerged, where so il pH correlated well with Si rate (Figure 2-8 A and B). The soil pH was significantly different between soils (Entisol pH 6.6; Ultisol pH 6.4) and among treatments. Si nce no significant soil pH differences were observed between cultivars, the average soil pH of the 0, 0.48, 0.96 and 1.92 MT Si ha-1 the soil Si treatments were 6.0, 6.4, 6.8, and 7.2, respectively. The amount of extractable soil Ca found in the Ultisol was greater than for the Entisol, in both experiments (Figure 2-7 B and Figure 2-8 C, D). In the s econd experiment, the amount of

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36 soil Ca in Ultisol treatme nts receiving 1.92 MT Si ha-1 was about 78% and 83% greater than the control treatment (0 MT Si ha-1) for the RR and FS cultivars, respectively. For the Entisol, soil Ca concentration increased 257% and 274%, resp ectively for RR and FS cultivars. Significant differences in soil Ca content were observed betw een cultivars, soils, and treatments. The soil Ca in the RR cultivar treatments was about 3% grea ter than in the FS cultivar treatments, and the soil Ca level in the Ultisol treatments was about 59% greater than in the Entisol treatments (Figure 2-2 C and D). Soil Ca increased with incr easing wollastonite applications (340 g of Ca per kg of wollastonite) for both experiments (Figure 2-7 B and Figure 2-8 C and D). In the first experiment, the amount of soil extractable Mg increas ed in the Ultisol treatments but it decreased in Entisol treatments, as compared with the control treatment (Figure 2-7 C). The wollastonite sources contained a pproximately 0.9% total Mg (1.5% MgO) and no measurable increase in extractable soil Mg co ncentrations were expected to occur upon application. In the second experiment, no signifi cant differences in soil Mg were observed between cultivars (Figure 2-8 E and F). The averag e soil Mg for the Ultiso l was 24% greater than the Entisol, and only the soil Mg level of the treatment with 1.92 MT of Si ha-1 (329 and 328 kg Mg ha-1, respectively for the Entisol and the Ultisol) was significantly greater than the other treatments. The 1.92 MT Si ha-1 (W-10 at 8 MT ha-1) treatment resulted in an equivalent of 72 kg ha-1 of plant-available Mg. Soil Drench The potass ium silicate solution (1% AgSil 25) drench treatment was applied in the first experiment, and it had a resulting soil pH similar to the 0.48 and 0.96 MT Si ha-1 treatments, while the extractable Ca and Mg levels were comparable to lo w Si rates (0.12 and 0.24 MT Si ha1) from W-10. The soil Si concentration was si milar to the soil treatment of 0.48 MT Si ha-1 (4

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37 MT of W-10 ha-1). Stem diameter, leaf area and dry leaf mass were the lowest for the drench treatment, while root dry mass was the highest. The average leaf Si concentration of the drench treatment for the Ultisol and the Entisol were 0.41% and 0.62%, respectively. The leaf Si concentration from the drench treatment applied to the Ultisol was similar to the 0.48 MT Si ha-1 treatment or about 45% greater than the control treatment. Drench applied to the Entisol resulted in a leaf Si concentration about 87% greater than the control. Conclusions This study dem onstrated that Si application rates did not a ffect the vegetative growth response of two different soybean cultivars tested in two different soils for a period of 35 days. Wollastonite had a liming effect, where it increased the soil pH and soil extractable Ca. Rates equal or greater than 8 MT ha-1 wollastonite significantly increased soil extractable Mg. The wollastonite source W-10 increased available Si more than DFSP. The Ultisol soil resulted in greater concentrations of extractable Ca and Mg and resulted in a higher correlation between leaf Si concentration and soil Si concen tration than did the Entisol soil. The generally low correlations observed fo r plant biometric measurements in both experiments (Figure 2-1 and Figure 2-2) indicated that increasing Si rates did not consistently affect soybean growth. Although the soil drench resulted in high leaf Si accumulation, the markedly reduced leaf biomass suggests that th e use of potassium silicate at the rate and frequency used in this experiment may be deleterious to soybean.

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38 Doses (MT Si ha -1 ) 0.00.51.01.52.0 Leaf dry mass (g) 0 2 4 6 8 10 Ent (y=4.15+2.06x-0.985x; r=0.14) Ult (y=8.55-1.07x+0.3224x; r=0.17) Root dry mass (g) 0 2 4 6 8 10 12 14 Ent (y=5.2+7.23x-4.03x; r=0.74) Ult (y=10.19+0.749x-0.631x; r=0.09) Trifoliate area (mm2) 1000 2000 3000 4000 5000 6000 Ent (y=1801+2563x-1258x; r=0.61) Ult (y=3721-1936x+783x; r=0.42) 0.00.51.01.52.0 Ent (y=3.85-1.74x+0.807x; r=0.15) Ult (y=2.26-4.85x+2.26x; r=0.4) Ent (y=4.86-0.2168x-0.2728x; r=0.15) Ult (y=8.43-1.16x+0.15x; r=0.26) Ent (y=1998+105x+52x; r=0.08) Ult (y=3852-801x+478x; r=0.06) W-10 Stem diam. (mm) 3 4 5 6 Ent (y=3.81-0.6202x+0.4478x; r=0.36) Ult (y=4.2+0.1938x+0.4478x; r=0.1) A CD EF G H DFSP Ent (y=3.93+0.0642x-0.0366x; r=0.001) Ult (y=4.42+0.5864x-0.2647x; r=0.05) B Figure 2-1. Effect of silicon sources and rates on plant biometric characteristics at 35 DAP in Entisol (Ent) and Ultisol (Ult) with the st andard deviation mean bars, in the first experiment. A and B) Stem diameter. C and D) Leaf area. E and F) Dry root mass. G and H) Dry leaf mass. A, C, E and G) W-10 wollastonite. B, D, F and H) DFSP wollastonite.

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39 Doses (MT Si ha-1) 0.00.51.01.52.0 Leaf dry mass (g) 0 2 4 6 8 10 Ent (y=4.32+0.3961x-0.3189x; r=0.06) Ult (y=8.21-1.51x-0.2433x; r=0.39) Roundup ready soybean Root dry mass (g) 0 2 4 6 8 Ent (y=3.59+0.496x-0.3091x; r=0.06) Ult (y=6.69-1.78x+0.2203x; r=0.32) 0.00.51.01.52.0 Ent (y=4.97-1.08x+0.4373x; r=0.08) Ult (y=4.92-2.87x-1.09x; r=0.12) Forage soybean Ent (y=4.29-0.3842x+0.0625x; r=0.11) Ult (y=3.82+2.67x-0.9864x; r=0.19) AB CD Figure 2-2. Effect of silicon sources and rates on dry root and leaf mass at 35 DAP in Entisol (Ent) and Ultisol (Ult) with the standard deviation mean bars, in the second experiment. A and B) Root dry mass. C and D) Leaf dry mass. E and F) Leaf silicon concentration. A and C) Roundup Ready soybean cultivar. B and D) Forage soybean cultivar.

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40 0.00.51.01.52.0 Leaf Si (dag kg-1) 0.3 0.4 0.5 0.6 Ent-W10 (y=0.3361+0. 1797x-0.063x; r=0.97) Ult-W10 (y=0.3265+0.134x-0.047x; r=0.53) Ent-DFSP (y=0.2733+0.15x-0.0332x; r=0.66) Ult-DFSP (y=0.2853+0.01x-0.0305x; r=0.96) Soil Si (mg kg-1) 0 50 100 150 Ent-W10 (y=16.97+31.52x+3.65x; r=0.99) Ult-W10 (y=31.5+78.5x-20.78x; r=0.99) Ent-DFSP (y=13.58+10.4x+2.2x; r=0.92) Ult-DFSP (y=29.82+31.66x -9.51x; r=0.96) Doses (MT Si ha-1) A B Figure 2-3. Effect of silicon sources and rates on soil and leaf silicon concentrations at 35 DAP in Entisol (Ent) and Ultisol (Ult), in the first experiment. A) Soil silicon concentration (0.5 N acetic acid (CH3COOH) extractant solution). B) Foliar silicon concentration (Elliot and Snyder, 1991).

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41 Soil Si (ppm) 20406080100 Si Leaf (dag kg-1) 0.2 0.3 0.4 0.5 0.6 Ent (y=0.2459+6.29x-4.45x; r=0.94) Ult (y=0.1589+5.88x-3.4x; r=0.78) 0204060 Ent (y=-6.16+0.0252x-3.53x; r=0.97) Ult (y=1.98+0.0296.x; r=0.95) A BDFSP W10 Figure 2-4. Correlation between soil silic on concentration (0.5 N acetic acid (CH3COOH) extractant solution) and leaf silicon concen tration (Elliot and Snyder, 1991) in Entisol (Ent) and Ultisol (Ult), in the first experiment. A) W-10 wollastonite. B) DFSP wollastonite.

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42 Forage soybean Roundup ready soybean Rates (MT Si ha-1) Soil Si (mg kg-1) 0 50 100 150 Ent (y=14.13+61.46x-1.32x; r=0.98) Ult (y=19.57+77.81x-14.96x; r=0.94) 0.0 0.5 1.0 1.5 2.0 Ent (y=25.87+60.34x-1.15x; r=0.92) Ult (y=32.06+72.09x-10.29x; r=0.98) 0.00.51.01.52.0 Leaf Si (dag kg-1) 0.0 0.2 0.4 0.6 Ent (y=0.1857+0.4028x-0.1385x; r=0.98) Ult (y=0.1808+0.3316x-0.0975x; r=0.93) A BC 0.00.51.01.52.0 Ent (y=0.1622+0.1366x-0.0216x; r=0.95) Ult (y=0.1409+0.4045x-0.1586x; r=0.82) D Figure 2-5. Effect of silicon sources and rates on soil and leaf silicon concentrations at 35 DAP in Entisol (Ent) and Ultisol (U lt) with the standard deviat ion mean bars, in the second experiment. A and B) Soil silicon concentration (0.5 N acetic acid (CH3COOH) extractant solution. C and D) Foliar silic on concentration (Elliot and Snyder, 1991). A and C) Roundup Ready soybean cultivar. B and D) Forage soybean cultivar.

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43 Soil Si (ppm) 020406080100120140 Leaf Si (dag kg-1) 0.0 0.2 0.4 0.6 Ent (y=0.0886+7.62x -3.75x; r=0.93) Ult (y=0.0879+5.4x-0.1871x; r=0.99) 020406080100120140 Ent (y=0.16+0.0008x+0.000004x; r=0.85) Ult (y=-0.1554+0.0107x-5.31x; r=0.91) A BForage soybean Roundup ready soybean Figure 2-6. Correlation between soil silic on concentration (0.5 N acetic acid (CH3COOH) extractant solution) and leaf silicon concen tration (Elliot and Snyder, 1991) in Entisol (Ent) and Ultisol (Ult), in the second experiment. A) Roundup Ready soybean cultivar. B) Forage soybean cultivar.

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44 0.00.51.01.52.0 Mg (kg ha-1) 0 200 400 600 800 Ent-W10 (y=152-19 8x+91x; r=0.56) Ult-W10 (y=308+21 9x-84x; r=0.60) Ent-DFSP (y=123-9 5x+40x; r=0.13) Ult-DFSP (y=286+459x-202x; r=0.81) Ca (kg ha-1) 0 1000 2000 3000 4000 Ent-W10 (y=263+230x+55.58x; r=0.91) Ult-W10 (y=1050+12 46x-278x; r=0.94) Ent-DFSP (y=158+313 x-70x; r=0.73) Ult-DFSP (y=979+161 4x-620x; r=0.92) pH 6.0 6.5 7.0 7.5 8.0 8.5 Ent-W10 (y=6.25-0.1535x+0.3588x; r=0.89) Ult-W10 (y=6.21+0.7 239x-0.1418x; r=0.94) Ent-DFSP (y=5.9+0.74 02x-0.1569x; r=0.68) Ult-DFSP (y=6.39+1. 33x-0.5595x; r=0.67) Doses (MT Si ha-1) A B C Figure 2-7. Effect of silicon source and rate on soil properties at 35 DAP in Entisol (Ent) and Ultisol (Ult), in the first experiment. A) Soil pH (soil water pH). B) Extractable calcium (0.5 N acetic acid (CH3COOH) extractant solution). C) Extractable magnesium (0.5 N acetic acid (CH3COOH) extractant solution).

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45 0.00.51.01.52.0 Mg (kg ha-1) 0 100 200 300 400 500 Entisol (y=142-18x+57x; r=0.96) Ultisol (y=278-192x+118x; r=0.91) Ultisol (kg ha-1) 0 500 1000 1500 2000 2500 Entisol (y=500+910x-86x; r=0.98) Ultisol (y=1384+804x-143x; r=0.96) Roundup ready soybean pH 5 6 7 8 Entisol (y=5.59+1.38x-0.286x; r=0.99) Ultisol (y=6.29+1.17x-0.3157x; r=0.91) 0.00.51.01.52.0 Entisol (y=148-27x+65x; r=0.97) Ultisol (y=252-178x+110x; r=0.74) Entisol (y=484+994x-137x; r=0.98) Ultisol (y=1314+604x-18x; r=0.96) Forage soybean Entisol (y=5.89+0.8378x-0.125x; r=0.61) Ultisol (y=6.23+1.08x-0.2598x; r=0.98) Doses (MT Si ha-1) A BC D EF Figure 2-8. Effects of silicon sources and rates on soil properties at 35 DAP with the standard deviation mean bars, in the second experiment. A and B) Soil pH (soil water pH). C and D) Soil extractable calcium (0.5 N acetic acid (CH3COOH) extractant solution). E and F) Soil extractable ma gnesium (0.5 N acetic acid (CH3COOH) extractant solution). A, C and E) Roundup Ready soyb ean cultivar. B, D and E) Forage soybean cultivar.

