Screening for Differential Responses to Drought and Shade in Selected Zoysiagrass Germplasm

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Screening for Differential Responses to Drought and Shade in Selected Zoysiagrass Germplasm
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english
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Christensen, Christian Thomas
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University of Florida
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Master's ( M.S.)
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University of Florida
Degree Disciplines:
Agronomy
Committee Chair:
Kenworthy, Kevin E
Committee Members:
Erickson, John E.
Kruse, Jason K
Schwartz, Brian

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zoysiagrass
Agronomy -- Dissertations, Academic -- UF
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Agronomy thesis, M.S.
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theses   ( marcgt )
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Abstract:
Zoysiagrasses are adapted to a variety of soils, have good winter-hardiness, and high temperature tolerance; however, they are still susceptible to abiotic stresses including shade and drought. The overall goal of the first study was to evaluate zoysiagrass species and genotypes for differential responses to drought stress in order to identify genotypes that can maintain color, density, quality, and green cover longer into a dry down to possibly reduce irrigation by homeowners. Shade decreases both the quantity and quality of light leading to changes in leaf structure and growth rates that reduce turfgrass persistence in reduced light environments. The overall goal of the second study was to identify zoysiagrass genotypes that are able to maintain similar growth habits in shade as would occur in full sun. In general, shade stress within a species resulted in reduced values for relative chlorophyll content, a more upright leaf orientation (but not always statistically different), reduced percent plot establishment, and no consistent trends in percent green cover. Based upon the variation observed between species and genotypes, potential does exist for the improvement of zoysiagrass in response to shade and drought environments.
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by Christian Thomas Christensen.
Thesis:
Thesis (M.S.)--University of Florida, 2012.
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Adviser: Kenworthy, Kevin E.
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RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-05-31

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1 SCREENING FOR DIFFER ENTIAL RESPONSES TO DROUGHT AND SHADE IN SELECTED ZOYSIAGR ASS GERMPLASM By CHRISTIAN THOMAS CHRISTENSEN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2012

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2 2012 Christian T homas C hristensen

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3 To Crystal, Cristina, Christopher, Brenda, and Tom

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4 ACKNOWLEDGMENTS I would first like to thank my advisor Dr. Kevin Kenworthy for his willingness to take me into the Agronomy department and allow me to study under him. My experience my education. I would also thank to thank my committee m embers including Dr. John Erickson, Dr. Jason Kruse, and Dr. Brian Schwartz for their guidance and input in this thesis. In addition to my committee members, I would like to thank all the OPS students that have assisted in my research more specifically Wal to be pinnacle at times. I also would like to thank all my friends and roommates who have been supportive throughout my research. I thank them for their willingness to assist me in any aspect of my life when needed. Most im portantly, I would like to thank my entire family for the ir constant support through not only my entire college career. I would not have been able to develop into the person I am today without positive examples provided by my pare nts and the loving su pport of my sisters Crystal and Cristina and my brother Christopher.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURE S ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 13 Zoysiagrass ................................ ................................ ................................ ............ 13 Drought ................................ ................................ ................................ ................... 16 ................................ ................................ ................................ ..... 16 Drought Responses ................................ ................................ .......................... 17 Previous Drought Avoidance Research ................................ ............................ 18 Shade ................................ ................................ ................................ ..................... 23 Irradiance Components ................................ ................................ .................... 23 Shade Responses ................................ ................................ ............................ 24 Previous Shade Tolerance Research ................................ ............................... 25 Current Efforts ................................ ................................ ................................ .. 27 Objectives ................................ ................................ ................................ ............... 27 2 FIELD DRY DOWN RESPSONSES OF 6 5 ZOYSIAGRASS GENOTYPES .......... 29 Background ................................ ................................ ................................ ............. 29 Materials and Methods ................................ ................................ ............................ 30 Locati on and Material ................................ ................................ ....................... 30 Plant Science Research and Education Unit ................................ .............. 30 Agronomy Forage Research Unit ................................ ............................... 31 Data ................................ ................................ ................................ .................. 32 Statistical Analysis ................................ ................................ ............................ 33 Result s and Discussion ................................ ................................ ........................... 34 AFRU Results ................................ ................................ ................................ ... 34 PSREU ................................ ................................ ................................ ............. 36 Summary ................................ ................................ ................................ ................ 43 3 SHADE RESPONSES OF 43 ZOYSIAGRASS GENOTYPES ............................... 69 Background ................................ ................................ ................................ ............. 69 Materials and Methods ................................ ................................ ............................ 71

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6 Procedure ................................ ................................ ................................ ......... 71 Statistical Analysis ................................ ................................ ............................ 72 Results and Discussion ................................ ................................ ........................... 73 Percen t Plot Establishment ................................ ................................ .............. 73 Chlorophyll Content ................................ ................................ .......................... 75 Leaf Orientation, Sun vs. Shade ................................ ................................ ....... 77 Percent Green Cover ................................ ................................ ....................... 79 Summary ................................ ................................ ................................ ................ 81 4 CONCLUSIONS ................................ ................................ ................................ ... 100 LIST OF REFERENCES ................................ ................................ ............................. 108 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 115

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7 LIST OF TABLES Table page 2 1 Zoysiagrass genotypes evaluated for dry down responses in 2010 and 2011 at Hague and Citra, FL. ................................ ................................ ...................... 45 2 2 Estimate of pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for years (2010 and 2011) and locations (PSREU and AFRU). .......................... 46 2 3 Estimate of pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for years (2010 and 2011) for AFRU, Hague, FL. ................................ ............... 47 2 4 Estimate of pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for years (2010 and 2011) for PSREU, Citra, FL. ................................ ............... 48 2 5 2010 estimate of analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass ge notypes for PSREU, Citra, FL. ................................ ................................ .............................. 49 2 6 2011 estimate of analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for PSREU, Citra, FL. ................................ ................................ .............................. 50 2 7 Pooled analysis of variance components for col or, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes percent difference across locations (PSREU and AFRU) and years (2010 and 2011). .................... 51 2 8 Pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for AFRU, Hague, FL for percent difference across years (2010 and 2011). ................................ ............ 52 2 9 Pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference across years (2010 and 2011). ................................ ............ 53 2 10 2010 analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference ................................ ................................ ............................ 54 2 11 2011 analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference ................................ ................................ ............................ 55

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8 2 12 Initial, final, and percent difference color ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). ....................... 56 2 13 Initial, final, and percent difference density ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). ....................... 58 2 14 Initial, final, and percent difference quality ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). ....................... 60 2 15 Initial, final, and percent difference for percent green cover ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (201 0 and 2011). ... 63 2 16 Initial, final, and percent difference leaf firing ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL f or 2011. ................................ ........................... 65 2 17 Total turf performance index of 65 zoysiagrass genotypes for 2010 and 2011 dry downs at PSREU, Citra, FL. ................................ ................................ ......... 67 3 1 Zoysiagrass species and entries studied for their comparative performance in full sun and 60 % shade, Citra, FL. ................................ ................................ ..... 85 3 2 Minimum, maximum and average performance values of Z. matrella and Z. japonica grown under full sun and 60% shade in 2011. ................................ ..... 86 3 3 Turf Performance Index for sun vs. shade genotype comparisons for percent plot establishment for 44 zoysiagrass genotypes in 2010 and 2011, Citra, FL. .. 87 3 4 Zoysiagrass genotypes mean percent plot establishment under 60% shade for November 2010 and late Augus t 2011, Citra, FL. ................................ ......... 89 3 5 Turf Performance Index for sun vs. shade genotype comparisons for relative chlorophyll content ................................ ................................ .............................. 90 3 6 Zoysiagrass genotype mean relative chlorophyll content under 60% shade for November 2010 and August 2011, Citra, FL. ................................ ................ 92 3 7 Turf Performance Index for sun vs. shade genotype comparisons for leaf orientation ................................ ................................ ................................ ........... 93 3 8 Zoysiagrass genotypes mean leaf orientation under 60% shade for August 2011, Citra, FL. ................................ ................................ ................................ ... 95 3 9 Turf Performance index for sun vs. shade genotype comparisons for percent green cover ................................ ................................ ................................ ......... 96 3 10 Zoysiagrass genotype mean percent green cover under 60% shade for November 2010 and August 2011, Citra, FL. ................................ ..................... 98

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9 LIST OF FIGURES Figure page 3 1 Shade experiment showing f ull sun and 60% shade treatment ........................ 103 3 2 Species sun vs. shade comparisons for percent plot establishment ................. 104 3 3 Species sun vs. shade comparisons for relative chlorophyll content ................ 105 3 4 Species sun vs. shade comparisons for leaf orientation ................................ ... 106 3 5 Species sun vs. shade comparisons for percent green cover .......................... 107

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10 LIST OF ABBREVIATION S AFRU Agronomy Forage and Research Unit AMRD Average Maximum Root Depth ARD Average Root Diameter DIA Digital Image Analysis ET Evapotransporation FTSW Fraction of Transpirable Water NDVI Normalized Difference Vegetation Index NTEP National Turfgrass Evaluation Program NTR Normalized Transpiration Rate PAR Photosynthetically Active Radiation PGC Percent Green Cover PI Performance Index PPE Percent Plot Establishment PPFD Photosynthetic Photon Flux Density PSREU Plant Science and Research Education Unit R/S Root to Shoot Ratio RCC Relative Chlorophyll Content RDW Root Dry Weight RLD Root Length Density RRDD Rate of Root Depth Development RSA Root Surface Area RV Root Volume SDW Shoot Dry Weight TPI Turf Performance Index

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11 TQ Turf Quality TRL Total Root Length TSW Total Transpiration Rate TTPI Total Turf Performance Index UF University of Florida

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12 Abstract of Thesis Presented to the Graduate School Of the University of Florida in Partia l Fulfillment of the Requirements for the Degree of Master of Science SCREENING FOR DIFFERENTIAL RESPONSES TO DROUGHT AND SHADE IN SELECTED ZOYSIAGRASS GERMPLASM By Christian Thomas Christensen May 2012 Chair: Kevin Kenworthy Major: Agronomy Zoysiagrasses are adapted to a variety of soils, have good winter hardiness, and high temperature tolerance ; however, they are still susceptible to abiotic stresses including shade and drought. The overall goal of the first study was to evaluate zoysiagras s species and genotypes for differential responses to drought stress in order to identify genotypes that can maintain color, density, quality, and green cover longer into a dry down to possibly reduce irrigation by homeowners. Shade decreases both the qua ntity and quality of light leading to changes in leaf structure and growth rates that reduce turfgrass persistence in reduced light environments. The overall goal of the second study was to identify zoysiagrass genotypes that are able to maintain similar growth habits in shade as would occur in full sun. In general, shade stress within a species resulted in reduced values for r elative chlorophyll content, a more upright leaf orientation (but not always statistically different ) reduced percent plot establi shment, and no consistent trends in percent green cover. Based upon the variation observed between specie s and genotypes potential does exist for the improvement of zoysiagrass in response to shade and drought environments.

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13 CHAPTER 1 INTRODUCTION Zoysiagr ass Zoysiagrasses ( Zoysia spp .) are C 4 perennial grasses that have been theorized as having post ancestral origin under the tropical conditions of southeastern China (Beard, 2012 ) Z oysiagrass continued to expand into their secondary centers of origin kno wn as the Australasian region. This region included Japan, Korea, northeastern Australia, and the south Pacific Islands extending to Polyne sia. T he migration and diversification of zoysiagrass was limited (Beard, 2012) due to the propagation by vegetative means as a result of limited seed germination Zoysiagrass was not introduced to the United States from the Orient until the early 1900 s (Ruemmele and Engelke, 1990). It was the contributions of Frank N. Meyer and C.V. Piper from their plant exploration t rips to the Pacific Rim around 1910 that allowed the U.S. to have access to zoysiagrass (Brede and Sun, 1995; Cunningham, 1984; Engelke and Murray, 1982). The two most commonly found species in the U.S. are Zoysia japonica Steud. a nd Z. matrella (L.) Merr. which readily intercross suggesting that they are genetically compatible (Beard, 2012). The first zoysiagrass cultivar, Z. matrella was recorded in 1927 (Hanson, 1965), but it was not until the in the southe rn United States included other species and cultivars. This can be contributed to their lack of adaptation for lawns at the time (A nonymous, 1994; Halsey, 1956). In the 1950 s, Dr. Roy Bair began a sod nursery in South Bay, FL and was the first sod producer to grow species of turfgrass other than St. Augustinegrass ( Stenotaphrum secundatum [Walt.] Kuntze) including Zoysia matrella and bermudagrass ( Cynodon

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14 dactylon ( L.) Pers ) The success surrounding Dr. Roy Bair soon became apparent and other sod producers such as O.S. Baker, Miami, FL, Walt Pursley, Palmetto, FL, and Joe Hall, Clewiston, FL began producing additional species of turf including zoysiagrasses (White and Busey, 19 87) By the end of the 1950 commercial standards for zoysiagrass (Grau and Radko 1951 ; Hanson, 1965 ). Dating from the release of these cultivars to the present day the lack of familiarity with management requirements (Madison, 1971) and mode of propagation has slowed the adoption of zoysiagrass for turf (Beard, 2012). Currently, St. Augustinegrass (> 50,000 acres) and bahiagrass ( Paspalum notatum Fluegge) (>34,0 00 acres) represent the majority of sod produced in Florida (Hodges and Stevens, 2010). According to Haydu et al. (2002), zoysi a grass accounted for less than 2% of total Fl o rid a sod production but despite the small amount of acreage in com parison to St. Au gustinegrass and bahiagrass zoysiagrass has an overall worth of 12 million dollars and was expanding at the time Many zoysiagrass cultivars are currently used for reside ntial and commercial landscape and various areas of golf courses (Unruh et al. 2000). Zoysiagrass contains 11 species: Z. japonica Z. matrella Z. macrantha Z. tenuifolia Z. pacifica Z. sinica Z. planifolia Z. paucifolia Z minima Z. seslerioides and Z. macrostachya (Anderson, 2000) The two most commonly used zoysiagrass s pecies for turfgrass are Z. japonica and Z. matrella Zoysia japonica more commonly referred zoysiagrasses while Z. matrella

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15 leaf texture and overall is not as cold hardy. Zoysiagrasses exhibit favorable traits including ability to grow in humid, semi arid, and transitional zones. They can produce a low lying dense turf that is tolerant of shade, salt, and traffic. Zoysiagrasses also have few disease and insect pests Common pests include root knot ( Meloidogyne spp .) and sting nematodes ( Belonolaimus spp .), hunting billbugs ( Sphenophor usvenatusvestitus Chittenden ), mole crickets ( Scapteriscus spp .), dollar spot ( Sclerotinia homoeocarpa ), and large patch ( Rhizoctonia solani ) (Unruh, et al. 2007). Zoysiagrasses are adapted to a variety of soils, have good winter hardiness, and high temper ature tolerance (Beard, 1973). These traits make them desirable for use on residential and athletic turfs in the transition zone of the United States. In terms of establishment, zoysiagrasses exhibit slow growth habits resulting in lower mowing, water and fertilizer requirements in comparison to other warm season turf specie s (Ruemmele and Engelke, 1990). Z. japonica genotypes exhibit faster establishment rates than Z. matrella (Forbes and Ferguson, 1947; Patton et al. 2007). Once established, the dense sod surface of the zoysiagrasses aids in their defense against weed invasion The combination of these desirable traits makes zoysiagrasses a favorable choice for reduced maintenance landscape s. Despite low maintenance, limitations exist and include thatch production when over fertilized slow establishment and recovery from damage, and poor growth in compacted soils (Ruemmele and Engelke, 1990). Two important limitations of zoysiagrass and other warm season species of turf is their response to drought and shade stress.

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16 Drought le Water is required during the entire life cycle of a plant to maintain normal metaboli c and physiological functions Water is required along with carbon dioxide and light for photosynthesis to occur in plants. Water reductions are directly related to red uctions in photosynthesis rates (Boyer, 1970 ). Water is crucially important for the process of trans piration and nutrient uptake P lant s pull nutrient rich water from the soil, through the roots, into the plant, then to the canopy where it is released as v apor into the atmosphere serving as a cooling mechanism while supporting the continuous pull of nutrients into the plant system. Of the total water taken up by the root systems, ~90% is transpired from the leaves while only 1 to 3% is used for metabolic pr ocesses (Beard 1973; Hopkins 1999). T ranspiration on a single leaf basis is controlled by three major physiological factors: the vapor pressure gradient between atmosphere and leaf, boundary layer resistance, and internal leaf diffusion mechanisms. Vapor pressure gradient is affected by several environmental factors including temperature, solar radiation, humidity and wind The boundary layer is undisturbed air on the surface of the leaf blade that resists water loss from the leaf. Wider leaves have a grea ter resistance to water loss due to an increased boundary layer. Internal leaf diffusion resistance is controlled by stomata size and conductance cuticle layer thickness, leaf cell density, and leaf thickness. Leaves with large stomatal openings, thinner cuticles, loosely packed cells, and thinner leaf blades typically have higher transpiration rates Stomata transpiration accounts for 90 95% of water loss with cuticle transpiration accounting for 5 10% loss. Transpiration can occur at a rate faster th an water can be taken up by the plant. This causes turfgrass

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17 to lose its ability to dissipate radiant heat resulting in various drought stress responses (Huang, 2012). Drought Responses Variable drought stress responses have been observed among species a nd between cultivars of the same species in both warm season and cool season turfgrass es (Beard and Green, 1994; Ki m et al., 198 8; Beard and Sifers 1997; Fuentea l ba 2010 ). Controls of these responses are attributed to the genetic variability in growth and metabolic activities. Growth characteristics associa ted with water use include morphological and anatomical differences in leaves canopy configuration, growth rate, tiller or shoot density, and growth h abit (Be ard 1973; Huang and Fry 1999). Available genetic variability allows for selection and development of cultivars that resist drought stress and require less water inputs (Carrow, 1996 ; Hanks et al. 2005). To effectively breed superior drought resist ant cultivars, the mechanisms behind different drought responses must be understood. Physiological responses of turf to drought stress include drought avoidance, tolerance, and escape. Drought escape is the ability of a plant to escape severe drought stres s by entering a state of dormancy in which physiological function nearly halts (perennials) or through life cycle completion (annuals). Drought avoidance is the ability of the plant to avoid tissue damage during conditions that favor water stress and is po ssible through evapotranspiration ( ET ) control and root water uptake (Huang, 2008; Beard and Sifers, 1997; Levitt, 1980 ; Marcum et al., 1995 ). Some physiological responses associated with drought avoidance include reduced transpiration levels through redu ced stomata number and aperture, elongated roots with greater densities to store water and carbohydrates, increased root water uptake rate through increased

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18 surface area, maintaining root plasticity, decreased leaf growth, enhanced leaf pubescence, and lea f rolling or folding. Drought tolerance is influenced by mechanisms that aid in maintaining turgor pressure or protoplasmic resistance during drought stress. These p hysiological mechanisms include osmotic adjustment to maintain membrane stability and the accumulation of proteins and other metabolites directly associated with cell production (Huang, 2008). A wide range of turf species and methods have been used to furt her understand drought avoidance ( Kim et al., 198 8 ; Beard and Sifers 1997; Johnson et al., 2009; Fuentealba, 2010; Marcum et al. 1995; Poudel et al., 2010 ) and tolerance ( Huang, 2008 Ki m et al., 198 8; Beard and Sifers 1997 ) in an effort to reduce water use through breeding. Previous Drought Avoidance Research Wilting and Leaf F iring Kim et al. (198 8) revealed differences in drought resistance betwee n eleven warm season turfgrass species which include d 22 bermudagrass, five St. Augustinegrass, six zoysi agrass, and four centipedegrass ( Eremochloa ophiuroides [Munro] Hack .) cultivars which w ere evaluated at Texas A&M University. Each entry was grown on a 30 inch deep sand root zone over eight inches of gravel in a randomized block design. Irrigation was withheld for 48 days. Drought resistance amongst entries was measured by the amount of leaf firing that occurred during the drought period and the time required for shoot recovery. Significant differences in shoot recovery an d leaf firing ex isted within species and between cultivars Z oysiagrass and centipedegrass genotypes showed good to excellent drought resistance while St. Augustine and bermudagrass showed larger amounts of variation. In addition, Kim et al. (1988) determined there was a n opposite relationship present

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19 between leaf firing and shoot recovery. Those genotypes that turned yellow or brown earlier in the drydown had poorer post drought shoot recovery. Beard and Sifers (199 7 ) evaluated both bermudagrass and zoysiagrass for differences within and between species for drought avoidance. The study was conducted on mature plugs grown in 100% sand at the Texas A&M University Turfgrass Field Research and Teaching Laboratory in College Station, Texas The plugs were planted in March of 1998. In May, a 158d dry down event was initiated with no supplemental irrigation applied from 1 May to 6 October (75 mm of rainfall occurred during this period). Leaf firing was visually rated and used to assess dehydration avoidance. Bermudagras s had overall better drought avoidance and resistance than zoysiagrass based upon leaf firing percentages D ifferences among genotypes within species were also reported indicating that genotypes with improved drought responses of both species cou ld be sele cted in comparison to bermudagrass genotypes, was contributed to their entry into dormancy earlier which allowed more time for internal tissue water stress to develop Steinke et al. (2009) conducted a 6 0 day dry down over the course of two years through the use of an automated rain out shelter to understand heat accumulation impacts on urban landscapes with limited water inputs Canopy temperatures and leaf firing of three turfgrass species and 24 total cultivars were measured in San Antonio, Texas. Eight cultivars of bermudagrass, seven cultivars of St. Augustinegrass, and 9 cultivars of zoysiagrass were selected. Cultivars were selected based upon commercial availability in San Antonio. Zoysiagrass acc umulated and retained heat more quickly than St. Augustine and bermudagrass. Bermudagrass maintained a lower overall leaf