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46 CHAPTER 3 EFFECTS OF SOIL AND FOLIAR APPL IE D SILICON ON ASIAN SOYBEAN RUST DEVELOPMENT UNDER GREENHOUSE CONDITIONS Introduction Asian soybean rust (ASR) caused by Phakopsora pachyrhizi Sydow, 1914, is an expressive fungal disease that threatens comm ercial and organic soybean [ Glycine max (L.) Merr.] production around the world (135). The uredin iospores may spread quickly and, as such, a potentially severe pathology make ASR a costly soybean disease (59,73,129). The main effect of P. pachyrhizi on soybean development is a reduction in photosynthetic area causing premature defoliation, early plant maturation, and low seed weight, thereby leading to severe yield reductions (175). High levels of AS R infection also result in plants with fewer pods, poor seed quality (18) and lo wer protein (133). According to the National Agricultural Statisti cs Service (131), Florida planted about 11 thousand hectares of soybean in 2008 out of a total of approximately 30 million hectares nationwide. Gulf Coast states, including Florida, were considered the lik ely introduction zones of ASR into the United States. Recently, 16 states have reported ASR (72). As with other regions of the world, the short-term option for managing ASR in the U.S. is with fungicides, such as triazoles and strobirulins. Howeve r, fungicide applications subs tantially increase the production costs and depending on the disease pressure, one to five fungicide applications are needed to keep the disease below economic threshold. Fungicid es are not always effective. For example, in years of high ASR pressure, soybean yield reduc tions in China were approximately 50%, even with chemical control (198). Mineral nutrition plays an important role in the physiological functi oning of plants, so it can be an important component for managing pl ant disease (110). Studies have reported the positive effects of silicon (Si), for increasing plant resistance to biotic stresses (disease and

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47 insects) and improving plant tolerance agai nst abiotic disturbances (30,44,45,94,96,100). The use of Si may lessen a plants sus ceptibility to fungal diseases. This has been documented for a number of monocots and seve ral dicot species (30,78,93,119,179). The mechanism describing Si effects on plant disease resistance may be associated with either an accumulation of absorbed Si in the epidermal tissue or an expression of pa thogenesis-induced host de fense responses (26). Plant Si concentrations can range from less than 1 to more than 100 g kg-1 on a dry mass basis (44). The broad range of Si concentrations among plant species is commonly attributed to different Si uptake mechanisms. Ba sed on plant Si content, three types of plant Si uptake are suggested: active, passive, and rejective (103,179). Soybeans are classified as passive for Si uptake (similar uptake of Si and water) and usually do not accumulate more than 5 g kg-1 Si. Yield gains in plants supplied with Si have been attributed to se veral possible factors, including increased plan t growth, improved mineral nutritional balance, increased mechanical strength, and resistance to vari ous environmental stresses (153). In Si accumulating plant species such as rice ( Oriza sativa ), wheat ( Triticum aestivum ) and sugarcane (Sacharum sp.), increased plant Si content were directly asso ciated with higher yields (28,42,77,78,153). Soybean receiving Si amendments displaye d reduced Al and Mn toxicity symptoms (7,84,95). However, under Si-free conditions, soybean plants displayed malformations, such as leaf curling of newl y-developed leaves (7th and 8th leaves) during flowering (128). They also reported necrotic spots on soybean leaves and low pollen fertility in cases of severe Si deficiency. Rice fields amended with Si had lower incidence of neck blast (Magnaporthe grisea ) thereby considerably reducing fungicide a pplication requirements (156,157,158). In greenhouse studies, positive correlati ons between cucumber ( Cucumis sativus ) amended with soluble

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48 potassium silicate, K2SiO3 (KSi) and resistance to powdery mildew ( Sphaerotheca fuliginea ) were found (8,120). Recently, potassium silicate fo liar sprays were tested in Brazil against soybean rust where disease severity wa s reduced 70% in some cases (130,145). Considering that Si amendments might suppr ess ASR severity in soybean, the objective of this study was to evaluate the efficacy of Si via soil or foliar applications as a means to improve soybean tolerance against ASR. Materials and Methods Treatments Two greenhouse experim ents were conducted, the first during Summer 2007 (June to August), and the second experiment during Summer 2008 (July to August) at North Florida Research and Education Center (NFREC), in Quincy, FL. Greenhouse temp erature and humidity averaged 28 C and 80%, respectively. Two soybean cultivar s were tested in the first experiment, a Roundup-ready (RR) DP 5634RR, maturity group 5, and a forage soybean (FS) cultivar Hinson Long Juvenile, maturity group 8. In the second experiment, only the RR cultivar was tested. In the first experiment, free-draining, 16-cm high 14-cm diameter plastic pots were filled with 0.85 kg of a potting mix (Hyponex potting soil. Hyponex Corp. Maryville, OH). The potting mix analysis (Mehlich-1 extractant) indicate d that P, K, Ca, Mg, S, B, Zn, Mn, Fe and Cu, were at adequate to very high concentrations (274, 937, 6326, 465, 284, 1.8, 15.7, 19, 306, 3.9 kg ha-1, respectively). The potting mix analysis also indicated that only manganese (19 kg ha1) concentration was in the low range. Potti ng mix pH, organic matter and cation exchange capacity were 6.8, 4%, and 18.9 meq 100 g-1, respectively. In the second experiment, freedraining 18-cm high 15-cm diameter plastic pots were filled with 1.5 kg of an Ultisol, Tifton loamy fine sand series (fine-loamy, kaolinitic, th ermic Plinthic Kandiudult), was used. The initial soil pH (1:2 v/v), extractable Ca and Mg (e xtraction in 0.5 N acetic acid), were 6.7, 2442 and

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49 233 kg ha-1, respectively. The 0.5 N HOAc-extractable Si (43) was 29 mg kg-1. For the second experiment pots were fertilized with 150 mL of nutrient solution three times: at sowing, 15 days after planting (DAP), and 25 DAP. The nutrient solution contained in kg ha-1, 20 N, 16 P, 43 K, 20 Ca, 1 Mg, 13 S, 0.1 B, 0.1 Mn, 0.01 Zn, 0.01 Mo, 0.004 Cu and 0.32 Fe. Pots were placed on plastic saucers (18-cm diameter) to minimize leaching. Three soybean seeds were sown per pot and thinned to one plant per pot at 10 DAP. The plants were watered as needed, typically once per day. Wollastonite W-50 Vansil (Vanderbilt Comp. Norwalk, CT) is a naturally occurring mineral ore that was the Si source used in both e xperiments. The W-50 is a fine grade (talc like) product (median diameter: 2.8 m) containing approximately 24% Si (CaSiO3). Wollastonite was mixed with the soil at rates equivale nt to 0 (control), 0.96 and 1.92 MT Si ha-1 (0, 4 and 8 MT ha1 of W-50), in the first experiment. This equated to 0, 0.48 and 0.96 g Si pot-1 (0, 2 and 4 g pot-1 of wollastonite). For the second experiment the Si rates were 0 (control) and 1.92 MT of Si ha-1 (0 and 8 MT ha-1 of W-50). This equated to 0, and 0.96 g Si pot-1 (0 and 4 g pot-1 of wollastonite). Additionally, a lime treatment wa s included in both experiments to account for liming effect and Ca fertilization provided by th e wollastonite treatment. The amount of hydrated lime (Ca(OH)2) (Cheney Lime & Cement CO. Allgood, AL) a pplied was at a rate equivalent to 8 MT ha-1, i.e., (4 g pot-1 of lime). Foliar Si applications were also tested using potassium silicate (K2SiO3) as AgSil 25 (PQ Corp. Valley Forge, PA). AgSil 25 is a readily soluble Si source with approximately 9.7% Si. An atomizer with a propellant cartridge (Spr-tool Arvoe Ind. Inc,. Gardnerville, NV) was used to apply AgSil 25 at four rates: 0, 500, 1000, 2000 mg Si kg-1 (pH 7.2, 10, 10.1, 10.4, respectively) in the first experi ment. In the second experiment, only two rates (0 and 2000 mg Si

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50 kg-1) were tested. Each plant was sprayed on adaxia l and abaxial leaf surf aces until the point of run-off (approximately 6 mL per plant) The control solution (0 mg Si kg-1) was applied as deionized (DI) water. In the second experi ment a combined treatment of 1.92 MT Si ha-1 (8 MT W-50 ha-1) and a foliar Si application at 2000 mg Si kg-1, was tested in the second experiment. The foliar Si treatment solutions were applied tw ice in the first experiment, at 38 and 48 DAP at the V6 (sixth trifoliate fully expanded) and R2 (full bloom, flower at top 2 nodes) soybean physiological stages. In the second experiment, the foliar Si treatment so lutions were applied 3 times at 18, 23 and 28 DAP at the V3 (third trifolia te fully expanded), V5 (fifth trifoliate fully expanded), and V6 (sixth trifoliate fully expanded) soybean physiological stages. A foliar control treatment of DI water with pH adjusted to 10.4 wi th KOH was also tested to mimic the pH of the 2000 mg Si kg-1 foliar solution pH (pH 10.4). Inoculum Production Leaves with approxim ately 35% diseased area (70) taken from soybean plants cultivated in the greenhouse were gently washed with r unning deionized water and blotted dry with absorbent paper tissue to obtain P. pachyrhizi urediniospore inoculum. Subsequently, the leaves were placed on paper filter (Whatman No. 1, Whatman, Piscataway, NJ), saturated with deionized water, and sealed in a transparen t plastic box. After 48 hr s of incubation at 23 oC, fresh urediniospores were collected with a brush and placed into a 0.05% Tween 20 (Sigma, Saint Louis, MO) solution. A hemacytometer was used to adjust the resulting urediniospores suspension to 14 (first experiment) and 34 (second experiment) cells mL-1. The soybean plants were inoculated on the day after the first foliar Si application, at 39 and 19 DAP for the first and second experiments, respectively. The ur ediniospore suspensions were sprayed using an atomizer containing a propellant cartridge (S pr-tool, Aervoe Indus tries Incorporated.

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51 Gardnerville, NV). Each plant was sprayed on abaxial and adaxial surfaces until run-off (approximately 6 mL per plant). The pots with the i noculated plants were se aled in 50-liter white plastic bags (Glad Tall Kitchen Bag. Oakland, CA) fo r 24 hours. The bag interiors were sprayed with deionized water to keep high rela tive humidity. The first experiment received a second application of urediniospore suspension (14 cells mL-1) nine days after the first inoculation since no symptoms of infection were observed up to that date. Measurements and Sampling Disease sev erity ratings were recorded accord ing to the Horsfall-Barrett scale (70). Seven evaluations were made from 12 August thr ough 31 August 2007 for the first experiment, and fifteen evaluations, from 28 June through 12 July 2008, for the second experiment. Disease evaluations were used to generate the rate ( r ) parameter and create disease progress curves. The r parameter is related to the best fit disease prog ress model and it expresses the rate of disease change as a function of time (21). The area under the disease progress curve (AUDPC) was used to determine treatment effectiv eness against ASR, and was ca lculated using the formula: AUDPC = ii n i iittyy 1 1 1 12, where yi = disease proportion (percentage severity) at the ith observation, ti = time (days), and n = total number of observations (156,159). At 69 and 34 DAP for the first and second expe riments, respectively; all soybean leaves from each pot were collected, gently rinsed wi th distilled water for approximately 10 seconds and oven dried at 70 C for 48 h for dry mass. The samples were ground to pass through a 2 mm2 stainless steel screen. Leaf Si concentration was determined by using the autoclave-induced digestion procedure, following the methodology described by Elliott and Snyder (1991), with subsequent automated colorimetric analysis at 6 70 nm. At the conclusion of each study air-dried

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52 soils were analyzed for pH, extr actable Ca and Mg, and Si concen trations at the University of Florida, Belle Glade EREC soil test laboratory. Briefly, concentrations of extractable calcium (Ca), magnesium (Mg) and Si in soil were dete rmined with 0.5 N acetic acid extraction (1:2.5 v/v soil:extractant) followed by atomic absorpti on spectrophotometry at wavelengths of 422.7, 285.2 and 650 nm (152). Soil pH (1:2 v/v) was determined on air-dried samples. Statistical Analyses The first experiment was a 2 factoria l design with nine treatments and three replications (n=54), while the second experiment was a randomi zed complete block design with two soybean cultivars, seven treatments, and four replications (n=28). Analysis of variance (ANOVA) was used (PROC ANOVA) to determine significan t treatment effects (SAS for Windows, version 9.1. SAS Institute, Cary, NC). The means were compared with Fishers Protected Least Significant Difference (L SD). Treatment means were compared ( P 0.05) using Fishers Protected Least Signifi cant Difference (LSD). SigmaPlot software (SigmaPlot version 10.0. Hearne Scientific Software San Rafael, CA) was used for re gression analysis of Si rate effects over time. Results and Discussion Leaf Mass Results for dry leaf mass, from both experi ments, are presented in Figure 3-1. No significant differences were observed for leaf mass between cultivars (Figure 3-1 A) in the first experiment, or among Si treatments in both experiments. This finding is similar to results observed in other studies (84, 128) where different Si treatments had no effect on soybean growth, especially during early physiological growth stages.