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20 firing rate than zoysiagrass and St. Augustinegrass. Zoysiagrass es showed higher leaf firing than bermudagrass es and St. Augustinegra ss es Steinke et al. suggested that similar drought stress responses between St. Augustine and bermudagrass could be contributed to enhanced heat dissipation through greater evapotranspiration. n elevated boundary layer preventing transpiration. Overall, results indicated that restrictions of water use resulted in turfgrass systems losing the ability to buffer radiant heat as they become desiccated from reductions in soil moisture. Transpiration. Ebdon and Petrovic (1998) compared morphological and growth characteristics of 61 Kentucky bluegrass ( Poa pratensis L.) cultivars in relation to water use. Two entries were randomly selected from the 1990 low maintenance National Turfgrass Evaluation Program (NTEP) and 59 entries selected from the 1990 medium high maintenance NTEP variety trial. Each genotype was seeded in to a 20 cm diameter lysimeter. Water use of each cultivar was determined by placing a rep into one of three controlled environment chambers. The temperatures where preset at 25, 30, and 35 C to represent a range of evaporative demand s Based upon the results, cultivars were categorized as either exhibiting high or low water use. Differences in ET were attributed to ho rizon tal leaf orientation, shoot density, and vertical leaf extension rates. Low water use cultivars showed slower leaf extension rates, a higher shoot density, and a more horizontal leaf orientation with narrower leaf texture. Johnson et al. (2009) examined the transpiration rates and normalized difference vegetation index ( NDVI ) responses of six seashore paspalum ( Paspalum vaginatum Swartz ) genotypes to soil drying in a greenhouse at the University of Florida (UF) in

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21 2006. Cul tivars were grown in pots filled with sand or organic soil as the medium. Normalized difference vegetative index (NDVI) measurements along with weights to determine the fraction of transpirable soil water (FTSW) were taken daily to asses dry down respons es. The study suggested that there were no significant differences amongst genotypes in regards to daily NDVI and ET but differences did exist between transpiration breakpoints. These differences could account for conservation of water use and stress tolerance during times of water deficits. Fuentealba (2010) observed differences in both daily transpiration rates and root depth development through a two part study conducted in Gainesville, FL. Nin eteen genotypes of five warm season turfgrass species were evaluated for differences in transpiration rates under controlled greenhouse conditions. The study contained ten replications of each genotype with four pots remaining well watered while six were p laced under a controlled dry down Daily transpiration rates, wilting ratings, average normalized transpiration rate (NTR), FTSW, total transpirable water (TSW), and days to reach the endpoint were recorded. It was observed that some genotypes respond ed to soil drying by decreasing their transpiration rate early in the dry down while others maintain ed a consistent rate longer in to the dry down cycle. Most zoysiagrass genotypes, in comparison to the other warm season species, maintained their transpiration rate longer into the dry down cycle along with variable wilting responses and respectively high and low break point values. This variat ion in break point values could allow for cultivar selection and improvement. Rooting R esponses. Fuentealba (2010) evalu at ed rate of root depth development (RRDD) of twenty six genotypes from eight warm season turfgrass

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22 species. The study used clear acrylic tubes with a depth of 122 cm by 6.4 cm diameter filled with 80% USGA spec sand and 20% peat mix. Each genotype was pla nted using a soilless 5 cm plug and allowed to grow for 60 days. Root depths were measured twice a week during these 60 days to determine RRDD. Roots were then s ectioned into 30cm increments, rinsed and then scanned using WhinRizo software (Regent Instruments, Nepean, ON, Canada) to determine root length (cm) and volume (cm 3 ) Samples were then dried and weighed. Conclusions were that within the Zoysia spp., Z. japonica had a significantly higher RRDD compared to Z. matrella Zoysia spp overall had lower volume, total root length density ( RLD ), and root dry weight than centi pedegrass, common bermudagrass, carpetgrass ( Axonopus affinis Chase ) and St. Augustinegrass. The improve ment of zoysiagrass cultivars with regard to water use would contribute t o the already existing desirable characteristics. Marcum et al. (1995) also used root tubes to evaluate rooting characteristics of 25 zoysiagrass entries in an attempt to make an association between roots and drought resistance. Twenty five mm diameter pl ugs were planted into individual translucent tubes and maintained for 16 weeks. They reported Belair Crowne El Toro Emerald, Marquis Meyer, and Palisades as having the highest average maximum rooting depth (AMRD) while Diamond Royal Cavalier and Sunburst had the lowest AMRD. They also concluded that AMRD was directly related to survival under severe (0% ET) to moderate (35% ET) water deficit indicating that zoysiagrass es survive d by maintaining high tissue water potential through de eper rooting. Poudel et al. (2010) looked at root archit ecture using polyethylene tubes in a greenhouse study conducted at Oklahoma State University Turfgrass Research Center

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23 in Stillwater, OK. Five replications of eight bermudagrass entries were arranged in a randomized complete block design. Turfgrasses evaluated fritted clay that had previously been screened to maintain only 1 2mm diameter part icles. Root extensions were measured weekly until the maximum root depth of 120 cm was achieved by one of the tubes. Each entry was then divided into 6 sections, rinsed, and scanned using Win Rhizo software. There were no significant differences between en tries for total root length (TRL) from 0 120 cm, root surface area (RSA from 0 120 cm) or visual turf quality (TQ) E ntries however, showed significant differences for average root diameter (ARD), root volume (RV), shoot dry weight (SDW), root dry weight (RDW), and root shoot ratio (R/S). Based upon the results of this study, it was apparent that some genotypes posed a greater genetic potential for improved drought performance. Shade Irradiance Components Under shaded conditions, both quality and quantity of light are reduced (Beard, 1997). P hotosynthetical l y active r adiation (PAR ) is the visible portion of light that falls between 3 80 and 70 0 nm that can be absorbed by leaves and used for photosynthesis (Beard 1997). Photosynthetically active radiation is measured quantitatively as photosynthetic photon flux d ensity (PPFD ) Unfiltered direct light has a total PPFD of about 1900 umol m 2 s 1 (Cockerham et al., 2002) ; however, considerably less irradiance can reach the turf surface depend i ng on the shaded environment. The amount of shade affecting absorbed radiation is most often impacted by buildings, fences and tree species ( Massey, 1970 ). An important aspect of shade when caused by trees is the

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24 presence of sun flecks which are irregularl y shaped spots of full sunlight that reach the turf canopy each diurnal cycle (Beard, 1973; Evans, 1956). Mobile sun flecks are a significant source of radiation; however, measuring the irradiance of a single spot in a naturally shaded condition is very di fficult (Beard, 1997). Light quality refers to the ratios of different wavelengths present in a light environment. Blue, green, and red wavelengths are responsible for photosynthesis Turfgrass quality increases as blue and green wavelengths increase in co mparison to far red ratios (McBee, 1969). S hade results in a higher percentage of far red wavelengths (> 700 nm) and a decreased percentage of red and blue light wavelengths responsible for normal turf development (Anderson, 1964; Evans, 1939). Effects fro m reduced light quality are observable but co nsidered to be less important than light quantity and the duration of shade exposure (Beard, 1973). Shade Responses Shaded conditions lead to a lighter green color, elongated internodes, reductions in shoot and root weights, a lo wer root:shoot ratio, and longer thinner leaves. These whole plant responses to shade can be partially attributed to poor stolon and rhizome growth that arise from active axillary buds in the crown of the plant. The activity of axillary buds is significantly influenced by environmental factors such as sunlight and temperature Traffic damage and disease also result from shade due to reductions in photosynthesis ( Qian and Engelke, 1997 ). Carbohyd rate synthesis and allocation are other majo r factor s influencing turfgrass performance under shade. Burton et al. (1959) stated that 70% shade can reduce carbohydrate synthesis by 43% in forage Coastal bermudagrass The reduced carbohydrates and root:shoot ratios that occur under shade increases the susceptibility of turf to damage from w ear, insects and diseases,

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25 and red uces its ability to recuperate ( Wilson 19 97 ).Therefore, selective criteria for shade tolerance could include measurements of leaf and stem width, leaf length, plant height, shoot density, internode lengths, and leaf orientation (Beard, 1973 ; McBee and Holt, 1966; Peacock and Du deck, 1981; Wherley et al., 2011 ; Wilkinson and Beard, 1974; Winstead and Ward, 1974). Previous Shade Tolerance Research Growth H abit. Qian and Engelke ( 1997 ) evaluated 19 zoysiagrass cultivars (commercial, experimental, and interspecific hybrids) under shade. All entries were included in the 1996 NTEP trial. For the study, entries were vegetatively planted in 9 9 8 cm plastic pots, and then maintained in 70% sunlight for more than 30 days prior to the shade treatment. The experiment was conducted over 11 weeks in a greenhouse using pots placed under 0.5 1.5 0.5 m frames with 40%, 75%, and 88% shade. Diamond, DeAnza Palisades, along with three experimental lines, TAES 4377, TAES 4373, and TAES 4365 produced the greatest number of buds at the 88% shade treatment. These cultivars all showed a growth habit shift from horizontal to more vertical as the shade increased due to increasing internode len gths. However, Diamond exhibited shorter internodes, less of a decrease in shoot or r oot biomass, less of an decrease in root:shoot ratio and maintained a green er color. Chlorophyll C ontent and R oot L ength. Baldwin e t al. (2008) evaluated 42 bermudagrass c ultivars selected from the 2002 NTEP trial in a reduced light environment. All genotypes were subjected to 0% shade an d 64% artificial shade for 60 days. This two year greenhouse study was conducted at Clemson University in 2005 and 2006 and used cone tain ers filled with 85% sand and 15% peat as the grow medium. Turfgrass qual ity ratings were recorded four and eight weeks after initiation of