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53 Soil pH, Ca and Mg The results for soil pH, Ca and Mg concentrations (kg ha-1) for the first experiment are presented in Table 3-1, and for the second e xperiment in Table 3-2. Since no significant differences were observed between cultivars fo r the substrate pH, extractable Ca and Mg concentration in the first expe riment, the data were pooled. Treatments with wollastonite (CaSiO3) or lime [Ca(OH)2] had significantly greater soil pH than those without amendments, in both experi ments. Soil extractable Ca also significantly increased in treatments with wollastonite or lime. The average substrate extractable Mg concentration of the 1.92 MT Si ha-1 treatment in the first experi ment was significantly greater (5.5%) than the control treatment, while no significant differences were observed for soil extractable Mg concentration among treatments from the second experiment (Table 3-2). Silicon composition The soil and leaf Si concentrations from the fi rst experiment are give n in Figure 3.2. No significant differences were observed between cultivars for soil Si concentration ( P <0.05). The soil Si concentration in treatments Si-amended were significantly greater than treatments that did not receive soil Si applications. The average su bstrate Si concentration of the 1.92 MT Si ha-1 treatment was 673% greater than the control, and 63% greater than the 0.96 MT Si ha-1 treatment (Figure 3.2 A). Silicon uptake is associated with evapotranspiration mediated transport. Consequently, older leaves are prone to ha ving greater Si concentrations than younger leaves (102). The average leaf Si concentration for the RR soyb ean cultivar was 45% gr eater than for the FS cultivar, in the first experiment (Figure 3.2 B). The soil Si treatments consistently increased l eaf Si concentration in the first experiment. The average leaf Si concentration of the 1.92 MT Si ha-1 treatment was about 29% greater than

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54 the 0.96 MT Si ha-1 treatment and 277% greater than the control treatment (Figure 3.2 A). The leaf Si concentration for the foliar Si treatments (500, 1000 and 2000 mg kg-1) were not significantly different from each other but folia r Si treatments were about 33% significantly greater than the control treatment (Figure 3.2 B). The soil and leaf Si concentrations for the se cond experiment are give n in Figure 3-3. The soil Si concentrations of treat ments containing 1.92 MT Si ha-1 and 1.92 MT Si ha-1 plus 2000 mg Si kg-1 were not significantly different from each other (Figure 3-3 A). The average soil Si concentration of the 1.92 MT Si ha-1 and 1.92 MT Si ha-1 plus 2000 mg Si kg-1 treatments were 387% greater than the control treatment. The average leaf Si concentration of the 1.92 MT Si ha-1 plus 2000 mg Si kg-1 treatment was 43% greater than the 2000 mg Si kg-1 foliar treatment and 76% gr eater than the 1.92 MT Si ha-1 treatment (Figure 3-3 B). No significant differ ences in average leaf Si concentration were observed among the other treatments. Dicotyledonous plants might take advantage of the benefits that Si provides against many biotic and abiotic stresses (30,153). In both experiments, soybean plants accumulated relatively high amounts of Si in the leaves. Although soybean is non-rejective for Si uptake (179), the results for leaf Si concentration suggest that soybeans freely translocated Si to the shoot from the substrate or soil. Miyake and Takahashi (1985) observed in hydroponic culture that depending on Si concentration and the period of Si supply, soybean Si leaf c oncentrations ranged from 0.01 to 18 mg kg-1. These values are in agreement with the aver age leaf Si values in found in our studies (Figure 3-2 B a nd Figure 3-3 B). ASR disease The ASR progress curve and AUDPC plus r parameter for the first experiment are presented in Figure 3-3 and Ta ble 3-4 (Appendix C). The ASR di sease progress for the second

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55 experiment is presented in Figure 3-5. The AUDPC and r parameter for the second experiment are presented in Table 3-4. An average delay of three days for disease ons et was observed with the soil Si treatments, in both experiments (Figure 3-4 A and Figure 3-5 A), and for the foliar Si treatment (2000 mg Si kg-1) of the second experiment as compared with the DI water spray treatment (Figure 3-5 B). However, no delay on disease onset was observed for foliar Si spray treatments in the first experiment (Figure 3-4 B). Higher soybean leaf Si concentrations may have reduced the penetration of P. pachyrhizi urediniospores and increased its incubation pe riod. The plant Si defense mechanism may be through a Si physical barrier, as reported by Yoshida et al. (1962), who described a double Si layer beneath the cuticle of Si amended rice l eaves and sheaths. This subcuticular Si layer appears to be more prominent when plants absorb Si from the environment via their roots (144). Foliar Si applications are likely less effective in cr eating a lasting Si layer beneath the leaf cuticle and were found not to be as effective as the r oot Si application to control powdery mildew ( Blumeria graminis f.sp. tritici ) on wheat (57). However, foliar Si solutions may physically coat the leaf surface where, after drying, restrict urediniospore germination and consequently, ASR development. Another mechanism proposed to explain the ro le of Si in plant disease resistance is increasing concentrations of phytoalexins compounds, thereby reducing pathogen activity (9,46,147). Together with the Si physical barr ier, the production of plant defense compounds mediated by soluble Si may reduce plant disease damage. However, in a recent study of the soybean-ASR pathosystem, it was found that although foliarly applied KSi treatments reduced ASR severity no increase in the activity of the plant defense enzymes was detected (136).

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56 The lime (8 MT ha-1) and KOH foliar treatments were intended to discriminate pH effects from Si effects in ASR control. The AUDPC for these treatments were significantly greater than the AUDPC for soil and foliar Si treatments (Table 3-3 and 3-4), indicating that Si concentration in soybean leaves was probably the main vari able accounting for changes in ASR development in both experiments. The AUDPC expresses the dynamic of plant diseas e progress over time as a single value calculated simply by integrating disease severity between two tim es. It is a simple approach for analysis of plant disease and is useful for evaluating different treatment effectiveness and strategic decisions on disease cont rol (76). Higher leaf Si concentrations were associated with reduced ASR development, as shown by the lowe r AUDPC with those treatments (Table 3-3 and 3-4). The AUDPC of treatments including Si amendments (0.96, 1.92 MT Si ha-1 and 500, 1000, 2000 mg Si kg-1) were not significantly different from each other, but significantly different from treatments that did not include Si (0 MT Si ha-1, lime, and KOH pH adjusted solution), in the first experiment (Table 3-3 and 3-4). The lowest AUDPCs observed in the first experiment were for the 1.92 MT Si ha-1 and 2000 mg Si kg-1, treatments, which were 116 and 166% lower than the control treatment (0 MT Si), respectively. The low AUDPC of the DI water spray (0 mg Si kg-1) in the first experiment was unexpected, as compared to other non-Si treatments. Similar AUDPC results for Si treatments were observed in the second expe riment (Table 3-4). No significant AUDPC differences were observe d among the 1.92 MT Si ha-1, 2000 mg Si kg-1, and the combined treatments (1.92 MT Si ha-1 plus 2000 mg Si kg-1), but their AUDPC values were significantly lower compared with treatments not treated with Si (0 MT Si ha-1, lime, DI water spray and pH adjusted solution) (Table 3-4).

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57 For polycyclic diseases, such as ASR the rate of disease progress ( r parameter) was estimated to be more consistent and accurate with the Gompertz (dy/dt=rGy[ln(1)-ln(y)]) model rather than with the Logistic [dy/dt= rLy(1-y)] model (11,137,192). Also, the Logistic model allowed for considerable misinterpretation of epidemic rates for low disease proportions, especially due to the symmetric curvilinearity of the absolute rate of disease increase (dy/dt) over time (11,12). The Gompertz model was used to calculate the r parameter for disease progress (11). This model generally fitted well for all treatments in both greenhouse experiments (Appendix C). Even with the second P. pachyrhizi inoculation, no significant differences were observed among the r parameters for all treatments in the first experiment (Table 3-3). Significantly higher values for the r parameter were observed for Si treatments in the second experiment (Table 3-4). The greater r parameter for Si treatments may be a consequence of the delay on disease onset, since the r parameter should be greater for those treatments with delayed disease onset, since the disease assessment time was the same and the final disease severity was similar to all treatments in the second experime nt. At around 14 days afte r inoculation (DAI), the disease progression rate of the Si treatments increased (Figure 3.5) until these treatments obtained the same severity as the non-Si treatments ( 19 DAI). These results suggest that the effects of Si in control of ASR might be restricted to th e initial period of infection. Conclusions The time delay for ASR onset with Si treatments, together with the higher AUDPC of the non-Si treatments, indicated that Si may ha ve affected urediniospore germination and consequently, disease development. The effects of Si treatments on AUDPC of ASR showed that Si applications, whether soil or fo liar, were not significantly differe nt, and regardless of tested Si application rates, but all AUDPC values were sign ificantly lower than non-Si treatments. The use of Si amendments may significantly reduce ea rly ASR development but these experiments

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58 suggest that Si alone ca nnot effectively control ASR. Further studies are needed to determine if Si in combination with fungicides might decr ease fungicide rate or application frequency requirements. The use of Si amendments, such as wollastonite and potassium silicate, is an environmentally friendly strategy for sustaina ble crop production. Add itional research with silicate amendments in combination with organi cally-approved products like copper sulfate, need to be evaluated. Including Si in plant disease management stra tegies may well reduce the number of costly fungicide treatments and optimize c ontrol practices in loca tions where soil Si is inherently low. In this study, the initial Ultisol Si concentration was 29 mg kg-1 and the control treatment had the highest AUDPC among all treatments. These findings suggest that the Ultisol might benefit from Si applications in order to lessen ASR development. Both, organic and commercial soybean production systems might benefit by a delay in ASR onset, thereby increasing the time for farmers to implement othe r strategies to moderate an ASR epidemic.

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59 ControlLime0.961.92WaterpHKOH50010002000 Leaf mass (g) 0 2 4 6 8 10 Roundup-ready soybean cultivar Forage soybean cultivar Treatments ControlLime1.92WaterpHKOH20001.92+2000 0 2 4 6 8 10 B Figure 3-1. Effects of soil and foliar applied Si on Roundup Ready and forage soybean cultivar leaf mass, with standard deviation of mean bars. A) Leaf mass in the first experiment at 69 DAP. B) Leaf mass of the roundup -ready soybean cultivar in the second experiment at 34 DAP. Treatme nts: control (0 MT Si ha-1), lime (8 MT ha-1), 0.96 (0.96 MT Si ha-1), 1.92 (1.92 MT Si ha-1), water (DI water), pHKOH (pH10.4), 500 (500 mg Si kg-1), 1000 (1000 mg Si kg-1), 2000 (2000 mg Si kg-1), 1.92+2000 (1.92 MT Si ha-1 plus 2000 mg Si kg-1).

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60 Treatments ControlLime0.961.92WaterpHKOH50010002000 Leaf Si (dag kg-1) 0.0 0.2 0.4 0.6 Soil Si (mg kg-1) 0 20 40 60 80 100 Roundup-ready soybean cultivar Forage soybean cultivar BA Figure 3-2. Soil Si concentra tion and leaf Si concentration at 69 DAP for the roundup-ready and forage soybean cultivar in the first experime nt, with standard error of mean bars. A) Soil silicon concentration (0.5 N acetic acid (CH3COOH) extractant solution). B) Foliar silicon concentration (E lliot and Snyder, 1991). Treatments: control (0 MT Si ha-1), lime (8 MT ha-1), 0.96 (0.96 MT Si ha-1), 1.92 (1.92 MT Si ha-1), water (0 mg Si kg-1), pHKOH (pH10.4), 500 (500 mg Si kg-1), 1000 (1000 mg Si kg-1), 2000 (2000 mg Si kg-1).

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61 Soil Si (mg kg-1) 0 20 40 60 80 100 120 140 160 180 A Treatments ControlLime1.92WaterpHKOH20001.92+2000 Leaf Si (dag kg-1) 0.0 0.1 0.2 0.3 B Figure 3-3. Soil Si concentration and leaf Si concentration at 34 DAP in the second experiment, with standard deviation of mean bars. A) Soil silicon concentration (0.5 N acetic acid (CH3COOH) extractant solution). B) Foliar silicon concentration (Elliot and Snyder, 1991). Treat ments: control (0 MT Si ha-1), lime (8 MT ha-1), 1.92 (1.92 MT Si ha-1), water (0 mg Si kg-1), pHKOH (pH10.4), 2000 (2000 mg Si kg-1), 1.92+2000 (1.92 MT Si ha-1 plus 2000 mg Si kg-1).

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62 10 15 20 25 30 Disease severity (%) 0 2 4 6 Water pHKOH 500 mg kg-1 SiO2 1000 mg kg-1 SiO2 2000 mg kg-1 SiO2 Days after inoculation 0 2 4 6 Control Lime 0.96 MT Si ha-1 1.92 MT Si ha-1 A B Figure 3-4. Disease progress of Asian soybean rust with standard deviation of mean bars, in the first experiment. A) Soil Si treatmen ts and Si untreated control and lime (8 MT ha-1) treatment. B) Foliar Si treatments and Si untreated water spray and pH adjusted (pH10.4, KOH) solution treatment The foliar Si treatments were applied the day before inoculation with uredinio spores and 8 days after inoculation.

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63 Days after inoculation Disease severity (%) 0 5 10 15 20 Control Lime 1.92 MT Si ha-1 68101214161820 Disease severity (%) 0 5 10 15 20 Water pHKOH 2000 mg kg-1 SiO2 1.92 MT Si ha-1 + 2000 mg kg-1 SiO2 A B Figure 3-5. Disease progress of Asian soybean rust with standard deviation of mean bars, in the second experiment. A) 1.92 MT Si ha-1, Si untreated control and lime (8 MT ha-1) treatment. B) 2000 mg Si kg-1, combined treatment (1.92 MT Si ha-1 plus 2000 mg Si kg-1), Si untreated water spray a nd pH adjusted (pH10.4, KOH) solution treatment. The foliar Si treatm ents were applied the day before the urediniospore inoculation and at 4 and 9 days after inoculation.

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64 Table 3-1. Substrate pH values and extractable Ca and Mg in treatments of the first experiment at 69 DAP. Soil Ca Soil Mg Treatment Soil pH (kg ha-1) (kg ha-1) Control (0 MT Si ha-1) 6.7 cdz6310 d 456 b 0.96 MT Si ha-1 7.4 b 6556 c 465 ab 1.92 MT Si ha-1 7.7 a 7179 a 481 a Lime (8 MT ha-1) 7.5 b 6888 b 458 ab 0 mg Si kg-1 6.8 c 6289 d 456 b 500 mg Si kg-1 6.6 d 6325 d 455 b 1000 mg Si kg-1 6.7 cd 6344 d 461 ab 2000 mg Si kg-1 6.8 c 6348 d 465 ab pH KOH (pH10.4) 6.7 cd 6274 d 464 ab z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test. Table 3-2. Soil pH extractable Ca and Mg in treatments of the second experiment at 34 DAP. Soil Ca Soil Mg Treatment Soil pH (kg ha-1) (kg ha-1) Control (0 MT Si ha-1) 6.7 bz2435 b 229 a 1.92 MT Si ha-1 7.5 a 3112 a 235 a Lime (8 MT ha-1) 7.4 a 3144 a 234 a 0 mg Si kg-1 6.7 b 2604 b 245 a pH KOH (pH10.4) 6.7 b 2721 b 240 a 2000 mg Si kg-1 6.7 b 2623 b 249 a 1.92MT Si ha-1 + 2000 mg Si kg-1 7.4 a 3110 a 236 a z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test.

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65 Table 3-3. Integrated area under disease progre ss curve (AUDPC) for treatments of the first experiment during 20 days of disease evaluation. Treatment AUDPC r parameter Control (0 MT Si ha-1) 49.3 az0.0402 a 0.96 MT Si ha-1 25.3 b 0.0370 a 1.92 MT Si ha-1 22.8 b 0.0349 a Lime (8 MT ha-1) 53.3 a 0.0437 a 0 mg Si kg-1 31.5 b 0.0382 a 500 mg Si kg-1 32.9 b 0.0407 a 1000 mg Si kg-1 31.1 b 0.0385 a 2000 mg Si kg-1 18.5 b 0.0326 a pH KOH (pH10.4) 50.8 a 0.0414 a z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test. Table 3-4. Area under disease progress curve (AUDPC) values and rate parameter from Gompertz model for treatments of the s econd experiment during 15 days of disease evaluation. Treatment AUDPC r parameter Control (0 MT Si ha-1) 86.6 az 0.0900 b 1.92 MT Si ha-1 55.4 b 0.1177 a Lime (8 MT ha-1) 85.4 a 0.0956 b 0 mg Si kg-1 83.1 a 0.0956 b 2000 mg Si kg-1 58.1 b 0.1164 a 1.92MT Si ha-1+2000 mg Si kg-1 54.4 b 0.1217 a pH KOH (pH10.4) 85.4 a 0.0937 b z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test.

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66 CHAPTER 4 EFFECTS OF SOIL AND FOLIAR APPL IE D SILICON ON ASIAN SOYBEAN RUST DEVELOPMENT UNDER FIELD CONDITIONS Introduction Phakopsora pachyrhizi Sydow, 1914, is the causal agent of Asian soybean rust (ASR), a devastating foliar fungal disease (135 ). Severe ASR damage on soybean [ Glycine max (L.) Merr.] is a consequence of wi ndborne urediniospores and se vere pathology under certain environmental conditions (58,59,73,129). A minimu m of a 6-hour dew peri od and temperatures ranging from around 15 to 29 C are normally necessary for urediniospore infection (91,108,118,129). Approximately seven days after in fection, ASR pustules (uredinia) start to emerge from the abaxial soybean leaf surface. Infection causes reductions in photosynthetic area, premature defoliation, and early plant maturation that together result in considerable yield reductions (86,162,175). Fewer pods, poor seed quality, and lower protein values were observed on soybean plants severely affected with ASR (18,133). Currently, there is little soybean cultivar re sistance to ASR so the short-term option to manage an ASR epidemic is through the applicati on of costly fungicides, such as triazoles and strobirulins. However, in years of high ASR pressure, yield reductions of approximately 50% were observed, even with chemical control ( 198). Another approach to lessen plant disease effects and to reduce the extensive use of fungici des is through nutrient management strategies. Since mineral nutrition plays an important role in the physiological func tioning of plants, it can be an important component in the overall mana gement of plant diseases (110). Studies have reported the positive effects of amendments containing Si for improving biotic stress resistance (disease and insects), and increasing plant tolerance against abiotic disturbances (30,44,45,94,96,100).

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67 The mechanisms involving Si in plant disease re sistance are considered to be related to an accumulation of absorbed Si in the epidermal tis sue (physical barrier) and/or an expression of pathogenesis-induced host defense response (physi ological barrier) (26). Yi eld gains in plants supplied with Si have been associated with se veral factors, such as increased plant growth, improved mineral nutrition balance, and mechanical strength, which result in resistance to various environmental stresses (30, 153). Increased plant Si content is directly associated with higher yields for Si accumulating plants, such as rice ( Oriza sativa ), wheat (Triticum aestivum) and sugarcane (Sacharum sp.) (28,42,78,153). Three types of Si uptake (active, passive and rejective), based on uptake rate relative to water are used to explain the large range (typically between 1 to 100 g kg-1) of Si concentrations found in different plant species (103,179). Soybeans have passive Si uptake (uptake rate of Si and water are sim ilar) and usually do not have Si concentrations beyond 5 g kg-1. Fertilization with Si reduced fungal disease susceptibility for a number of monocotyledonous and several dicotyledonous pl ant species (30,77,78,93,119,179). Rice fields amended with Si suppressed th e incidence of neck blast ( Magnaporthe grisea ), thereby considerably reducing or eliminating the need for fungicides (156,157,158). The application of foliar Si sprays reduced the number of powdery mildew (Uncinula necator ) colonies on grape ( Vitis vinifera ) leaves and considerably increased yiel d (15,142). It was shown using scanning electron microscopy and energy-dispersive X-ray imagery that large quantities of Si were deposited near the infection sites, suggesting that grape fruit may utili ze endogenous Si to control disease (142). In greenhous e studies with cucumber ( Cucumis sativus), soluble potassium silicate, K2SiO3, applications showed positive correlations with powdery mildew ( Sphaerotheca fuliginea ) resistance (8,120). Liang et al (2005), found root or folia r Si applications reduced

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68 disease severity and enhanced the activity of pathoge nesis-related proteins in cucumber. The same effect on protein activity wa s not observed for foliar Si applic ations, indicating that disease control promoted by the foliar trea tments was likely a physical eff ect of the Si being deposited on the leaf surface and/or an osmotic or pH eff ect of the Si solutions on the leaf surface. Studies evaluating nutrient t oxicity (Al and Mn) and physiological effects have shown that soybean responds positively to Si amendments (7,84,95,128). The use of potassium silicate sprays against ASR on soybean was tested with considerable success, with ASR severity reduction of up to 70% (130,145). In comparison, Nolla et al ., (2006) reported that soil Si applications reduced the incidence of frog eye (Cercospora sojina) and downy mildew ( Peronospora manshurica ) in soybean but it was less effective on ASR. Considering that Si amendments might suppr ess ASR development in soybean, especially for organic farmers, the objective of this study wa s to evaluate the efficacy of soil and foliar Si applications on soybean resistan ce to ASR under field conditions. Materials and Methods Treatments The field experiment was conducted in 2007 (J uly to November) a nd repeated in 2008 (July to November) at North Florida Research an d Education Center (30.54 Lat, -89.60 Long), in Quincy, FL. Temperature and rainfall daily av erages for both years are presented in Appendix D. The average daily temperature for July, August, and September (months for disease and treatment efficacy evaluations) was 26.4, 27.5, 25 C and 26.7, 25.5, 24.1 C, respectively, for 2007 (year 1) and 2008 (year 2). The largest diffe rence in average rainfall was observed for August, where 2007 received 8.3 mm and 2008 re ceived 43.4 mm (47). However, irrigation (traveling gun) was used in 2007 to alleviate mois ture stress. Two soybean cultivars were tested,

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69 a Roundup-ready (RR) soybean (DP 5634RR, maturi ty group 5), and a forage soybean (FS), cultivar Hinson Long Juvenile (maturity group 8), which has hi gh foliage production. The plot area used for year 1 was comprised of two similar soil series with 60% being a Tifton fine loam (fine-loamy, kaolinitic, thermi c Plinthic Kandiudult), and 40% being a Norfolk fine loam (fine-loamy, kaolinitic, thermic Typic Kandiudult). The prim ary difference between series was that Tifton had plinth ite in the B horizon. The plot ar ea used for the second year was a Norfolk series soil (168). Both areas had a long hi story of agricultural use previous to these experiments. Both fields received conventional commercial soybean cultural practices, including soil fertilization, insecticide and herbicide sprays, cultivation, and overhead irrigation, as needed. Each experimental plot (22.2 m2) was comprised of four 6.1-m rows with 0.91 m between rows. Alleys (1.8 m) separated treatment plots. Thirty soybean seeds were sown per linear meter. Wollastonite is a naturally occurring CaSiO3 mineral ore that was the Si source for this study. Vansil W-50 (Vanderbilt Comp. Norwalk, CT) is a fine grade (median diameter: 2.8 m) talc-like wollastonite product containing ap proximately 24% Si a nd 34% Ca as CaSiO3, with a pH 10-11 (10% slurry). Vansil was spr ead by hand and raked into the upper 5 cm of soil in field plots at 0, 4.44, 8.88 and 17.76 kg plot-1 (0.0, 0.48, 0.96 and 1.92 MT Si ha-1) one day prior to sowing in year 1 and six days prior to sowing in year 2. Additionally, a Ca (lime) control treatment was applied at 9.6 kg Ca plot-1 (8 MT lime ha-1). The hydrated lime [Ca(OH)2] had a pH of 12.4 (saturated solution at 25C, Cheney Lime & Cement CO. Allgood, AL). The calcium oxide equivalencies of the wollastonite and hydrated lime were 440 and 760 g kg-1 CaO, respectively.

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70 Foliar Si applications were also tested using potassium silicate, K2SiO3 (KSi), as AgSil 25 (PQ Corp. Valley Forge, PA), at pH 11.3. Ag Sil 25 is a readily soluble Si source containing approximately 9.7% Si. A backpack sprayer (D.B Smith Field King, Mills, NY) was used to apply KSi solution treatments. Four rates of KSi were applied, 0, 500, 1000, 2000 mg Si kg-1 (pH 7.2, 10, 10.1, and 10.4, respectively). The centr al row of each plot was sprayed with the KSi solutions until runoff at 1.1 L plot-1, which was proportional to 1000 L ha-1. The control solution (0 mg Si kg-1) was applied as deionized (DI) water. A control solution with pH adjusted with KOH was also tested (pH 10.4). All foliar treatments were applied three times, at 39, 53, and 67 days after planting (DAP) for y ear 1, and at 29, 42, and 53, DAP for year 2. The foliar Si applications were applied at the V5 (fully expanded fifth trifoliate), R2 (full bloom) and R3 (beginning pod) soybean physiolo gical stages, respectively. Inoculum Production Due to low rainfall in year 1 (which was not conducive for natural ASR infection) the plots were artificially inoc ulated at 47 DAP (evening). To produce the inoculum, P. pachyrhizi urediniospores, were removed from plants cultivated in the greenhous e using leaves with approximately 35% diseased area (7 0). Excised leaves were gently washed with deionized water and blotted dry with absorbent paper towel. Subs equently, the leaves were placed in a sealed transparent plastic box containing Whatman No 1 filter paper (Whatm an. Piscataway, NJ) saturated with DI water. After 48 hr incubation at 23 oC, fresh urediniospores were collected with a brush and placed into a 0.05% surfactan t solution (Tween-20, Sigma Co., Saint Louis, MO). A hemacytometer was used to adjust the urediniospore concentration to 33 spores mL-1. The urediniospore suspension (1.1 L plot-1) was sprayed with a backpack sprayer (D.B. Smith Field King Mills, NY).

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71 Measurements and Sampling Disease severity ratings were determined with the Horsfall-Barrett scale (70). The two central rows of each plot were used for disease data collection, thereby avoiding border effects. Five ASR infection evaluations were conducted from 8 September through 6 October 2007, and seventeen evaluations were conducted from 13 August through 16 September 2008. Disease evaluations were used to generate the rate (r ) parameter and create disease progress curves. The r parameter is related to the best fit disease pr ogress model by expressi ng the rate of disease change as a specific function of time (21). Th e area under the disease progress curve (AUDPC) determined treatment effectiveness and was calculated as: AUDPC = ii n i iittyy 1 1 1 12, where yi = disease proportion (percentage severity) at the ith observation; ti = time (days); n = total number of observations (156,159). At soybean development stage R7 (80 and 101 DAP for RR and FS, respectively in year 1, and 84 and 98 DAP for RR and FS, respectively in year 2), six randomly collected plants from each plot were taken for dry mass determination and leaf Si analysis. Dried leaf samples were ground and sieved through a 2 mm st ainless steel screen. Leaf Si concentration was determined following the methodology described by Elliott and Snyder (1991). Briefly, 0.1 g ground tissue was digested with 2 mL of NaOH (1:1, NaOH:H2O) plus 3 mL of H2O2 (30% solution) and autoclave-digested in three cycles of 20 minutes each 3 mL of H2O2 (30% solution) was added to the digest every autoclave cycle. The digest was cooled and 47 mL of DI water was added; after 30 minutes 0.1 mL of the digest solution received 0.25 mL HCl (1:1, HCl:H2O), 0.5 mL ammonium molybdate solution (100 g of (NH4)6Mo7O24 L-1, at pH 7.0), 0.5 mL tartaric acid (200

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72 g of C4H6O6 L-1), and sodium bisulfite (50 g of NaHSO3 L-1) Once a blue color developed it was read using an automated colorimetric analysis at 650 nm. At the conclusion of each experiment air-dried soils were sent to the University of Florida, Belle Glade EREC soil test laboratory to quantify soil Si, Ca, and Mg. Briefly, plantavailable soil calcium (Ca), magnesium (Mg) a nd Si were determined with a 0.5 N acetic acid extractant (10:25 v/v soil:HOAc) followed by atomic absorption spectrophotometry at wavelengths of 422.7, 285.2 and 650 nm (152). So il pH (1:2 v/v) was determined on air-dried samples. When the plants reached full maturity the plot s were harvested to determine seed yield, weight of 100 seeds and seed quality, at the conclusion of each experiment year (111 and 103 DAP, respectively). Seed quality was based on a visu al scale from 1 to 5, where equated to undamaged seeds and re presented the most damaged seeds (Appendix E). Statistical Analyses Each experiment was a 2 factorial desi gn with two soybean cultivars, ten Si treatments, and four replications (n=80). An alysis of variance (ANOVA) was used (PROC ANOVA) to determine significant treatment e ffects (SAS for Windows, version 9.1. SAS Institute, Cary, NC). The means were compared ( P 0.05) with Fishers Protected Least Significant Difference (LSD). SigmaPlot software (SigmaPlot v. 10.0. Hearne Scientific Software. San Rafael, CA) was used to estimate regressions and to compare Si rate effects. Results and Discussion Soil and Tissue Composition The initial (prior to treatments) soil water pH, extractable Ca and Mg and 0.5 N HOAcextractable Si (Elliot and S nyder, 1991), were 6.7, 2436 kg ha-1, 239 kg ha-1, and 38 mg kg-1, respectively for year 1. Values for year 2 were 6.7, 583 kg ha-1, 212 kg ha-1, and 30 mg kg-1 for