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26 shade stress and were based on a combination of color, density, texture and uniformity. Chlorophyll (mg g 1 ) was reco rded at week four and eight along in addition to root biomass (g) and length (cm) determined at the end of the study. Baldwin et al. (2008) observed a reduction in turfgrass quality below the acceptable levels by week four along with a significant variatio n in chlorophyll concentrations at both four and eight weeks. Root length was the least affected of all parameters: however, each cultivar showed a significant decrease in root biomass. Establishment. Sladek et al. (2009) used plant diameter, percent cover, and overall turf quality ratings to distinguish the level of shade adaptation between six zoysiagrass cultivars including Meyer, Shadow Turf Diam ond, DALZ 0501 Zorro and Emerald. Plugs of each culti var measuring 2.5 cm 2 were planted in 3.8 L plastic pots and allowed to grow in full sun for one week prior to shade treatment. Shade treatments included 0%, 50%, and 90%. Lateral plant diameters were taken every two weeks for the 12 week duration of the s tudy. Percent turf cover and turfgrass qu alities were collected every two weeks The results showed that Shadow Turf and Diamond exhibited the highest turfgrass quality and acceptable increases in lateral diameter when grown under 50% shade when all other genotypes were less than acceptable and showed unacceptable lateral growth. These results identified variation for shade responses among the cultivars studied. Cultural P ractices. Cultural practice must also be kept in mind when maintaining acceptable turf under shaded conditions. Ries et al. (2002) identified cultural practices that help ed to maintain acceptable DeAnza zoysiagrass under traffic in shade and full sun environments. Shade was created by constructing a superstructure of opaque

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27 louvers running north to south allowing for a seasonal time pattern of shade and light ranging from 4.5h d 1 in the early spring and 6.5h d 1 in t he mid summer. Three mowing heights of 0.3, 1.9, and 2.5 cm were used with biweekly nitrogen applications that totaled at 53, 106, and 159 kg N ha 1 mo 1 (1.0, 2.0, and 3.0 lbs/1000ft 2 mo 1 ). Traffic was simulated by releasing baseballs from a JuggsTM baseball pitching machine set at a maximum speed of 145 km/h 1 .5 m above and 4.9 m away from the impact zone at an angle of 12 14 which resulted in significant turf damage. Re sults showed that the shaded De Anza recovered significantly better at the 1.9 and 2.5cm mowing heights in comparison to the 0.3cm height with the higher ni troge n rates having a positive e ffect when used with favorable mowing heights. I n full sun plots the 159 kg N rate showed the lowest injury with 1.9 cm mowing height. These results relate to Bell and Danneberger (1999) who stated that increasing mowing heights leads to increased leaf area, photosynthetic activity, and carbohydrate accumulation Current Efforts The negative impacts of shade and drought conditions could be reduced through selection and development of species and cultivars of turfgrass that can ei ther avoid or tolerate drought stress and maintain vigor through adequate tillering, stolon, and rhizome growth under shaded conditions. The majority of research on drought and shade involves the evaluation and comparisons of existing commercial cultivars. More effort is needed with respect to evaluating germplasm and breeding to improve these important characteristics. Objectives The objectives of this study were : 1) to identify zoysiagrasses with improved dry down responses (those that maintain better aes thetic value) and 2) to identify

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28 zoysiagrass es with improved shade responses (those that maintain similar growth patterns between full sun and shaded environments).

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29 CHAPTER 2 FIELD DRY DOWN RESPSONSES OF 65 ZOYSIAGRASS GENOTYPES Background Maintenance of acceptable turfgrass can be difficult during periods of limited water Drought condition s and population growth have resulted in restrictions for i rrigating landscapes, golf courses and residential lawns in many parts of the United States (Morris, 2007 ). I n 2010, the City of Tampa FL water management district i mplemented a wa ter restriction ordinance ( Section 26 97 ) Th is ordinance stated that address numbers determined the two days a week that lawns could be irrigated and that irri gation should be low volume, unless f rom a reclaimed source. In addition wasteful use of reclaimed water as determined by the city, could result in a penalty (City of Tampa Water Management District, 2010). O rdinances similar to the one previously stated are being implemented in the state of Florida due to a lack of available water during periods of limited rainfall (St. Johns Water Management District, 2010) Unfortunately, limiting irrigation during periods without precipitation can lead to a loss of turf cover and impacts the aesthetic value and functionality (i.e. soil stabilization) of landscapes ( Huang, 2008 ). Improving the drou ght resistant mechanisms in turfgrass is a desirable strategy to compensate for limited rainfall, watering restrictions and to increase the sustainability of the turfgrass industry. Zoysiagrass ( Zoysia spp .) is becoming an increasingly important turfgras s species, favored for its high turfgrass quality and adaptation to a wide range of environmental conditions. It is adapted from the southern region of the United States to the northern transition zone and forms a dense, uniform turf through the production and spread of rhizomes and stolons (Turgeon, 2008). Unfortunately, zoysiagrass has proven through

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30 research to lack favorable drought responses in comparison to other warm season t urfgrass species (Kim et al., 1988; Beard and Sifers, 1997; Carrow, 1996). W hen water is limited z oysiagrass can quickly enter into a state of dormancy which causes immediate reductions in quality (Beard and Sifers, 1997). H owever, v ariations in drought response exist within zoysiagrass allowing potential for improvement (Fuentea lba, 2010; Marcum et al., 1995). Vari ability in drought responses have been associated with color (Zhao et al., 1994; Steinke et al., 2009; Kim et al., 1987), density (Giesler et al., 1996), quality (Fu et al., 2004; Qian and Engelke, 1999 a ; 1999b; Steinke et al., 2009), leaf firing (Kim et al., 1988; Beard and Sifers 1997 ; Carrow and Duncan, 2003; Kim et al., 1987), and percent green cover (PGC) also referred to as percent living color (Steinke et al., 2009). The objective of the present study is to quantify differences between zoysiagrass genotypes for their whole plant responses during periods of limited water and to identify those genotypes th at maintain higher aesthetic value. Materials and Methods Location and Material Plant Science Research and Education Unit Fifty four experimental lines of Z. japonica and Z. matrella were selected in 2008 from larger replicated germplasm nurseries previously located at the University of Florida Plant Scien ce Research and Education Unit (PSREU) located near Citra, Florida (29.408872, 82.16574). The fifty four experimental lines along with eleven commercial cultivars (Table 2 1) were plant ed in the fall of 2007 using 10 .0 cm plugs on 91.4 cm centers in a randomized complete block design with five replications in a Candler sand (hyperthermic, uncoated Lamellic Quartzipsamment). Plots were irrigated 20 minutes, three times per week to prevent moisture stress, mowed once a week at 8.25 cm height

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31 of cut and fertilized using a 15 5 15 (N P 2 O 5 K 2 O) mixture of a release polymer coated Release Fertilizer, Agrium Advanced Technologies, Lakeland, FL) and an imm ediate release Carpetmaker fertilizer (Southern States Cooperative, Richmond, Virginia) at a n N rate of 49 .0 kg N/ ha 1 every 60 days during the growing season. In 2011 mole crickets ( Scapteriscus borellii Giglio Tos) were controlled using Allectus (Bayer Crop Science) at a rate of 100 lb/ acre Two dry down studies wer e conducted on established plots with the first study initiated 6 September 2010 and the second study 7 May 2011 The 2010 dry down in PSREU was completed in 18 days while the dry dow n at PSREU in 20 11 required 20 days. Dry downs were halted once a large majority of genotypes had a uniform brown and dormant appearance. Between studies, the plots received supplemental irrigation three times a week to a depth of 0.32 cm to ensure adequate recovery. Recovery prior to initiating the second dry down event was considered adequate when all plots had uniform green cover. Agronomy Forage Research Unit The same experiment described above was planted in June 2010 at the Agronomy Forage Rese arch Unit (AFRU), Hague, FL (29.410663, 82.173328) under a rainout shelter in a Pelham (Loamy, siliceous, subactive, thermic Arenic Paleaquults ) Mulat (Loamy, siliceous, subactive, thermic Arenic Endoaquults) soil which is described as approximately lev el and poorly drained. They are sand for the initial 50 100 cm and then loamy underneath Plots were planted as de scribed above at PSREU mowed at 8.25 cm irrigated for 15 minutes three times per week to prevent stress and fertilized using a 15 5 15 (N P 2 O 5 K 2 O) mixture of a release polymer Polyon Controlled Release Fertilizer, Agrium Advanced Technologies, Lakeland, FL)

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32 and an immediate release Carpetmaker fertilizer (Southern States Cooperative, Richmond, Virginia) at a N r ate of 49.0 kg N/ ha 1 every 30 days to encourage rapid establishment. Two dry down cycles were imposed on these plots with the first cycle initiated 15 Octobe r, 2010 and the second 5 June 2011. The 2010 and 2011 dry down s required 18 and 27 days respectively. Supplemental irrigation was provided three times to a depth of 0.32 cm as described above to ensure plot recovery between dry down periods. Dry downs at AFRU were halted once a majority of plots showed moderate decline in appearance. Data Tur f ratings for PSREU and AFRU were conducted using both visual ratings and digital image analysis every third day during active dry down s. Digital images were collected for percent green cover (PGC) using a ~ 0.3 m 0.3 m 0.3m light box. The light box co ntained an internal light source, ( Compact fluorescent light Longstar Lighting Co., Fujian, China ) to provide a consistent light to eliminate image differences that might result from taking pictures under natural daylight. Once images were collected, they were analyzed as described by Karcher and Richardson (2003) and Richardson et al. (2001). Visual ratings were taken for color, density, leaf firing, and overall turfgrass quality using the NTEP (National Turfgrass Evaluation Performance) 1 9 scale of perf ormance (1= brown or dead plots and 9= excellent) (Morris and Shearman, 2006). It should be noted that density refers to the persistence of leaf cover (dormant or active) within the plot and should not be confused with percent green cover of plots. Therefore, a dormant plot could have been relatively dense but have very low percent green cover.