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73 pH, Ca, Mg, and Si, respectively. Since no si gnificant differences were observed between cultivars for soil pH and Si, the data were pooled (Table 4-1). Treatments receiving wollastonite or lime generally had greater soil pH than those without amendments. Soil Si concentrations of the 1.92 MT Si ha-1 treatment was much greater than control treatments, i.e. 363 and 464%, respectively for year 1 and year 2. There were no significant differences between the control soil Si concentration and the five foliar treatme nts (KOH control, 0, 500, 1000 and 2000 mg Si kg-1) for either year. Extractable soil Ca increased in treatments receiving wollastonite or lime (Table 4-2). The Ca concentration of the lime (8 MT ha-1), 0.96 and 1.92 MT Si ha-1 treatments were 62%, 25%, and 35% greater than the control treatment for year 1 and 595%, 71%, and 253%, greater than the control treatment for year 2. The soil Ca concentration of the 0.48 MT Si ha-1 treatment was not significantly different from the control treatment in either years. The greater initial Ca concentration (2436 MT Ca ha-1) in year 1 might be due to residual Ca from lime applications of previous experiments that were conducted at this field site. The average extractable soil Mg increased for the lime treatments (Table 4-2). The extractable Mg concentrations of lime treatmen ts were 133% and 31% greater than the control treatment for year 1 and year 2, respectively. The Si applications did not appear to affect plantavailable soil Mg. Although the amount of Mg in the wollastonite source was about 0.9% (1.5% MgO), no considerable increases in soil Mg were measured. Soybean Dry Biomass Measurements There were no significant Si effects in soybean dry bioma ss (leaf, pod, stem, and root) among the treatments for either year (ANOVA Tabl es in Appendix F). Others (84,128) observed similar results where different Si treatments had no effect on soybean growth, particularly during early physiological growth stages. In year 1, the FS cultivar had 47% greater stem dry mass and

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74 36% greater root dry mass than the RR cultivar, but no differences were observed for dry leaf or dry pod mass. In year 2 the FS cultivar stem dr y mass was 50% greater, and the root dry mass was 16% greater than the RR values. There was a cult ivar Si treatment interaction, resulting in a 71% increased dry pod mass for the FS cultivar as compared to RR. There was an additional cultivar Si treatment for leaf dry mass wher e the leaf dry mass was 17% greater for the RR cultivar than for the FS cultivar. The results for dry leaf mass from both years suggested that the FS cultivar may be more resistant to drought cond itions (Appendix E, Figure E-1 A and C) than the RR cultivar, which performed relatively bett er (i.e., leaf production) in years of higher rainfall. The leaf Si concentration of both years ar e found in Figure 4-1. The average leaf Si concentration for the FS soybean cultivar was 56% greater than for the RR cultivar, in both experiments. The Si leaf concentration increase d as the leaves aged since Si accumulates as a result of the transpiration stream, and transp ort mediated, as reporte d in rice (102). The differences in leaf Si concentration between th e soybean cultivars might be related to possible differences in transpiration rates. This has not been determined. Another possibility is that at harvest, the FS cultivar had less low canopy leaf drop than the RR soybean. Therefore, FS kept more of its older, high Si content leaves than the RR cultivar. This preliminary data warrants additional research into cultivar variability in Si accumulation. No significant differences were observe d between the treatments 1.92 MT Si ha-1 and 2000 mg Si kg-1, or among the 0.96 MT Si ha-1, 500 mg Si kg-1 and 1000 mg Si kg-1 treatments over the two years. Leaf Si con centration from the 0.48 MT Si ha-1 treatment was the lowest among the Si treatments over both years. No significant differences were observed among treatments not receiving Si (0 MT Si ha-1, 8 MT lime ha-1, 0 mg Si kg-1 and pH KOH). In both

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75 experiments, soybean plants accumulated relatively high amounts of Si in leaves, as compared to the control treatment. Although most of the dico tyledonous plant species ca nnot efficiently take up high amounts of Si, they are still able to ta ke advantage of the bene fits that Si provides against many types of biotic a nd abiotic stresses (30,153). Soybean plants have non-rejective Si uptake (179), and the soybean leaf Si concentratio n results from this study suggest that soybeans freely translocated Si to the s hoot from the soil solution as the Si rates increased. In a hydroponic culture study on soybean growth, Miyake and Takahashi (1985) observed that depending on Si concentration and the period of Si supply, soybean Si leaf concentration ranged from 0.01 to 18 g kg-1. These values are in agreement with the averag e leaf Si concentration reported in this study (Figure 4-1). ASR disease progression An average delay of three days for disease onset was evident (Figur e 4-3) when Si was provided via soil and even more so in year 2 (F igure 4-3 A and C). The foliar Si treatments were less effective on delaying disease onset. The postponement of disease onset caused by th e soil Si treatments is probably due to a reduction in the P. pachyrhizi urediniospores penetration and an increase in incubation period, thus delaying the appearance of the first di sease symptoms (ASR pustules). The mechanism responsible for the delay of ASR onset may be attr ibuted to a Si physical barrier, similar to the double Si layer reported beneath th e cuticle of Si amended rice l eaves and sheaths (196). This subcuticular Si layer appears to be more promin ent when plants absorb Si through by the roots than from a foliar applicati on (144), since foliar Si ab sorption is low. Guvel et al (2007) found that foliar Si applications were not as effectiv e as soil treatments in controlling powdery mildew ( Blumeria graminis f.sp. tritici ) on wheat. However, the applicati on of foliar Si may physically

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76 coat the leaf surface after drying, thereby inhibiting urediniospores germination and consequently, disease development (86). Another mechanism proposed to explain Si medi ated disease resistan ce is that Si can modulate plant resistance within th e plant. Studies of different pa thosystems showed that plants amended with Si increased production a nd accumulation of phytoalexins and phenolic compounds that are toxic to pathogen developmen t (9,46,147). Together with the Si physical barrier, the production of pathogen-toxic compo unds mediated by the presence of soluble Si increase the plants natural defense mechanis ms, thereby reducing disease damage. However, Pereira et al. (2009) reported th at foliar potassium silicate treat ments reduced ASR severity, but did not increase the activ ity of soybean defense enzymes. The f act that greater concentrations of leaf Si retarded ASR onset does not necessarily prove a cause-and-effect relationship between a physical protection and reduced disease. Furthe r studies are necessary to confirm the actual mechanism of soybean resistance ag ainst ASR initial development. The AUDPC is an approach for assessing plant di sease epidemics and is a useful tool for evaluating treatment effectiveness and to develop strategic decisions on disease control (76). The AUDPC and r parameter (model determination in Table 4-3), for both years, are presented in Table 4-4. The lime and KOH foliar treatments we re to discriminate calcium and potassium effects from Si effects on ASR development. Th e AUDPC for these treatments were generally greater than the AUDPC for soil or foliar Si treatments (Table 4-4) indicating that it was the Si in soybean leaves that was the major variable accounting for effects on ASR development. In both years, the 1.92 MT Si ha-1 and 2000 mg Si kg-1 treatments displayed the lowest AUDPC values among all treatments (Tab le 4-4), while the non-Si treatments resulted in the highest

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77 AUDPC values. In year 1, only the 1.92 MT Si ha-1 had lower AUDPC than some of the other Si treatments. However, in year 2 higher Si rates led to significantly less disease (Table 4-4). According to Plaut (1980) and Berger (1981) the estimation of the rate of disease progress ( r parameter) is more consistent and accurate for polycyclic diseases with the Gompertz (dy/dt= rGy[ln(1)-ln(y)]) model than with the Logistic (dy/dt= rLy(1-y)) model (192). The Logistic model can be quite biologically restrictive due to the symmetric curvilinearity of absolute rate of disease increase (dy/dt) over time, allowing misint erpretation of epidemic rates for low disease proportions (11,12). The Gompertz model (11) was used to calculate the r parameter since it was the model that gave the best treatment fit (Table 4-3) in both years (21). No signi ficant differences were observed among the r parameters for all treatments in year 1 (Table 4-4), whic h was less prone to disease development due to lower rainfall, when compared to year 2. In year 2, the lowest r parameter was observed for the 2000 mg Si kg-1 treatment. The r parameter of the lime, KOH, 0, 500 and 1000 mg Si kg-1 treatments were not significantl y different from one another. No differences were observed between cultivars for r parameter. Significantly higher values for the r parameter were observed for treatments receiving soil Si amendments in year 2 (Table 4-4). The greater r parameter of the soil Si treatments may be an effect of the delay on disease onset, once the disease assessment started when the disease was first detected in field, on control treatments. No disease was observed on the soil Si treatments, consequently, the r parameter should be greater for those treatments that started di sease later because the time length for disease assessment was the same and the final disease severity was similar for all treatments. Soybean yield Table 4-5 shows the results for seed quali ty, 100 seed weight a nd crop yield for both experiments. The differences were minimal betw een Si treatments and non-Si treatments for seed

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78 quality, 100 seeds weight and crop yield. Due to the fact that no fungici de applications were applied to control ASR infection, the diseas e freely developed under fi eld conditions, reaching high severity by the time of harvest. Under high ASR disease pressure, Si use may not be appropriate. Since Si delayed disease onset, combining Si with more conventional fungicidal treatments should be studied (24,157). Conclusions Soil Si treatments were generally more able to slow ASR development, especially at the initial stages of the epidemic, possibly by affecting urediniospore germination and/or penetration. The lower AUDPC gene rally observed for Si treatments (soil or foliar) as compared with non-Si treatments, also indicat ed that Si treatments affected disease development. The lack of consistent results between Si treatments a nd non-Si treatments for seed quality, 100 seed weight and crop yield indicated that Si alone may not effectively control ASR under normal field conditions found in Florida. Fertilization with Si amendments, such as wollastonite and potassium silicate, are considered to be environment friendly stra tegies for sustainable crop production. However, further research that includes Si application timi ngs and/or combinations of Si amendments with other organic approved products, lik e copper sulfate, need to be tested for control of ASR, particularly in organic production agriculture. A combination of disease control strategies may be the best approach to reduce the number of fu ngicide applications (red uced costs) and optimize control practices, even in conventionally managed fields. In either production system (organic or conventional), the use of Si amendments ma y delay ASR onset thereby increasing the time soybean farmers have to implement additional ASR control strategies.

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79 Treatments 12345678910 Leaf Si (%) 0.0 0.1 0.2 0.3 0.0 0.1 0.2 0.3 Roundup-ready soybean cultivar Forage soybean cultivar B A Figure 4-1. Leaf Si concentration at the R7 (beginning maturity) soybean physiological stage, with standard deviation of mean bars. A) Year 1. B) Year 2. Tr eatments: 1 (0 MT Si ha-1), 2 (8 MT lime ha-1), 3 (0.48 MT Si ha-1), 4 (0.96 MT Si ha-1), 5 (1.92 MT Si ha1), 6 (DI water), 7 (pH10.4), 8 (500 mg Si kg-1), 9 (1000 mg Si kg-1), 10 (2000 mg Si kg-1).

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80 55606570758085 55606570758085 0 10 20 30 40 50 Water pH KOH 500 mg kg-1 Si 1000 mg kg-1 Si 2000 mg kg-1 Si Days after sown Disease severity (%) 0 5 10 15 20 25 30 Control Lime 0.48 MT Si ha-1 0.96 MT Si ha-1 1.92 MT Si ha-1 A B C D Figure 4-2. Disease progress of As ian soybean rust with standard de viation of mean bars, in year 1. A and B) Roundup Ready soybean cultivar. C and D) Forage s oybean cultivar. A and C) Soil Si treatments and Si unt reated control and lime (8 MT ha-1) treatment. B and D) Foliar Si treatments and Si untreate d water spray and pH adjusted (pH10.4, KOH) solution treatment. The foliar Si treatments were applied the 39, 53 and 67 days after soybeans were sown.

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81 Days after sown 25303540455055 Disease severity (%) 0 2 10 15 20 25 30 Control Lime 0.48 MT Si ha-1 0.96 MT Si ha-1 1.92 MT Si ha-1 25303540455055 25303540455055 25303540455055 0 5 10 15 20 25 30 Water pH KOH 500 mg kg-1 Si 1000 mg kg-1 Si 2000 mg kg-1 Si A B C D Figure 4-3. Disease progress of As ian soybean rust with standard de viation of mean bars, in year 2. A and B) Roundup Ready soybean cultivar. C and D) Forage s oybean cultivar. A and C) Soil Si treatments and Si unt reated control and lime (8 MT ha-1) treatment. B and D) Foliar Si treatments and Si untreate d water spray and pH adjusted (pH10.4, KOH) solution treatment. The foliar Si treatments were applied the 29, 42 and 55 days after soybeans were sown. Shadow ing area on soil Si treatments disease progression highlight the disease onset delay for Si treatments.

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82 Table 4-1. Final soil pH and Si concentra tion at 80 and 84 DAP for year 1 and year 2, respectively. Year 1 Year 2 Si Si Treatments Soil pH mg kg-1 Soil pH mg kg-1 Soil (MT Si ha-1) Lime (8 MT ha-1) 7.3 abz 31 d 8.2 a 49 d 0 6.8 cde 32 d 6.6 e 25 e 0.48 6.6 e 48 c 7.2 d 75 c 0.96 7.2 ab 99 b 7.6 c 120 b 1.92 7.5 a 148 a 7.9 b 141 a Foliar (mg Si kg-1) KOH (pH 10.4) 6.7 de 30 d 6.5 e 22 e 0 (DI water) 6.8 cde 34 d 6.5 e 22 e 500 6.9 cd 32 d 6.5 e 24 e 1000 7.0 bc 33 d 6.6 e 26 e 2000 7.0 bc 35 d 6.6 e 25 e z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test. Table 4-2. Final soil Ca and Mg at 80 a nd 84 DAP for year 1 and year 2, respectively. Year 1 Year 2 Ca Mg Ca Mg Treatments ----------------------------kg ha-1 -----------------------------Soil (MT Si ha-1) Lime (8 MT ha-1) 4472 az586 a 4092 a 261 a 0 2763 d 251 cd 589 d 200 bc 0.48 2754 d 252 cd 1005 cd 191 c 0.96 3465 cb 260 cd 1480 c 204 bc 1.92 3747 b 270 bcd 2080 b 239 ab Foliar (mg Si kg-1) KOH (pH 10.4) 2796 d 247 d 698 d 195 bc 0 (DI water) 3068 cd 271 bcd 678 d 197 bc 500 3054 cd 275 bcd 623 d 200 bc 1000 3350 cb 296 cb 714 cd 225 abc 2000 3493 ab 308 b 507 d 197 bc z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test.

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83 Table 4-3. Logistic an d Gompertz model parameters of Asian soybean rust for the 0, 1.92 MT of Si ha-1, 0 and 2000 mg Si kg-1 for the field experiments. Five ASR infection evaluations were conducted during year 1, and seventeen evaluations were conducted during year 2. Year 1 Year 2 Treatments R2 MSEyrzR2MSE r Logistic model 0 MT Si ha-1 0.93 0.01411 0.20592 0.93 0.01714 0.14360 1.92 MT Si ha-1 0.97 0.00288 0.24924 0.91 0.04873 0.23183 0 mg Si kg-1 0.91 0.01031 0.18754 0.91 0.02401 0.14195 2000 mg Si kg-1 0.97 0.00288 0.24924 0.85 0.02692 0.13553 Gompertz model 0 MT Si ha-1 0.99 0.00072 0.05418 0.95 0.00633 0.04295 1.92 MT Si ha-1 0.98 0.00059 0.05301 0.97 0.00581 0.05702 0 mg Si kg-1 0.99 0.00046 0.04485 0.96 0.00598 0.04366 2000 mg Si kg-1 0.98 0.00059 0.05301 0.94 0.00503 0.03840 y Mean Square Error z rate of disease progress

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84 Table 4-4. Area under disease progress curv e (AUDPC) values and rate parameter ( r ) from Gompertz model for both experiments. Year 1 Year 2 Treatment AUDPC r AUDPC r Soil (MT Si ha-1) Lime (8 MT ha-1) 280 abcz0.0524 a 387 c 0.0453 de 0 315 a 0.0538 a 384 c 0.0444 e 0.48 214 ed 0.0520 a 357 d 0.0512 c 0.96 227 cde 0.0539 a 340 e 0.0551 b 1.92 181 e 0.0527 a 324 f 0.0581 a Foliar (mg Si kg-1) KOH (pH 10.4) 295 ab 0.0563 a 417 ab 0.0469 d 0 (DI water) 297 ab 0.0570 a 418 a 0.0454 de 500 247 bcd 0.0522 a 412 b 0.0464 d 1000 211 ed 0.0563 a 382 c 0.0462 d 2000 189 ed 0.0546 a 337 e 0.0412 f z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test. Table 4-5. Seed quality, cr op yield, and weight of 100 s eeds for year 1 and year 2. Year 1 Year 2 Seed Qualityy 100 seeds (g) Yield (kg ha-1) Seed Quality 100 seeds (g) Yield (kg ha-1) Treatment Soil (MT Si ha-1) Lime (8 MT ha-1) 3.6 az 10.6 a 2305 a 2.6 abc 10.4 a 1789 ab 0 3.1 ab 10.0 abc 1854 cd 3.0 a 9.7 bc 1792 ab 0.48 2.6 c 9.4 bc 2239 ab 2.4 bcd 9.4 c 1757 ab 0.96 3.0 ab 10.4 a 2267 ab 2.4 bcd 9.6 bc 1871 ab 1.92 3.0 ab 9.39 c 2156 abc 2.1 d 9.9 abc 1831 ab Foliar (mg Si kg-1) KOH (pH 10.4) 3.4 a 10.4 a 2084 abcd 2.3 cd 9.5 bc 1661 b 0 (DI water) 3.1 ab 10.3 ab 1824 d 2.3 cd 9.6 bc 1808 ab 500 3.3 ab 9.9 abc 2116 abcd 2.4 bcd 9.5 bc 1798 ab 1000 3.1 ab 9.5 bc 1983 bcd 2.8 ab 9.9 abc 1847 ab 2000 3.1 ab 9.9 abc 1873 cd 2.4 bcd 10.1 ab 1911 a y Seed quality scale: 1 (health y) through 5 (most damaged). z Results with the same letter within a column do not differ significantly at P 0.05 as determined by the Fishers Protected LSD test.

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85 APPENDIX A SUMMARY TABLE OF THE STATISTICAL ANALYSIS OF SILICON E FFECTS ON PLANT BIOMETRIC MEASUREMENTS AND SOIL ANALYSIS (CHAPTER 2) Table A-1. Stem diam eter, first experiment. The ANOVA Procedure Dependent Variable: Stem Sum of Source DF Squares Mean Square F Value Pr > F Model 71 23.28178571 0.32791247 7.18 0.0003 Error 12 0.54809524 0.04567460 Corrected Total 83 23.82988095 R-Square Coeff Var Root MSE Stem Mean 0.977000 5.130654 0.213716 4.165476 Source DF Anova SS Mean Square F Value Pr > F Soil 1 3.56297619 3.56297619 78.01 <.0001 Source 1 0.00107143 0.00107143 0.02 0.8808 Treat 6 7.78571429 1.29761905 28.41 <.0001 Block 2 0.26023810 0.13011905 2.85 0.0972 Soil*Source 1 1.07440476 1.07440476 23.52 0.0004 Soil*Treat 6 0.62285714 0.10380952 2.27 0.1066 Soil*Block 2 0.00452381 0.00226190 0.05 0.9519 Source*Treat 6 1.78809524 0.29801587 6.52 0.0030 Source*Block 2 0.19785714 0.09892857 2.17 0.1574 Treat*Block 12 3.88142857 0.32345238 7.08 0.0009 Soil*Source*Treat 6 0.53476190 0.08912698 1.95 0.1528 Soil*Source*Block 2 0.14023810 0.07011905 1.54 0.2549 Soil*Treat*Block 12 1.67714286 0.13976190 3.06 0.0320 Source*Treat*Block 12 1.75047619 0.14587302 3.19 0.0275

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86 Table A-2. Leaf area, first experiment. The ANOVA Procedure Dependent Variable: LA Sum of Source DF Squares Mean Square F Value Pr > F Model 71 69971048.88 985507.73 6.99 0.0004 Error 12 1691985.12 140998.76 Corrected Total 83 71663034.00 R-Square Coeff Var Root MSE LA Mean 0.976390 13.72936 375.4980 2735.000 Source DF Anova SS Mean Square F Value Pr > F Soil 1 35108829.00 35108829.00 249.00 <.0001 Source 1 426003.86 426003.86 3.02 0.1077 Treat 6 7570575.50 1261762.58 8.95 0.0007 Block 2 565579.50 282789.75 2.01 0.1772 Soil*Source 1 2718720.76 2718720.76 19.28 0.0009 Soil*Treat 6 5903468.83 983911.47 6.98 0.0022 Soil*Block 2 501249.50 250624.75 1.78 0.2108 Source*Treat 6 1854641.64 309106.94 2.19 0.1165 Source*Block 2 375575.64 187787.82 1.33 0.3004 Treat*Block 12 4031544.50 335962.04 2.38 0.0734 Soil*Source*Treat 6 3858699.74 643116.62 4.56 0.0123 Soil*Source*Block 2 207226.88 103613.44 0.73 0.5000 Soil*Treat*Block 12 2341193.17 195099.43 1.38 0.2913 Source*Treat*Block 12 4507740.36 375645.03 2.66 0.0514

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87 Table A-3. Dry root mass, first experiment. The ANOVA Procedure Dependent Variable: DR Sum of Source DF Squares Mean Square F Value Pr > F Model 71 393.3214286 5.5397384 8.86 0.0001 Error 12 7.5000000 0.6250000 Corrected Total 83 400.8214286 R-Square Coeff Var Root MSE DR Mean 0.981288 13.44833 0.790569 5.878571 Source DF Anova SS Mean Square F Value Pr > F Soil 1 260.7619048 260.7619048 417.22 <.0001 Source 1 24.3219048 24.3219048 38.92 <.0001 Treat 6 13.9147619 2.3191270 3.71 0.0254 Block 2 5.6835714 2.8417857 4.55 0.0339 Soil*Source 1 0.0576190 0.0576190 0.09 0.7666 Soil*Treat 6 16.9047619 2.8174603 4.51 0.0128 Soil*Block 2 4.5430952 2.2715476 3.63 0.0583 Source*Treat 6 15.8947619 2.6491270 4.24 0.0160 Source*Block 2 1.9759524 0.9879762 1.58 0.2458 Treat*Block 12 16.2180952 1.3515079 2.16 0.0980 Soil*Source*Treat 6 2.2857143 0.3809524 0.61 0.7189 Soil*Source*Block 2 3.0116667 1.5058333 2.41 0.1319 Soil*Treat*Block 12 20.2852381 1.6904365 2.70 0.0489 Source*Treat*Block 12 7.4623810 0.6218651 0.99 0.5034

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88 Table A-4. Dry leaf mass, first experiment. The ANOVA Procedure Dependent Variable: DL Sum of Source DF Squares Mean Square F Value Pr > F Model 71 534.2522619 7.5246797 9.57 <.0001 Error 12 9.4319048 0.7859921 Corrected Total 83 543.6841667 R-Square Coeff Var Root MSE DL Mean 0.982652 12.74101 0.886562 6.958333 Source DF Anova SS Mean Square F Value Pr > F Soil 1 284.9058333 284.9058333 362.48 <.0001 Source 1 67.1429762 67.1429762 85.42 <.0001 Treat 6 63.9316667 10.6552778 13.56 0.0001 Block 2 1.8866667 0.9433333 1.20 0.3348 Soil*Source 1 0.7058333 0.7058333 0.90 0.3620 Soil*Treat 6 23.3783333 3.8963889 4.96 0.0090 Soil*Block 2 1.3866667 0.6933333 0.88 0.4391 Source*Treat 6 35.9045238 5.9840873 7.61 0.0015 Source*Block 2 3.0580952 1.5290476 1.95 0.1854 Treat*Block 12 14.7833333 1.2319444 1.57 0.2239 Soil*Source*Treat 6 11.4416667 1.9069444 2.43 0.0902 Soil*Source*Block 2 0.6580952 0.3290476 0.42 0.6672 Soil*Treat*Block 12 16.5166667 1.3763889 1.75 0.1725 Source*Treat*Block 12 8.5519048 0.7126587 0.91 0.5660

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89 Table A-5. Dry root mass, second experiment. The ANOVA Procedure Dependent Variable: DR Sum of Source DF Squares Mean Square F Value Pr > F Model 41 87.07770833 2.12384654 2.11 0.1770 Error 6 6.05208333 1.00868056 Corrected Total 47 93.12979167 R-Square Coeff Var Root MSE DR Mean 0.935015 22.30814 1.004331 4.502083 Source DF Anova SS Mean Square F Value Pr > F Treat 3 5.82229167 1.94076389 1.92 0.2269 Soil 1 21.20020833 21.20020833 21.02 0.0038 Cultivar 1 0.11020833 0.11020833 0.11 0.7522 Block 2 4.38291667 2.19145833 2.17 0.1951 Treat*Soil 3 11.99562500 3.99854167 3.96 0.0713 Treat*Cultivar 3 5.98229167 1.99409722 1.98 0.2189 Treat*Block 6 8.34208333 1.39034722 1.38 0.3533 Soil*Cultivar 1 3.05020833 3.05020833 3.02 0.1327 Soil*Block 2 3.49041667 1.74520833 1.73 0.2551 Cultivar*Block 2 1.21541667 0.60770833 0.60 0.5775 Treat*Soil*Cultivar 3 9.90229167 3.30076389 3.27 0.1009 Treat*Soil*Block 6 7.23125000 1.20520833 1.19 0.4172 Treat*Cultivar*Block 6 3.99958333 0.66659722 0.66 0.6862 Soil*Cultivar*Block 2 0.35291667 0.17645833 0.17 0.8436

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90 Table A-6. Dry leaf mass, second experiment. The ANOVA Procedure Dependent Variable: DL Sum of Source DF Squares Mean Square F Value Pr > F Model 41 138.5602083 3.3795173 3.92 0.0457 Error 6 5.1745833 0.8624306 Corrected Total 47 143.7347917 R-Square Coeff Var Root MSE DL Mean 0.963999 16.80220 0.928671 5.527083 Source DF Anova SS Mean Square F Value Pr > F Treat 3 4.64062500 1.54687500 1.79 0.2484 Soil 1 57.86020833 57.86020833 67.09 0.0002 Cultivar 1 2.47520833 2.47520833 2.87 0.1412 Block 2 7.57541667 3.78770833 4.39 0.0668 Treat*Soil 3 8.34229167 2.78076389 3.22 0.1035 Treat*Cultivar 3 5.52729167 1.84243056 2.14 0.1969 Treat*Block 6 13.80125000 2.30020833 2.67 0.1289 Soil*Cultivar 1 7.28520833 7.28520833 8.45 0.0271 Soil*Block 2 1.21791667 0.60895833 0.71 0.5304 Cultivar*Block 2 3.66791667 1.83395833 2.13 0.2004 Treat*Soil*Cultivar 3 9.35729167 3.11909722 3.62 0.0845 Treat*Soil*Block 6 9.07208333 1.51201389 1.75 0.2560 Treat*Cultivar*Block 6 7.42208333 1.23701389 1.43 0.3362 Soil*Cultivar*Block 2 0.31541667 0.15770833 0.18 0.8374

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91 Table A-7. Leaf silicon concentration, second experiment. The ANOVA Procedure Dependent Variable: SiL Sum of Source DF Squares Mean Square F Value Pr > F Model 41 0.54321096 0.01324905 36.69 <.0001 Error 6 0.00216671 0.00036112 Corrected Total 47 0.54537767 R-Square Coeff Var Root MSE SiL Mean 0.996027 6.141591 0.019003 0.309417 Source DF Anova SS Mean Square F Value Pr > F Treat 3 0.40832283 0.13610761 376.91 <.0001 Soil 1 0.00156408 0.00156408 4.33 0.0826 Cultivar 1 0.07520833 0.07520833 208.27 <.0001 Block 2 0.00110279 0.00055140 1.53 0.2910 Treat*Soil 3 0.01153042 0.00384347 10.64 0.0081 Treat*Cultivar 3 0.01189217 0.00396406 10.98 0.0075 Treat*Block 6 0.00457354 0.00076226 2.11 0.1926 Soil*Cultivar 1 0.00848008 0.00848008 23.48 0.0029 Soil*Block 2 0.00000529 0.00000265 0.01 0.9927 Cultivar*Block 2 0.00109929 0.00054965 1.52 0.2920 Treat*Soil*Cultivar 3 0.01648842 0.00549614 15.22 0.0033 Treat*Soil*Block 6 0.00103771 0.00017295 0.48 0.8040 Treat*Cultivar*Block 6 0.00180271 0.00030045 0.83 0.5855 Soil*Cultivar*Block 2 0.00010329 0.00005165 0.14 0.8696