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33 Statistical Analysis Data were analyzed using the SAS statistical package for Windows (SAS Systems for Windows Version 9.2, SAS Institute Inc. Cary, NC, USA) using the PROC GLM procedure. Least square means were estimated and tested for significant differences between species and genotypes at an alpha level of 0.05. The sources of variation included for the complete model were: rep location, genotype locat ion, genotype, genotype rep location, location year, genotype year, genotype location year (Table 2 2). The pooled analysis produced a significant genotype location interaction for all measured traits. Therefore, models were developed for ea ch location with years pooled. At AFRU, year genotype interactions were not significant for any parameters, except for quality ratings at the beginning of the dry down; therefore all data was combined across years (Table 2 3). At PSREU, genotype year i nteractions were significantly different for all traits (Table 2 4). As a result PSREU data was analyzed by year (Tables 2 5 and Table 2 6). Interpretation of data was based on mean g enotype performance at the initiation and termination of dry down periods G reater emphasis was placed on the final ratings at the time of dry down termination and on the mean percent change that occurred within each genotype between initial and final ratings. Percent change was calculated as follows: [ ( final rating initial r ating)/initial rating ] *100 Percent change was only calculated for those parameters in which genotypes were different for their final rating. least significant difference. A total turfgrass performance index (TTPI) table (Wherley et al., 2011) was generated to identify those genotypes that perform ed in the top statistical

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34 group, for final ratings and percent changes, for color, density, quality, leaf firing, and % green colo r Results and Discussion AFRU Results T here were no significant differences between genotypes for color, quality, leaf firing, or PGC at the end of the dry down s across years at AFRU (Table 2 3) The lack of significant differences for leaf firing and PGC at the end of the dry down may be at tributed to the soil seri es at AFRU. The Pelham Mulat soil contained an impermeable horizon high in clay content th at created a perched water table. Despite t he AFRU study occurring under a rainout shelter the perched water table allowed for subsurface lateral water movement underneath the shelter causing a gradual dry down We hypothesize that the lateral water movement limited drought stress and provided tim e for all genotypes to acclimate to reduced water availability resulting in narrow ranges for leaf firing and PGC that were not statistically different. No differences for leaf firing and PGC prior to dry down were as expected si nce plots were not yet exhi biting drought stress. Differences for genetic color among zoysiagrass genotypes have been frequently reported during periods of severe environmental stress such as drought ( Zhao et al., 199 4; Steinke et al., 2009) and with no environmental stress (Morris, 1996, 2001, 2007 ). In contrast, no color differences were observed in our study. A potential contributing factor could have been that the AFRU plots were relatively new and not well established when the first dry down was initiated (in comparison, PSREU plots were planted two years prior to the ir first dry down ). Because the AFRU plots were still establishing they were fertilized more frequently to promote spreading. Therefore, genetic color

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35 differences were likely masked by N fertilization. Residu al N could have carried through to the second dry down Significant differences in quality existed between genotypes prior to the initiation of dry down but these differences were not present when the dry down was terminated (Table 2 3). This difference pr ior to the dry down can be at tributed to differences in uniformity of plots, which was a function of variable establishment rates (not rated). As the dry down progressed, these immature plots appeared to direct energy resources to new growth during the dry down as opposed to supporting established tissue resulting in less uniform plot coverage. Therefore, due to poor cover and desiccated tissue all plots had poor quality and genotypes did not differ when the dry down concluded. Reductions in color, uniform ity, and quality of zoysiagrass under drought stress have been previously documented (Steinke et al., 2009). Differences for density did exist between genotypes prior to and at the end of the dry down Loss of density resulting from drought stress in zoys iagrass has been previously reported (Steinke et al., 2009). Final density among genotypes ranged from 3.8 to 6.0 with 24 entries having a final rating greater than 5.0 indicating that several genotypes maintain ed relatively decent density through a prolonged period of drought (data not shown). However, no significant differences for density were observed for percent changes in density among genotypes (Table 2 8) High density values at the end of the drought and a lack of differences for percent chan ge are, again, likely due to subsurface lateral water movement and zoysiagrass acclimation to limited available water.

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36 PSREU There were significant differences in PSREU 2010 and 2011 for color, density, quality, and PGC ratings (Tables 2 5 and 2 6). Differ ences in leaf firing occurred only in 2011 (Table 2 6). Differences prior to dry down initiation can be at tributed to genetic differences amongst entries under non stressed conditions which were similar to several previous reports of zoysiagrass performanc e (Morris, 1996, 2001 ). The differences at the end of the dry down should be due to variable genotypic responses to dry down and are similar responses to those reported by White et al. (1993) Marcum et al. (1995), and Steinke et al. (2009).Differences at the termination of dry down were of greater value; th erefore, the following discussion will focus on the final ratings and percent changes through drought periods. Final color ratings ranged from 3.2 to 6.4 in 2010 and from 2.0 to 6.0 in 2011 (Table 2 12 ). There were several genotyp es with color ratings above 5.0 indicating that s ome genotypes of zoysiagrass were able to maintain better color through the both drought period s Percent changes in color ratings were significant (Table 2 10 and Table 2 11 ) and decreases ranged from 21 to 52% in 2010 and from +1 to 63% in 2011 (Table 2 12 ) i nd icating that some entries were relatively less affected by drought Three Z. japonica entries TAES 5331 ranked in the top statistical gro up for percent difference and final ratings for color i n both 2010 and 2011 (Table 2 17 ). Final d ensity ratings ranged from 3.8 to 6.4 and from 4.4 to 7.0 in 2010 and 2011 respectively (Table 2 13 ). Several genotypes from both years had final density rat ings greater than 5.0 indi cating that many zoysiagrasses, did not drastically decline in density due to drought stress Differences among genotypes for changes in density

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37 ranged from 1 to 42% in 2010 and from a gain of 14% to a de crease of 49% in 2011 (Tab le 2 13 ). Therefore, some genotypes did not change (may have improved) in density through the drought period. Three entries Z. Japonicas TAES 5257 8, ranked in the top statistical group for percent differenc e and final ratings for density in both years (Table 2 17) Final mean quality ranged from 3.6 to 5. 2 and 2.6 to 5.2 in 2010 and 2011 respectively (Table 2 14 ) Only a few entries had quality greater than five indicating that the dry down periods were more detrimental to overall quality than color and density. Changes in quality ranged from 22 to 49% in 2010 but were not significant in 2011 (Table 2 14 ). Plots at PSREU 2011 had noticeable mole cricket damage prior to initiation of dry down. The average initial quality ratings betw een 2010 and 2011 were not different, but percent green cover was less in 2011 at the time of dry down initiation (data not shown). Because mole crickets feed on roots, their presence could have impacted final dry down ratings in 2011. Mole cricket damage could have severely hinder ed the aesthetic value an d functionality of the turf Several entries ranked in the top statistical group for percent differences (2010) and final ratings (2010 and 2011) of turf quality T hose entries include d seven Z. japonica s : 12; and one Z. matrella, Z. matrella by phenotype) (Table 2 17) Percent green cover (PGC) final ratings ranged from 11 to 97% in 2010 and from 3 to 32 % in 2011(Table 2 15 ). Changes in PGC in 2010 ranged from 1 to 87% and 47 to 93% in 2011. No entries were identified that ranked consistently high for final dry down PGC and changes in PGC between years at PSREU (Table 2 17) This indicates that

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38 considerable genotype environm ent (GE) interaction occurred for PGC between years. T he ranges reported above for color density and quality were similar for both years; whereas, the PGC ranges for both years were very different. It must be considered that the reduced mean values for PGC in 2011 and the lack of consistent observations (GE) were due to mole cricket damage (described above) prior to dry down initiation. Leaf firing resulting from drought stress has been shown to occur rapidly in zoysiagrass (Steinke et al., 2009; Kim et a l., 1988, Beard and Sifers, 1997 ). Final leaf firing ratings in 2011 were significant (Table 2 11) and ranged from 2.8 to 5.4 and percent changes r anged from 12 to 62% (Table 2 16 ). Thirteen entries ranked in the top statist ical group for percent difference and final ratings for leaf firing in 2011 (Table 2 17 ) Four were Z. japonicas (BA 182 DALZ 8516, BA 188, and TAES 5330 23) and nine were Z. matrellas 358, BA 1 23, and BA 336). A summative total turf performance index ( T TPI ) table (Table 2 17 ) was developed to provide a turf performance index (Wherley et al., 2011) value for each genotype across all parameters and years at PSREU that showed significant differences for both percent differences and final dry down rating s Difference performance index (DPI) value was the number of parameters a genotype ranked in the top statistical group for percent differences. F inal performance index value was the number of parameters a genotype ranked in the top statistical group for final ratings. Each genotype received a DPI and FPI value. There were nine parameters included in the FPI portion and eight

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39 parameters in the DPI portion resulting in a maximum TTPI value of 17. No genotypes performed in the top statistical group for all parameters T he T TPI table provided a clear representation of which genotypes were able to avoid drought induced damage by either maintaining a higher rating throug h drydown for a given param eter, by minimizing percent change of a parameter through drydown or a combination of both Total t urf performance ind ex values ranged from 0 to 11 S ix entries had a TTPI value of 9 10, or 11 all of which were Z. japonicas Those entries with a TTPI of 9 were TAES 5257 8, TAES 5331 34, and Meyer. E ntries with a TTPI value of 10 include d DALZ 8516 and JaMur E ntry BA 182 was the only genotype with a TTPI of 11. The differences in color, density, quality, leaf firing, and PGC seen between genotypes in the current stu dy can be explained through both differential drought avoidance and tolerance responses. Zoysiagrass will enter a dormant state as part of a dehydration tolerance strategy when soil moisture becomes too limited; however, brown turf is not curren tly acceptable in most landscape settings The refore, the purpose of this study was to identify genotypes that were able to avoid dormancy through the utilization of processes that aid the plant in maintaining improved aesthetic value during periods of lim ited water availability. Dehydration avoidance techniques include evapotranspiration (ET) control or root wate r uptake (Beard and Sifers, 1997 ) and al though both contribute to plant survival, hydration involves two separate descriptions of avoidance: 1) the water savers, those that avoid dehydration by water conversation; and 2) the water spenders, which avoid dehydration by extracting

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40 more water through the root system to compensate for the wa ter used through transpiration to maintain active shoots (Maksimov, 1929) Genotypic c olor in the current study offers information of the overall health of the remaining tissue and how this tissue was kept alive. Zhao et al (199 4) conducted a study on cool season grass species including tall fescue ( Festuca arundinacea Schreb.), Kentucky bluegrass ( Poa pratensis L.) and perennial ryegrass ( Lolium perenne L.) using pots Zhao et al. (1994) showed that lower ET during times of water deficit always result ed in a greener color indicating superior drought resistance. Zhou et al. (2009) conducted a study on bermudagrass genotypes also using pots and further explained that those genotypes that showed reduced ET early in the stages of dry down maintained a gree n color and survived longer in to the dry down In the current study, similar observations where made with a number of genotypes showing smaller reductions in color than observed in other genotypes (Table 2 12) Perhaps these genotypes can maintain reduced ET rates longer into a dry down cycle. Steinke et al. (2009) showed that zoysiagrass accumulated heat and had higher canopy temperatures than St. Augustinegrass ( Stenotaphrum secundatum [Walt.] Kuntze) and bermudagrass during a 60 day dry down T he elevat ed canopy temperatures observed by Steinke et al. (2009) were the result of decreased transpiration rates of zoysiagrass relative to St. Augustinegra ss and bermudagrass. They also reported that leaf firing and loss of color and quality caused by reduced tr anspiration rates was much greater in zoysiagrass than the other species. Therefore, the variable color and leaf firing (Table 2 1 2 and Table 2 16 ) responses observed in this ce

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41 This dehydration avoidance may be attributed to continued water use and/or green leaf retention through ET control during continued drought stress ( Beard and Sifers 1973). Those entries (the water spenders) that limit leaf wilting and firing avoid tissue damage and increased canopy temperatures through continued trans pi ration ( Beard and Sifers 1998). Those g enotypes (water savers) that can retain color and wilt without firi ng regulat e their ET in order to tolerate limited available water and increased tissue temperatures. According to Marcum (1995), tho se entries considered as superior rooters (maximum root depth, total root weight, and root numbers at a lower depth) w ere th ose that maintained PGC the longest Percent green cover has been used as a tool to quantify drought response. Recently this parameter has been reported as being able to more accurately quantify visual color differences and living green cover among zoysiagrass ( Zoysia japonica Steud.) and creeping bentgrass ( Agrostis palustris Huds.) through analysis of digital images (Karcher and Richardson, 2003 ) E ntries with the ability to maintain better color, density, quality and PGC can be at tributed to con tinued transpiration (Steinke et al., 2009 ) and ET control ( Beard and Sifers 1973) This would contribute to lower canopy temperatures and contribute to the preservation of color, density, quality, and PGC along with resisting leaf firing. H owever, in order for turfgrasses to maintain transpiration during times of no precipitation water deeper in the soil profile must be accessible. Accessibility to water through root branching at lo wer soil profile depths can be considered an important drou ght resistance characteristic (Kramer, 1983). Deep rooting along with other rooting characteristics (total root number, num ber per profile depth, weight) and their relation to

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42 percent green plot cover also referred to as PGC has been studied in 25 zoysia grass entries by Marcum et al. (1995). Eleven of the 25 entries were included in previous field dry down studi es and rated for percent green plot cover (Morton et al., 1991; White et al., 1993). Five of the eleven entries that were evaluated in the field a nd glasshouse experiment were considered to be drought resistant because of their superior roots. They exhibited larger average maximum root depth ( AMRD ) total root weight, and root numbers at lower depths. This allowed Marcum et al. (1995) to suggest connections between rooting characteristics and field drought response In the current study, two separate TPI tables where created to access genotypic response to drought, one for final dry down ratings and one for percent difference. The value s of these two tables were added together to produce an overall total turf performance index (TTPI) value. It is important to note that both methods of accessing drought responses should be taken into consideration especially in the presence of additional environmental stresses (e.g. mole crickets in 2011). Final ratings present valuable information but if additional environmental stresses are present, then final values are not entirely representative of a genotypes performance during drought stress. Theref ore, by using percent differences, genotypic performance was accurately depicted assuming decline in performance was directly related to limited water availability only In the current study, TTPI values ranged from 0 to 11 and entries w ith a T TPI value of 9 11 exhibited superior resistance to drought stress over other cultivars The ab ility of these genotypes (BA 182, TAES 5257 8, DALZ 8516, TAES 5331 34, Meyer, and JaMur) to resist large percent changes and maintain high final ratings acr oss a majority of parameters may be attributed to ET control ( Beard and Sifers

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43 1973; Zhao et al 1994; Zhou et al., 2009) and rooting characteristics (Marcum et al., 1995); however, further research should be conducted to confirm their method of resistance to drought stress. Summary Of the two sites used for conducting dry down s, PSREU proved to be more effective at identifying significant differences between genotypes for color, density, quality, leaf firing, and PGC. The presence of t he impermeable horizon at AFRU allowed for subsurface movement of water into the rainout shelter that allowed the majority of plots to access water during a time that was intended to be water limiting. As a result, genotypes as a whole were able to adapt t o a somewhat water limited environment and never reached a level of drought stress observed at PSREU in 2010 and 2011. PSREU allowed for the separation of entries based upon varying responses to drought, although mole cricket damage may have impact ed 2011 results. Previou s research conducted on turfg r a ss performance under drought stress has looked at initial and final visual ratings of leaf firing (Jiang and Carrow, 2005; Steinke et al 2009), quality (Jiang and Carrow, 2005; Steinke et al 2009), and color (Steinke et al 2009) to separate genotype performance P erformance in the current study was based upon the percent difference between ratings taken at the initiation and termination of the dry down and final ratings (Table 2 1 7 ). These methods prov ed to be an effective approach except for percent differences in leaf firing in 2010 and for quality in 201 1. P revious research has focused on days to reach an unacceptable rating (e.g. color 5) (Steinke et al., 2009, Jiang and Carrow, 2005). This appro ach was attempted, but did not provide useful information. This may be attributed to environmental

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44 characteristics which led to a more ra pi d dry down in comparisons to other studies (e.g. soil type). The duration of these dry down s were 18 and 22 days in 2010 and 2011 respectively Steinke et al. ( 2009 ) conducted their dry down for 60 days while others conducted their dry down s from 11 to 15 days (Jiang and Carrow, 2005). The results of the current study indicated that the duration of the dry down s were su fficient for ass essing genotypic response s to drought. Total t urf performance index values indicated tha t BA 182, a Z japonica was the genotype that had the greatest ability to resist changes across all parameters along with maintaining high er levels of color, density, quality, and PGC and less leaf firing at the final date of the dry down In previous research Z. matrellas showed reductions in color, quality, and increased leaf firing quicker than Z. japonicas during periods without precipitat i on and supplemental irrigation (Steinke et al 2009) Our results concur, as the six entries with the highest T TPI values were all Z. japonicas The mechanisms for the drought avoidance and tolerance of thes e genotypes should be further researched Deep ro oting has been considered as a drought resistance mechanism in many different plants (Levitt, 1980). It has also been reported as heritable in creeping bentgrass (Lehman and Engelke, 1991) and has been used as a selection criterion in breeding programs for drought tolerance (Sullivan and Ross, 1979; Taylor, 1983 ) ; however focusing breeding efforts on ET control may lead to greater water savings. Thus both rooting and ET should be utilized when selecting for drought responses.

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45 T able 2 1 Zoysiagrass genotypes evaluated for dry down responses in 2010 and 2011 at Hague and Citra, FL. Zoysia japonica Zoysia matrella JaMur* Meyer* UltimateFlora* Empire Palisades* BA 182 BA 188 BA 402 TAES 1543 TAES 2430 TAES 3363 TAES 4360 TAES 5288 TAES 5300 DALZ 8516 TAES 5257 8 TAES 5275 2 TAES 5283 5 TAES 5307 1 TAES 5335 3 TAES 5337 2 TAES 5256 20 TAES 5269 24 TAES 5305 48 TAES 5306 45 TAES 5307 16 TAES 5309 12 TAES 5309 23 TAES 5309 35 TAES 5330 23 TAES 5330 38 TAES 5331 23 TAES 5331 34 TAES 5332 52 TAES 5332 53 TAES 5333 53 TAES 5337 46 TAES 5343 52 UFZ02 UFZ10 Shadow Turf* PristineFlora* Diamond* Zeon* Zorro* BA 123 BA 152 BA 167 BA 252 BA 306 BA 309 BA 328 BA 332 BA 336 BA 356 BA 357 BA 358 BA 374 BA 375 BA 422 BA 463 BA 483 TAES 1567 TAES 3588 *Commercially available cultivars. Z. japonica x pacifica [ Goudsw .] ) zoysiagrass

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46 Table 2 2. Estimate of pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysi agra ss genotypes for years (2010 and 2011) and locations ( PSREU and AFRU ) Color Density Quality Leaf firing PGC £ Source D f Initial Final Initial Final Initial Final Initial Final Initial Final rep 4 ** ns ns *** ** ns ** location 1 *** ns ns *** *** ** *** ** *** *** genotype*location 64 *** *** *** *** ns *** ** ns ns *** genotype 64 *** *** *** *** ns ** ** ns *** year 1 *** *** *** *** ns ** *** *** *** ** location*year 1 *** ns ns *** ns *** *** *** *** *** genotype*year 64 ** ** *** ** ns *** ns ** *** genotype*location*year 64 ** *** ** *** ns ns ns *** Visually estimated on a scale of 1 to 9, where 1 = poor turf, 9 = excellent turf £ PGC = percent green cover estimated using SigmaScan analysis of digital images. 6 September and 7 May at PSREU in 2010 and 2011 and on 15 October and 5 June at AFRU in 2010 and 2011 respectively. conducted on 24 September and 27 May at PSREU in 2010 and 2011 and on 2 No vember and 3 July at AFRU in 2010 and 2011 respectively. ,**, *** = significant at p 0.01 and 0.001 respectively; ns= non significant

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47 Table 2 3. Estimate of pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for years (2010 and 2011) for AFRU, Hague, FL. Color Density Quality Leaf firing PGC £ Source Df Initial Final Initial Final Initial Final Initial Final Initial Final r ep 4 ns ns ns ns ns ns ns ns g enotype 64 ns ns *** *** ns ns ns ns ** ns year 1 *** *** *** ns ns *** *** *** *** *** g enotype*year 64 ns ns ns ns ns ns ns ns ns turf £ PGC = percent green cover estimated using SigmaScan analysis of digital images. respe ctively. estimates were conducted on 2 November and 3 July at AFRU in 2010 and 2011 respectively.

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48 Table 2 4. Estimate of pooled analysis of variance co mponents for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for years (2010 and 2011) for PSREU, Citra, FL. Color Density Quality Leaf firing PGC £ Source Df Initial Final Initial Final Initial Final Initial Final Initial Final r ep 4 *** ns ns ns *** *** ** *** ** ns g enotype 64 *** *** *** *** *** *** *** ns ** *** year 1 *** *** *** *** ns *** *** ns *** *** g enotype*year 64 *** *** *** *** *** ns *** ns ** *** a scale of 1 to 9, where 1 = poor turf, 9 = excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images. conducted on 6 September and 7 May at PSREU in 2010 and 2011 respectively. conducted on 24 September and 27 May at PSREU in 2010 and 2011 respectively.