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92 Table A-8. Soil water pH, second experiment. The ANOVA Procedure Dependent Variable: pH Sum of Source DF Squares Mean Square F Value Pr > F Model 41 14.00937500 0.34169207 16.35 0.0010 Error 6 0.12541667 0.02090278 Corrected Total 47 14.13479167 R-Square Coeff Var Root MSE pH Mean 0.991127 2.177515 0.144578 6.639583 Source DF Anova SS Mean Square F Value Pr > F Treat 3 9.92229167 3.30743056 158.23 <.0001 Soil 1 2.21020833 2.21020833 105.74 <.0001 Cultivar 1 0.00520833 0.00520833 0.25 0.6354 Block 2 0.11541667 0.05770833 2.76 0.1412 Treat*Soil 3 0.16062500 0.05354167 2.56 0.1508 Treat*Cultivar 3 0.09895833 0.03298611 1.58 0.2899 Treat*Block 6 0.08958333 0.01493056 0.71 0.6534 Soil*Cultivar 1 0.03520833 0.03520833 1.68 0.2420 Soil*Block 2 0.08291667 0.04145833 1.98 0.2182 Cultivar*Block 2 0.15541667 0.07770833 3.72 0.0891 Treat*Soil*Cultivar 3 0.10895833 0.03631944 1.74 0.2584 Treat*Soil*Block 6 0.36875000 0.06145833 2.94 0.1076 Treat*Cultivar*Block 6 0.60291667 0.10048611 4.81 0.0388 Soil*Cultivar*Block 2 0.05291667 0.02645833 1.27 0.3478

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93 Table A-9. Soil Ca concen tration, second experiment. The ANOVA Procedure Dependent Variable: Ca Sum of Source DF Squares Mean Square F Value Pr > F Model 41 16066599.85 391868.29 123.91 <.0001 Error 6 18975.62 3162.60 Corrected Total 47 16085575.48 R-Square Coeff Var Root MSE Ca Mean 0.998820 3.750125 56.23704 1499.604 Source DF Anova SS Mean Square F Value Pr > F Treat 3 9881237.063 3293745.688 1041.47 <.0001 Soil 1 5610852.521 5610852.521 1774.12 <.0001 Cultivar 1 26649.188 26649.188 8.43 0.0272 Block 2 15643.292 7821.646 2.47 0.1647 Treat*Soil 3 291809.729 97269.910 30.76 0.0005 Treat*Cultivar 3 5103.729 1701.243 0.54 0.6734 Treat*Block 6 27504.375 4584.062 1.45 0.3318 Soil*Cultivar 1 18447.521 18447.521 5.83 0.0522 Soil*Block 2 6231.792 3115.896 0.99 0.4266 Cultivar*Block 2 17093.375 8546.688 2.70 0.1456 Treat*Soil*Cultivar 3 43933.063 14644.354 4.63 0.0528 Treat*Soil*Block 6 18546.208 3091.035 0.98 0.5107 Treat*Cultivar*Block 6 90735.958 15122.660 4.78 0.0392 Soil*Cultivar*Block 2 12812.042 6406.021 2.03 0.2127

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94 Table A-10. Soil Mg concen tration, second experiment. The ANOVA Procedure Dependent Variable: Mg Sum of Source DF Squares Mean Square F Value Pr > F Model 41 251473.4792 6133.4995 5.95 0.0161 Error 6 6187.5000 1031.2500 Corrected Total 47 257660.9792 R-Square Coeff Var Root MSE Mg Mean 0.975986 14.35890 32.11308 223.6458 Source DF Anova SS Mean Square F Value Pr > F Treat 3 180672.5625 60224.1875 58.40 <.0001 Soil 1 27122.5208 27122.5208 26.30 0.0022 Cultivar 1 825.0208 825.0208 0.80 0.4055 Block 2 1108.1667 554.0833 0.54 0.6100 Treat*Soil 3 26698.7292 8899.5764 8.63 0.0135 Treat*Cultivar 3 33.8958 11.2986 0.01 0.9983 Treat*Block 6 2021.0000 336.8333 0.33 0.9004 Soil*Cultivar 1 2715.0208 2715.0208 2.63 0.1558 Soil*Block 2 1082.1667 541.0833 0.52 0.6166 Cultivar*Block 2 2888.1667 1444.0833 1.40 0.3169 Treat*Soil*Cultivar 3 218.5625 72.8542 0.07 0.9735 Treat*Soil*Block 6 3043.3333 507.2222 0.49 0.7955 Treat*Cultivar*Block 6 1473.6667 245.6111 0.24 0.9478 Soil*Cultivar*Block 2 1570.6667 785.3333 0.76 0.5073

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95 Table A-11. Soil silicon concentration, second experiment. The ANOVA Procedure Dependent Variable: SiS Sum of Source DF Squares Mean Square F Value Pr > F Model 41 77058.54167 1879.47663 36.01 0.0001 Error 6 313.12500 52.18750 Corrected Total 47 77371.66667 R-Square Coeff Var Root MSE SiS Mean 0.995953 10.09186 7.224092 71.58333 Source DF Anova SS Mean Square F Value Pr > F Treat 3 71416.83333 23805.61111 456.16 <.0001 Soil 1 176.33333 176.33333 3.38 0.1157 Cultivar 1 1776.33333 1776.33333 34.04 0.0011 Block 2 101.54167 50.77083 0.97 0.4306 Treat*Soil 3 2329.83333 776.61111 14.88 0.0035 Treat*Cultivar 3 728.83333 242.94444 4.66 0.0522 Treat*Block 6 162.29167 27.04861 0.52 0.7781 Soil*Cultivar 1 16.33333 16.33333 0.31 0.5961 Soil*Block 2 45.29167 22.64583 0.43 0.6668 Cultivar*Block 2 7.29167 3.64583 0.07 0.9333 Treat*Soil*Cultivar 3 40.50000 13.50000 0.26 0.8528 Treat*Soil*Block 6 84.54167 14.09028 0.27 0.9320 Treat*Cultivar*Block 6 71.54167 11.92361 0.23 0.9523 Soil*Cultivar*Block 2 101.04167 50.52083 0.97 0.4321

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96 APPENDIX B SOIL ANALYSIS OF SILICON DRENCH TREATMENT Table B-1. Soil pH, extractable Ca and Mg, soil Si concentrations and le af Si concen tration for two soil orders with two wollastonite sources at six rates and a drench treatment. Rate Cay Mgy Soil Siy Leaf Siz Soil Wollastonite (MT ha-1) Soil pHx -------kg ha-1 -------(mg kg-1) (dag kg-1) Entisol Control 0 6.20 679 201 18 0.330 Ultisol Control 0 6.10 851 243 28 0.280 Entisol W-10 0.5 6.30 284 109 20 0.352 1 6.10 231 67 23 0.385 2 6.50 517 73 35 0.418 4 6.30 478 75 50 0.440 8 7.30 917 103 91 0.451 Ultisol 0.5 6.40 1,353 377 42 0.363 1 6.40 1,452 398 53 0.385 2 6.60 1,564 397 64 0.407 4 6.70 1,917 410 86 0.374 8 7.10 2,436 427 106 0.418 Entisol DFSP 0.5 5.90 114 63 13 0.275 1 5.80 155 52 13 0.264 2 6.10 277 76 17 0.297 4 6.70 457 110 29 0.440 8 6.70 487 78 41 0.429 Ultisol 0.5 6.70 1,211 341 33 0.297 1 6.90 1,378 413 39 0.319 2 6.90 1,763 521 45 0.319 4 7.00 1,810 483 49 0.352 8 6.90 1,818 435 56 0.363 Entisol Drench (1% AgSil 25) 6.20 679 201 18 0.616 Ultisol Drench (1% AgSil 25) 6.10 851 243 28 0.407 x Soil water pH (1:2 v/v). y 0.5 N acetic acid (CH3COOH) extractant solution. z Autoclave induced digestion method (Elliot and Snyder, 1991).

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97 APPENDIX C SUMMARY TABLE OF THE STATIS TICAL ANALYS IS OF GH STUDIES Table C-1. AUDPC, first experiment. The ANOVA Procedure Dependent Variable: AUDPC Sum of Source DF Squares Mean Square F Value Pr > F Model 37 13359.86758 361.07750 2.03 0.0651 Error 16 2847.39477 177.96217 Corrected Total 53 16207.26234 R-Square Coeff Var Root MSE AUDPC Mean 0.824314 38.03309 13.34025 35.07537 Source DF Anova SS Mean Square F Value Pr > F Treat 8 8001.429293 1000.178662 5.62 0.0017 Block 2 314.566604 157.283302 0.88 0.4324 Cultivar 1 109.824817 109.824817 0.62 0.4436 Treat*Block 16 3648.991396 228.061962 1.28 0.3128 Treat*Cultivar 8 897.596033 112.199504 0.63 0.7413 Block*Cultivar 2 387.459433 193.729717 1.09 0.3604

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98 Table C-2. r parameter, first experiment. The ANOVA Procedure Dependent Variable: rGomp Sum of Source DF Squares Mean Square F Value Pr > F Model 37 0.00167158 0.00004518 1.18 0.3753 Error 16 0.00061496 0.00003844 Corrected Total 53 0.00228654 R-Square Coeff Var Root MSE rGomp Mean 0.731051 16.06852 0.006200 0.038582 Source DF Anova SS Mean Square F Value Pr > F Treat 8 0.00055968 0.00006996 1.82 0.1465 Block 2 0.00002601 0.00001301 0.34 0.7179 Cultivar 1 0.00005176 0.00005176 1.35 0.2629 Treat*Block 16 0.00062876 0.00003930 1.02 0.4826 Treat*Cultivar 8 0.00032936 0.00004117 1.07 0.4290 Block*Cultivar 2 0.00007601 0.00003801 0.99 0.3936

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99 Table C-3. MSE (low value) a nd R-square (high value) check fo r disease progression model, in experiment 1 (Chapter 3). Example: Si treatment 1.92 MT Si ha-1 with the cultivar Hinson Long Juvenile (forage soybe an cultivar), replication 2. REGRESSION OF BACK-TRANSFORMED PREDICTED ON OBSERVED FOR RECALCULATED r2 AND MSE -----------------------------------------TREAT=1.92FS2 -----------------------------------------The REG Procedure Dependent Variable: BACKGomp Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 1 0.00034962 0.00034962 125.19 <.0001 Error 5 0.00001396 0.00000279 Corrected Total 6 0.00036358 Root MSE 0.00167 R-Square 0.9616 Dependent Mean 0.00432 Adj R-Sq 0.9539 Coeff Var 38.68245 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > |t| Intercept Intercept 1 0.00006508 0.00073726 0.09 0.9331 SEV 1 0.51353 0.04590 11.19 <.0001

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100 Table C-4. r parameter determination, first experiment. LINEAR REGRESSIONS OF TRAN SFORMED SEVERITY ON TIME -----------------------------------------TREAT=1.92FS2 -----------------------------------------The REG Procedure Model: MODEL1 Dependent Variable: GSEV Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 1 0.92029 0.92029 12.51 0.0166 Error 5 0.36772 0.07354 Corrected Total 6 1.28801 Root MSE 0.27119 R-Square 0.7145 Dependent Mean -1.95065 Adj R-Sq 0.6574 Coeff Var -13.90249 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > |t| Intercept 1 -2.58540 0.20665 -12.51 <.0001 DAYS 1 0.04114 0.01163 3.54 0.0166

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101 Table C-5. Leaf ma ss, first experiment. The ANOVA Procedure Dependent Variable: LMass Sum of Source DF Squares Mean Square F Value Pr > F Model 37 9.04481481 0.24445445 1.06 0.4696 Error 16 3.69518519 0.23094907 Corrected Total 53 12.74000000 R-Square Coeff Var Root MSE LMass Mean 0.709954 6.268325 0.480572 7.666667 Source DF Anova SS Mean Square F Value Pr > F Treat 8 1.28666667 0.16083333 0.70 0.6903 Block 2 0.11444444 0.05722222 0.25 0.7835 Cultivar 1 0.04740741 0.04740741 0.21 0.6566 Treat*Block 16 4.39888889 0.27493056 1.19 0.3658 Treat*Cultivar 8 3.11925926 0.38990741 1.69 0.1773 Block*Cultivar 2 0.07814815 0.03907407 0.17 0.8458

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102 Table C-6. Leaf mass, second experiment. The ANOVA Procedure Dependent Variable: LMass Sum of Source DF Squares Mean Square F Value Pr > F Model 9 0.86392857 0.09599206 0.79 0.6281 Error 18 2.18285714 0.12126984 Corrected Total 27 3.04678571 R-Square Coeff Var Root MSE LMass Mean 0.283554 4.829455 0.348238 7.210714 Source DF Anova SS Mean Square F Value Pr > F Treat 6 0.37428571 0.06238095 0.51 0.7898 Block 3 0.48964286 0.16321429 1.35 0.2909

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103 Table C-7. Soil Ca concen tration, first experiment. The ANOVA Procedure Dependent Variable: Ca Sum of Source DF Squares Mean Square F Value Pr > F Model 37 5066651.185 136936.519 21.51 <.0001 Error 16 101864.074 6366.505 Corrected Total 53 5168515.259 R-Square Coeff Var Root MSE Ca Mean 0.980291 1.227300 79.79038 6501.296 Source DF Anova SS Mean Square F Value Pr > F Treat 8 4946794.593 618349.324 97.13 <.0001 Block 2 9187.148 4593.574 0.72 0.5012 Cultivar 1 12942.519 12942.519 2.03 0.1731 Treat*Block 16 73254.519 4578.407 0.72 0.7414 Treat*Cultivar 8 18967.481 2370.935 0.37 0.9202 Block*Cultivar 2 5504.926 2752.463 0.43 0.6564

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104 Table C-8. Soil Ca concen tration, second experiment. The ANOVA Procedure Dependent Variable: Ca Sum of Source DF Squares Mean Square F Value Pr > F Model 9 2168222.821 240913.647 6.46 0.0004 Error 18 670958.143 37275.452 Corrected Total 27 2839180.964 R-Square Coeff Var Root MSE Ca Mean 0.763679 6.842675 193.0685 2821.536 Source DF Anova SS Mean Square F Value Pr > F Treat 6 2071722.714 345287.119 9.26 0.0001 Block 3 96500.107 32166.702 0.86 0.4782