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49 T able 2 5. 2010 estimate of analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for PSREU, Citra, FL. Color Density Quality Leaf firing PGC £ Source Df Initial Final Initial Final Initial Final Initial Final Initial Final g enotype 64 *** *** *** *** *** *** ns ns ns *** rep 4 ** ns *** *** *** ns *** ns ns £ PGC = percent green cover estimated using SigmaScan analysis of digital images. 0.05, 0.01 and 0.001 respectively; ns= non significant

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50 Table 2 6. 2011 estimate of analysis of variance components for color, density, quality, leaf firing, and percent green cover means in zoysiagrass genotypes for PSREU, Citra, FL. Color Density Quality Leaf firing PGC £ Source Df Initial Final Initial Final Initial Final Initial Final Initial Final g enotype 64 *** *** *** *** *** *** *** ** ** rep 4 *** ns ns ns *** ns ** = poor turf, 9 = excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images. Initial est imates were conducted on 7 May at PSREU in 2011. imates were conducted on 27 May at PSREU in 2011. *, *** = significant at p

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51 Table 2 7 Pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes percent difference acr oss locations (PSREU and AFRU) and years (2010 and 2011). Source D f Color Density Quality Leaf Firing PGC £ rep 4 ns ns *** ** location 1 *** *** *** *** genotype*location 64 *** ns *** genotype 64 ns ns ns *** year 1 *** ns ** *** *** location*year 1 *** *** *** *** *** genotype*year 64 ns ns *** genotype*location*year 64 ns ns ns ns *** initial rating)/ initial rating) 100 excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images.

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52 Tabl e 2 8. Pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for AFRU, Hague, FL for percent difference across years (2010 and 2011). Source Df Color Density Quality Leaf Firing PGC £ rep 4 ns ns ns ns genotype 64 ns ns *** ns ** year 1 *** *** ** *** *** genotype*year 64 ns ns ns ns ns initial rating)/ initial rating) 100 excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images.

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53 Table 2 9 Pooled analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference across years (2010 and 2011). Source Df Color Density Quality Leaf Firing PGC £ rep 4 ns *** *** ns genotype 64 *** ns ns *** year 1 *** *** *** *** *** genotype*year 64 ** ns ns *** initial rating)/ initial rating) 100 9 = excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images.

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54 Table 2 10 2010 analysis of variance components for colo r, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference Source Df Color Density Quality Leaf Firing PGC £ g enotype 64 *** ** ** ns *** r ep 4 ** *** *** *** ns % difference = ((Final rating initial rating)/ initial rating) 100 £ PGC = percent green cover estimated using SigmaScan analysis of digital images. *, *** = significant at p

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55 Table 2 11 2011 analysis of variance components for color, density, quality, leaf firing, and percent green cover in zoysiagrass genotypes for PSREU, Citra, FL for percent difference Source Df Color Density Quality Leaf Firing PGC £ g enotype 64 ** *** ns *** *** r ep 4 ns ns ns initial rating)/ initial rating) 10 0. poor turf, 9 = excellent turf. £ PGC = percent green cover estimated using SigmaScan analysis of digital images.

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56 Table 2 12 Initial, final, and percent difference color ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). 2010 Color 2011 Color Entry Initial x Final y % Difference Entry Initial Final % Difference UltimateFlora 7.6 6.0 21 BA 152 5.0 4.8 1 TAES 5331 34 8.4 6.4 24 BA 357 5.8 5.4 6 UFZ02 7.0 5.2 24 BA 358 5.2 4.8 8 TAES 8516 7.6 5.6 26 TAES 5309 23 6.5 6.0 10 BA 188 8.2 5.8 29 TAES 5256 20 6.2 6.0 10 TAES 5330 23 7.2 5.0 30 BA 252 5.2 4.6 12 TAES 1543 7.6 5.2 32 BA 356 5.2 4.6 12 Zeon 6.0 4.0 32 TAES 8516 6.6 5.6 15 TAES 5256 20 9.0 6.0 33 TAES 3363 7.0 6.0 15 TAES 3363 7.6 5.0 34 PristineFlora 5.0 4.2 16 TAES 5331 23 8.4 5.4 35 TAES 5257 8 7.0 5.8 17 TAES 5307 16 9.0 5.8 36 BA 463 5.2 4.2 17 Emerald 8.4 5.4 36 Meyer 7.4 6.0 18 TAES 5305 48 7.2 4.6 36 JaMur 6.2 5.0 19 BA 336 7.2 4.6 36 TAES 5275 2 7.0 3.4 20 BA 182 8.8 5.6 36 TAES 5300 6.8 5.2 23 JaMur 8.2 5.2 36 TAES 5332 53 5.8 4.4 23 TAES 5309 35 6.8 4.4 36 BA 182 6.6 5.0 24 BA 328 8.2 5.2 37 UltimateFlora 7.6 5.8 24 Shadow Turf 7.4 4.6 37 TAES 5335 3 5.2 4.2 25 TAES 1567 7.6 4.8 38 TAES 5331 34 6.4 4.8 25 TAES 5330 38 7.4 4.6 38 BA 167 4.8 3.6 25 TAES 5332 52 7.8 4.8 38 TAES 1543 6.2 4.6 26 BA 356 7.4 4.6 39 BA 422 5.2 3.8 27 BA 402 8.2 5.0 39 Emerald 5.6 4.0 27 TAES 5337 2 7.0 4.2 39 TAES 5330 23 7.8 5.6 27 TAES 5309 23 6.6 4.0 39 TAES 5283 5 4.2 3.2 28 PristineFlora 7.0 4.2 39 TAES 2430 6.4 4.6 28 TAES 5309 12 8.3 4.8 40 TAES 5309 12 6.2 4.4 29 TAES 5343 52 8.0 4.8 40 Empire 6.4 4.6 29 BA 167 7.4 4.4 40 TAES 5309 35 6.2 4.4 30 BA 123 7.4 4.4 41 Shadow Turf 5.8 4.2 30 TAES 5306 45 8.2 4.8 41 BA 123 5.8 4.0 30 BA 374 7.2 4.2 42 BA 336 5.0 3.4 30 TAES 5332 53 7.2 4.2 42 BA 309 5.2 3.6 31

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57 Table 2 12 Continued 2010 Color 2011 Color Entry Initial x Final y % Difference Entry Initial Final % Difference TAES 2430 7.4 4.2 42 BA 374 5.0 3.4 31 TAES 5257 8 7.6 4.4 43 TAES 1567 5.2 3.4 33 BA 306 7.0 4.0 43 TAES 5333 53 5.4 3.6 33 TAES 3588 7.6 4.2 43 BA 483 5.4 3.6 33 BA 252 7.4 4.2 43 UFZ02 6.6 4.4 33 TAES 5337 46 8.4 4.8 43 Palisades 6.4 4.0 35 UFZ10 7.8 4.4 44 TAES 4360 6.8 4.4 35 TAES 5300 7.8 4.4 44 BA 306 5.2 3.4 35 Diamond 6.6 3.8 44 Zorro 4.0 2.4 35 TAES 5283 5 7.2 4.0 44 TAES 5337 2 5.6 4.0 36 TAES 5269 24 8.2 4.6 44 TAES 5332 52 5.8 3.6 37 Empire 8.6 4.8 44 TAES 5331 23 6.8 4.2 37 BA 358 7.2 4.0 44 TAES 5269 24 5.2 3.2 37 TAES 4360 8.8 4.8 45 BA 328 4.4 2.6 38 BA 463 7.8 4.2 45 BA 375 4.6 2.8 38 TAES 5275 2 6.0 3.2 45 Diamond 5.0 3.0 38 BA 152 7.4 4.0 46 TAES 5306 45 5.8 3.6 38 BA 309 7.4 4.0 46 TAES 5307 16 5.2 3.2 39 Palisades 7.4 4.0 46 UFZ10 6.4 3.8 40 BA 483 8.6 4.6 46 TAES 5305 48 7.2 4.2 40 BA 375 6.8 3.6 47 TAES 5330 38 7.4 4.2 41 BA 422 6.8 3.6 47 TAES 5288 6.6 3.8 41 Meyer 8.8 4.6 48 BA 188 6.2 3.6 42 BA 357 7.4 3.8 48 TAES 3588 5.8 3.2 43 TAES 5307 1 7.4 3.8 48 BA 332 4.8 2.6 45 TAES 5335 3 7.6 3.8 50 BA 402 6.6 3.6 46 BA 332 7.4 3.6 51 TAES 5343 52 5.8 3.0 47 TAES 5288 7.8 3.8 51 TAES 5307 1 4.4 2.6 50 TAES 5333 53 7.4 3.6 51 Zeon 5.0 2.2 55 Zorro 6.6 3.2 52 TAES 5337 46 5.4 2.0 63 LSD z 1.0 1.0 12 LSD 1.0 1.5 27 conducted on 6 September and 7 May at PSREU in 2010 and 2011 respectively before drought stress, where turf color of 9.0=ideal; 1.0=brown turf condu cted on 24 September and 27 May at PSREU in 2010 and 2011 and respectively. z LSD= least significant difference for comparison of means with in columns ((final ratings initial ratings )/initial ratings )*100.

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58 Table 2 13 Initial, final, and percent difference density ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). 2010 Density 2011 Density Entry Initial x Final y % Difference Entry Initial Final % Difference TAES 5331 34 5.8 5.6 1 TAES 5331 23 6.2 7.0 14 TAES 3588 6.4 6.2 3 Empire 6.2 6.8 12 TAES 5257 8 6.2 4.2 10 JaMur 6.4 7.0 12 TAES 5269 24 5.8 5.2 10 TAES 5307 16 6.2 6.6 7 TAES 5283 5 6.4 4.0 11 TAES 5343 52 6.4 6.4 1 TAES 5332 52 6.8 6.0 11 TAES 5307 1 7.2 7 .0 1 TAES 5331 23 5.6 5.0 11 TAES 5269 24 6.4 6.2 2 TAES 5288 6.6 5.8 12 BA 483 7.4 7.0 3 TAES 5309 35 6.4 5.6 12 BA 422 6.0 5.8 3 Meyer 6.2 5.4 13 TAES 5283 5 7.4 7 .0 5 UltimateFlora 5.8 5.0 13 TAES 5257 8 6.6 6.2 6 JaMur 7.0 6.0 14 Palisades 7.0 6.2 7 BA 252 6.6 5.6 15 TAES 5288 7.6 7.0 8 BA 374 7.0 6.0 15 TAES 2430 6.8 6.2 8 Empire 6.6 5.6 15 BA 402 6.2 5.6 10 TAES 1543 7.4 6.2 15 UltimateFlora 7.4 6.6 10 TAES 5343 52 6.2 5.2 16 TAES 5305 48 6.6 5.8 10 Shadow Turf 6.2 5.2 16 BA 182 6.8 6.0 11 BA 332 6.6 5.6 16 TAES 5330 38 7.4 6.6 11 BA 306 5.8 4.8 16 TAES 5306 45 6.8 6.0 11 TAES 5306 45 5.6 4.6 17 BA 306 6.4 5.6 12 TAES 5305 48 6.6 5.4 17 TAES 5275 2 7.2 6.2 13 Palisades 5.6 4.6 18 TAES 5331 34 7.8 6.8 13 BA 328 6.6 5.4 18 TAES 5333 53 7.0 5.8 13 BA 356 6.8 5.6 18 Meyer 6.0 5.2 14 Zorro 6.4 5.2 18 TAES 5337 2 7.6 6.4 14 TAES 5330 23 6.7 5.0 19 UFZ10 7.8 6.6 14 Emerald 6.0 4.8 19 BA 332 6.4 5.4 15 TAES 5332 53 5.8 4.6 20 BA 152 6.6 5.6 15 TAES 8516 6.0 4.8 20 Zeon 7.6 6.4 15 PristineFlora 6.8 5.4 20 TAES 5332 53 7.4 6.2 16 BA 402 8.2 6.4 22 TAES 5332 52 7.4 6.2 16 TAES 5337 46 5.8 4.4 22 Emerald 7.2 6.0 17 Zeon 6.8 5.2 23 Zorro 7.8 6.4 17 BA 463 7.4 5.6 23 BA 356 7.0 5.6 18