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105 Table C-9. Soil Mg concen tration, first experiment. The ANOVA Procedure Dependent Variable: Mg Sum of Source DF Squares Mean Square F Value Pr > F Model 37 11519.46296 311.33684 0.86 0.6633 Error 16 5814.40741 363.40046 Corrected Total 53 17333.87037 R-Square Coeff Var Root MSE Mg Mean 0.664564 4.124056 19.06307 462.2407 Source DF Anova SS Mean Square F Value Pr > F Treat 8 3102.037037 387.754630 1.07 0.4314 Block 2 359.592593 179.796296 0.49 0.6187 Cultivar 1 115.574074 115.574074 0.32 0.5806 Treat*Block 16 4323.740741 270.233796 0.74 0.7198 Treat*Cultivar 8 3558.925926 444.865741 1.22 0.3463 Block*Cultivar 2 59.592593 29.796296 0.08 0.9217

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106 Table C-10. Soil Mg concen tration, second experiment. The ANOVA Procedure Dependent Variable: Mg Sum of Source DF Squares Mean Square F Value Pr > F Model 9 2044.678571 227.186508 0.69 0.7075 Error 18 5907.428571 328.190476 Corrected Total 27 7952.107143 R-Square Coeff Var Root MSE Mg Mean 0.257124 7.606070 18.11603 238.1786 Source DF Anova SS Mean Square F Value Pr > F Treat 6 1120.857143 186.809524 0.57 0.7495 Block 3 923.821429 307.940476 0.94 0.4427

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107 Table C-11. Soil water pH con centration, first experiment. The ANOVA Procedure Dependent Variable: pH Sum of Source DF Squares Mean Square F Value Pr > F Model 37 9.04629630 0.24449449 18.18 <.0001 Error 16 0.21518519 0.01344907 Corrected Total 53 9.26148148 R-Square Coeff Var Root MSE pH Mean 0.976766 1.661111 0.115970 6.981481 Source DF Anova SS Mean Square F Value Pr > F Treat 8 8.19148148 1.02393519 76.13 <.0001 Block 2 0.09148148 0.04574074 3.40 0.0588 Cultivar 1 0.00074074 0.00074074 0.06 0.8174 Treat*Block 16 0.56851852 0.03553241 2.64 0.0302 Treat*Cultivar 8 0.18925926 0.02365741 1.76 0.1600 Block*Cultivar 2 0.00481481 0.00240741 0.18 0.8378

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108 Table C-12. Soil water pH con centration, second experiment. The ANOVA Procedure Dependent Variable: pH Sum of Source DF Squares Mean Square F Value Pr > F Model 9 3.61178571 0.40130952 15.88 <.0001 Error 18 0.45500000 0.02527778 Corrected Total 27 4.06678571 R-Square Coeff Var Root MSE pH Mean 0.888118 2.267813 0.158990 7.010714 Source DF Anova SS Mean Square F Value Pr > F Treat 6 3.49928571 0.58321429 23.07 <.0001 Block 3 0.11250000 0.03750000 1.48 0.2526

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109 Table C-13. Soil Si concen tration, first experiment. The ANOVA Procedure Dependent Variable: SiSoil Sum of Source DF Squares Mean Square F Value Pr > F Model 37 33569.44444 907.28228 173.04 <.0001 Error 16 83.88889 5.24306 Corrected Total 53 33653.33333 R-Square Coeff Var Root MSE SiSoil Mean 0.997507 9.367249 2.289772 24.44444 Source DF Anova SS Mean Square F Value Pr > F Treat 8 33437.33333 4179.66667 797.18 <.0001 Block 2 3.44444 1.72222 0.33 0.7248 Cultivar 1 10.66667 10.66667 2.03 0.1730 Treat*Block 16 72.55556 4.53472 0.86 0.6124 Treat*Cultivar 8 37.33333 4.66667 0.89 0.5462 Block*Cultivar 2 8.11111 4.05556 0.77 0.4779

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110 Table C-14. Soil Si concen tration, second experiment. The ANOVA Procedure Dependent Variable: SiSoil Sum of Source DF Squares Mean Square F Value Pr > F Model 9 73797.46429 8199.71825 577.67 <.0001 Error 18 255.50000 14.19444 Corrected Total 27 74052.96429 R-Square Coeff Var Root MSE SiSoil Mean 0.996550 5.837933 3.767552 64.53571 Source DF Anova SS Mean Square F Value Pr > F Treat 6 73778.21429 12296.36905 866.28 <.0001 Block 3 19.25000 6.41667 0.45 0.7190

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111 Table C-15. Leaf Si concen tration, first experiment. The ANOVA Procedure Dependent Variable: Sileaf Sum of Source DF Squares Mean Square F Value Pr > F Model 37 1.13166946 0.03058566 46.20 <.0001 Error 16 0.01059241 0.00066203 Corrected Total 53 1.14226187 R-Square Coeff Var Root MSE Sileaf Mean 0.990727 10.55544 0.025730 0.243759 Source DF Anova SS Mean Square F Value Pr > F Treat 8 0.99958170 0.12494771 188.74 <.0001 Block 2 0.00339515 0.00169757 2.56 0.1081 Cultivar 1 0.09787780 0.09787780 147.85 <.0001 Treat*Block 16 0.00927352 0.00057959 0.88 0.6032 Treat*Cultivar 8 0.02106104 0.00263263 3.98 0.0091 Block*Cultivar 2 0.00048026 0.00024013 0.36 0.7014

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112 Table C-16. Leaf Si concen tration, second experiment. The ANOVA Procedure Dependent Variable: SiLeaf Sum of Source DF Squares Mean Square F Value Pr > F Model 9 0.10870714 0.01207857 34.09 <.0001 Error 18 0.00637857 0.00035437 Corrected Total 27 0.11508571 R-Square Coeff Var Root MSE SiLeaf Mean 0.944575 10.80099 0.018825 0.174286 Source DF Anova SS Mean Square F Value Pr > F Treat 6 0.10813571 0.01802262 50.86 <.0001 Block 3 0.00057143 0.00019048 0.54 0.6626

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113 APPENDIX D RAINFALL AND AIR TEMPERATURE OF FIELD EXPERIMENTS Time 16Jul30Jul13Aug27Aug10Sep24Sep08Oct Temperature (C) 18 20 22 24 26 28 30 Rain (cm) 0 2 4 6 8 10 12 16Jul30Jul13Aug27Aug10Sep24Sep08Oct A B C DFigure D-1. Daily average of total rainfall and ai r temperature. A and C) Total rainfall at 2 m height. B and D) Air temperature at 60 cm height. A and B) Year 1. C and D) Year 2. Source: FAWN, 2009.

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114 APPENDIX E SOYBEAN SEED QUALITY VISUAL SCALE Figure E-1. Visual scale used for field experiments to evaluate seed quality. equated to undamaged seeds, and equated to the most damaged seeds.

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115 APPENDIX F SUMMARY TABLE OF THE STATISTI CAL ANALYS IS FOR BIOMASS AMONG TREATMENTS FOR FIELD EXPERIMENTS IN 2007 AND 2008 Table F-1. Dry leaf mass, 2007. The ANOVA Procedure Dependent Variable: DryLeaf Sum of Source DF Squares Mean Square F Value Pr > F Model 52 1185.000500 22.788471 0.86 0.6846 Error 27 714.267500 26.454352 Corrected Total 79 1899.268000 R-Square Coeff Var Root MSE DryLeaf Mean 0.623925 16.50106 5.143379 31.17000 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 22.2605000 22.2605000 0.84 0.3671 Treat 9 256.1830000 28.4647778 1.08 0.4111 Block 3 80.0920000 26.6973333 1.01 0.4039 Cultivar*Treat 9 142.4645000 15.8293889 0.60 0.7870 Cultivar*Block 3 5.0575000 1.6858333 0.06 0.9786 Treat*Block 27 678.9430000 25.1460370 0.95 0.5519

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116 Table F-2. Dry leaf mass, 2008. The ANOVA Procedure Dependent Variable: DryLeaf Sum of Source DF Squares Mean Square F Value Pr > F Model 52 4138.676000 79.589923 2.17 0.0160 Error 27 991.836000 36.734667 Corrected Total 79 5130.512000 R-Square Coeff Var Root MSE DryLeaf Mean 0.806679 23.23079 6.060913 26.09000 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 340.312500 340.312500 9.26 0.0052 Treat 9 647.594500 71.954944 1.96 0.0856 Block 3 428.121000 142.707000 3.88 0.0198 Cultivar*Treat 9 764. 605000 84.956111 2.31 0.0446 Cultivar*Block 3 49.046500 16.348833 0.45 0.7228 Treat*Block 27 1908.996500 70.703574 1.92 0.0474 Table F-3. Dry pod mass, 2007. The ANOVA Procedure Dependent Variable: DryPod Sum of Source DF Squares Mean Square F Value Pr > F Model 52 4203.857000 80.843404 1.34 0.2100 Error 27 1634.816875 60.548773 Corrected Total 79 5838.673875 R-Square Coeff Var Root MSE DryPod Mean 0.7200 02 16.54850 7.781309 47.02125 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 37.675125 37.675125 0.62 0.4371 Treat 9 772.037625 85.781958 1.42 0.2300 Block 3 40.753375 13.584458 0.22 0.8786 Cultivar*Treat 9 786. 688625 87.409847 1.44 0.2192 Cultivar*Block 3 290. 404375 96.801458 1.60 0.2128 Treat*Block 27 2276.297875 84.307329 1.39 0.1976

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117 Table F-4. Dry pod mass, 2008. The ANOVA Procedure Dependent Variable: DryPod Sum of Source DF Squares Mean Square F Value Pr > F Model 52 21118.47400 406.12450 3.72 0.0002 Error 27 2946.25487 109.12055 Corrected Total 79 24064.72887 R-Square Coeff Var Root MSE DryPod Mean 0.8775 70 21.57556 10.44608 48.41625 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 12789.15312 12789. 15312 117.20 <.0001 Treat 9 784.73762 87.19307 0.80 0.6204 Block 3 893.94937 297.98312 2.73 0.0634 Cultivar*Treat 9 2276.76563 252.97396 2.32 0.0441 Cultivar*Block 3 526.21138 175.40379 1.61 0.2108 Treat*Block 27 3847.65688 142.50581 1.31 0.2463 Table F-5. Dry stem mass, 2007. The ANOVA Procedure Dependent Variable: DryStem Sum of Source DF Squares Mean Square F Value Pr > F Model 52 4305.172000 82.791769 3.52 0.0004 Error 27 635.636000 23.542074 Corrected Total 79 4940.808000 R-Square Coeff Var Root MSE DryStem Mean 0.871350 15.84591 4.852018 30.62000 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 2672.672000 2672.672000 113.53 <.0001 Treat 9 424.803000 47.200333 2.00 0.0786 Block 3 83.263000 27.754333 1.18 0.3362 Cultivar*Treat 9 194.6230 00 21.624778 0.92 0.5243 Cultivar*Block 3 98.0190 00 32.673000 1.39 0.2678 Treat*Block 27 831.792000 30.807111 1.31 0.2447

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118 Table F-6. Dry stem mass, 2008. The ANOVA Procedure Dependent Variable: DryStem Sum of Source DF Squares Mean Square F Value Pr > F Model 52 3573.747500 68.725913 2.74 0.0029 Error 27 676.628000 25.060296 Corrected Total 79 4250.375500 R-Square Coeff Var Root MSE DryStem Mean 0.840807 19.64496 5.006026 25.48250 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 2032.128000 2032.12800 0 81.09 <.0001 Treat 9 183.995500 20.443944 0.82 0.6065 Block 3 431.474500 143.824833 5.74 0.0036 Cultivar*Treat 9 178.827000 19.869667 0.79 0.6255 Cultivar*Block 3 50.947000 16.982333 0.68 0.5733 Treat*Block 27 696.375500 25.791685 1.03 0.4705 Table F-7. Dry root mass, 2007. The ANOVA Procedure Dependent Variable: DryRoot Sum of Source DF Squares Mean Square F Value Pr > F Model 52 291.9070000 5.6135962 4.24 <.0001 Error 27 35.7725000 1.3249074 Corrected Total 79 327.6795000 R-Square Coeff Var Root MSE DryRoot Mean 0.890831 11.62379 1.151046 9.902500 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 186.6605000 186. 6605000 140.89 <.0001 Treat 9 10.4945000 1.1660556 0.88 0.5545 Block 3 3.9855000 1.3285000 1.00 0.4067 Cultivar*Treat 9 19.0695000 2.1188333 1.60 0.1656 Cultivar*Block 3 15. 9375000 5.3125000 4.01 0.0175 Treat*Block 27 55.7595000 2.0651667 1.56 0.1276

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119 Table F-8. Dry root mass, 2008. The ANOVA Procedure Dependent Variable: DryRoot Sum of Source DF Squares Mean Square F Value Pr > F Model 52 188.3010000 3.6211731 1.08 0.4254 Error 27 90.6345000 3.3568333 Corrected Total 79 278.9355000 R-Square Coeff Var Root MSE DryRoot Mean 0.675070 24.98693 1.832166 7.332500 Source DF Anova SS Mean Square F Value Pr > F Cultivar 1 24.20000000 24.20000000 7.21 0.0122 Treat 9 9.44800000 1.04977778 0.31 0.9639 Block 3 19.22650000 6.40883333 1.91 0.1519 Cultivar*Treat 9 30. 37250000 3.37472222 1.01 0.4597 Cultivar*Block 3 34. 66300000 11.55433333 3.44 0.0307 Treat*Block 27 70.39100000 2.60707407 0.78 0.7421

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135 BIOGRAPHICAL SKETCH Ernane Miranda Lem es, son of Arlindo Leme s Coelho and Nilza Maria Miranda Coelho, was born in Monte Alegre de Mina s, Minas Gerais state, Brazil in 1982. Ernane attended E.E. Guiomar de Freitas Costa during high school and graduated in 2000. He attended the Universidade Federal de Uberlndi a in Minas Gerais state, where he majored in agronomy. He was awarded a B.Sc. degree in April 2006. In the Fall of 2006 he accepted an assistantship with the University of Florida to obtain the a maste rs degree in the Department of Plant Pathology. Under the guidance of Dr. Cheryl Mackowiak a nd Dr. Lawrence Datnoff he conducted research on the effect of silicon amendments to contro l Asian soybean rust. On October 2008 Mr. Lemes was awarded a travel grant to present his part ial results at the ENDURE Conference in La Grande Motte, France. After his masters degree, Mr. Lemes plans to continue his education as a PhD student at the Universidade Federal de Uberlndia under the guidance of Dr. Gaspar Korndrfer and Dr. Lsias Coelho. His research will focus on the effects of Si on sugarcane performance under stresses.