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59 Table 2 13 Continued 2010 Density 2011 Density Entry Initial x Final y % Difference Entry Initial Final % Difference TAES 5337 2 6.4 4.2 24 BA 375 7.2 5.8 18 BA 375 7.2 5.4 25 TAES 1543 6.2 5.0 19 TAES 5330 38 6.8 5.0 25 TAES 3588 7.0 5.6 19 BA 336 6.8 5.0 25 TAES 5337 46 7.0 5.6 19 UFZ10 7.2 5.4 25 BA 358 7.2 5.6 21 Diamond 6.2 4.6 25 TAES 5335 3 7.4 5.8 21 TAES 2430 7.4 5.4 25 TAES 5330 23 6.6 5.2 21 TAES 1567 7.0 5.2 26 BA 309 7.2 5.6 22 UFZ02 6.6 4.8 26 TAES 5309 35 7.4 5.8 22 TAES 5309 12 7.4 5.4 26 TAES 5309 23 7.0 5.3 23 BA 358 7.0 5.0 27 BA 123 6.2 4.6 23 BA 422 6.4 4.6 27 TAES 5300 8.2 6.2 24 BA 182 7.2 5.2 27 TAES 3363 7.6 5.6 26 TAES 5309 23 6.6 4.8 27 BA 328 6.6 4.8 26 BA 188 6.6 4.8 27 PristineFlora 7.4 5.4 26 TAES 3363 7.0 5.0 27 BA 374 7.0 5.0 26 BA 357 6.8 4.8 28 TAES 5309 12 7.6 5.6 26 TAES 5300 6.8 4.8 28 TAES 8516 7.2 5.2 27 TAES 4360 6.6 4.6 29 TAES 5256 20 7.4 5.2 27 BA 123 6.6 4.6 30 BA 357 7.0 5.0 28 BA 483 6.6 4.6 30 BA 463 6.8 4.8 28 TAES 5333 53 6.0 4.2 30 BA 188 7.8 5.6 28 BA 309 6.8 4.6 31 BA 336 6.8 4.8 28 TAES 5256 20 5.8 4.4 32 TAES 4360 8.4 6.0 28 BA 152 7.2 4.8 33 TAES 1567 7.2 4.8 31 TAES 5335 3 5.8 3.8 34 UFZ02 7.4 4.8 35 TAES 5307 1 7.0 6.2 34 BA 252 7.8 5.0 35 BA 167 8.0 5.2 35 Diamond 7.8 4.8 38 TAES 5275 2 6.2 5.6 37 BA 167 7.2 4.4 39 TAES 5307 16 7.2 4.2 42 Shadow Turf 7.2 4.4 39 LSD z 1.0 1.1 17 LSD 1.1 1.2 21 ucted on 6 September and 7 May at PSREU in 2010 and 2011 respectively before drought stress, where turf density of 9.0=ideal; 1.0= bare soil estimates were conducted on 24 Septe mber and 27 May at PSREU in 2010 and 2011 respectively. initial ratings)/initial ratings)*100. Z LSD= least significant difference for comparison of means with in column s.

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60 Table 2 14 Initial, final, and percent difference quality ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for both years (2010 and 2011). 2010 Quality 2011 Quality Entry Initial x Final y % Difference Entry Initial Final % Difference UFZ02 5.4 4.2 22 DALZ 8516 6.6 4.6 30 TAES 5332 52 6.2 4.6 25 TAES 3363 7.4 5.2 30 TAES 5283 5 6.2 4.2 28 TAES 5331 34 5.8 4.0 31 Meyer 6.8 4.8 28 BA 188 6.8 4.6 32 TAES 5305 48 7.0 5.0 29 TAES 5330 23 6.8 4.6 32 JaMur 7.2 5.0 30 Palisades 7.2 4.8 33 BA 328 6.4 4.4 30 TAES 5256 20 6.6 4.4 33 Emerald 7.2 5.0 31 TAES 5335 3 8.0 5.2 34 BA 402 6.8 4.6 31 TAES 4360 7.8 5.0 36 Palisades 7.0 4.8 31 Meyer 7.0 4.4 37 TAES 1543 6.0 4.0 32 TAES 5309 23 6.5 4.3 37 BA 356 6.8 4.6 32 TAES 5309 12 7.0 4.4 38 TAES 3363 6.8 4.6 32 TAES 5307 1 6.8 4.2 38 TAES 5275 2 7.4 4.8 32 TAES 5300 6.8 4.2 39 Zeon 6.2 4.2 32 TAES 5257 8 7.4 4.6 39 TAES 5307 16 7.2 4.8 32 Emerald 7.8 4.6 39 TAES 5337 2 7.0 4.0 32 UFZ02 6.0 3.6 40 TAES 3588 6.6 4.4 33 BA 182 8.0 4.8 40 DALZ 8516 6.6 4.4 33 TAES 5332 53 7.4 4.4 40 TAES 5309 12 7.0 4.6 33 JaMur 7.4 4.4 40 BA 182 7.8 5.2 33 TAES 5330 38 7.2 4.2 40 TAES 5331 34 7.2 4.8 33 BA 309 6.2 3.6 41 TAES 5343 52 7.2 4.8 33 BA 374 5.8 3.4 41 UltimateFlora 7.0 4.6 34 TAES 2430 7.2 4.2 41 TAES 2430 7.0 4.6 34 TAES 5305 48 6.8 4.0 41 TAES 5309 23 6.4 4.2 34 Empire 6.8 4.0 41 TAES 5331 23 6.6 4.2 34 BA 152 6.2 3.6 41 TAES 5257 8 6.4 4.0 35 TAES 5288 7.4 4.2 42 TAES 5269 24 7.4 4.8 35 BA 123 6.2 3.8 42 TAES 5306 45 7.4 4.8 35 TAES 5333 53 7.0 4.0 43 BA 336 6.8 4.4 35 UltimateFlora 6.8 3.8 43 BA 309 6.6 4.2 36 BA 252 6.4 3.6 43 BA 374 6.6 4.2 36 BA 357 6.8 3.8 43

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61 Tabl e 2 14 Continued 2010 Quality 2011 Quality Entry Initial x Final y % Difference Entry Initial Final % Difference TAES 5309 35 6.2 4.0 36 Shadow Turf 6.4 3.6 43 TAES 5337 46 6.6 4.2 36 TAES 5331 23 7.0 4.0 44 Shadow Turf 6.6 4.2 36 UFZ10 7.2 4.0 44 TAES 5256 20 6.6 4.4 36 TAES 5309 35 7.2 4.0 45 TAES 5330 38 6.4 4.0 36 TAES 5275 2 7.0 3.8 45 BA 483 7.6 4.8 36 TAES 5343 52 7.0 3.8 46 BA 167 6.8 4.2 37 BA 167 6.6 3.6 46 BA 358 7.0 4.4 37 BA 402 7.8 4.2 46 TAES 5300 7.4 4.6 38 TAES 5337 2 7.4 4.0 46 BA 357 6.8 4.2 38 BA 358 6.4 3.4 46 TAES 5307 1 7.0 5.0 38 BA 306 6.4 3.4 47 PristineFlora 6.6 4.0 39 TAES 5306 45 6.4 3.4 47 Zorro 6.6 4.0 39 PristineFlora 5.8 3.0 47 TAES 5330 23 7.0 4.3 40 TAES 5269 24 6.6 3.4 48 Empire 7.4 4.4 40 TAES 1567 5.8 3.0 48 UFZ10 7.0 4.2 40 TAES 1543 6.6 3.4 48 BA 332 6.8 4.0 40 BA 328 5.8 3.0 49 BA 123 6.6 3.8 41 BA 332 6.2 3.2 49 TAES 5288 7.2 4.2 41 BA 356 6.2 3.2 49 TAES 5332 53 6.8 4.0 41 BA 483 7.8 4.0 49 Diamond 6.2 3.6 42 TAES 5307 16 6.6 3.4 49 TAES 5335 3 6.8 4.2 43 BA 463 6.4 3.2 49 TAES 5333 53 7.0 4.0 43 BA 336 6.4 3.2 50 TAES 1567 6.8 3.8 43 TAES 5337 46 5.8 3.0 50 BA 306 6.8 3.8 44 TAES 5332 52 7.2 3.6 50 BA 422 6.8 3.8 44 TAES 5283 5 6.6 3.2 51 BA 463 7.2 4.0 44 BA 422 6.6 3.2 52 BA 188 7.4 4.0 46 BA 375 5.8 2.6 55 BA 252 7.0 3.8 46 Zorro 6.6 3.0 55 BA 152 6.8 3.6 47 TAES 3588 7.4 3.2 56 TAES 4360 7.8 4.0 48 Zeon 6.4 2.6 60 BA 375 7.0 3.6 49 Diamond 6.8 2.6 61 LSD z 0.7 1.0 12 LSD 0.8 1.1 ns ucted on 6 September and 7 May at PSREU in 2010 and 2011 respectively before drought stress, where turf quality of 9.0=ideal; 1.0=brown, dead turf

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62 cted on 24 September and 27 May at PSREU in 2010 and 2011 respectively. ings initial ratings)/initial ratings)*100. Z LSD= least significant difference for comparison of means with in columns.

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63 Table 2 15 Initial, final, and percent difference for percent green cov e r ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL fo r both years (2010 and 2011). 2010 Percent Green Cover 2011 Percent Green Cover Entry Inital x Final y % Difference Entry Initial Final % Difference BA 375 98 97 1 Meyer 42 19 47 BA 188 88 84 5 TAES 1543 52 23 51 TAES 3588 92 87 6 TAES 2430 61 30 51 TAES 4360 99 93 6 Palisades 62 29 52 BA 252 95 89 7 UFZ02 38 13 53 BA 374 94 88 7 TAES 5331 23 44 7 56 TAES 5305 48 92 83 10 BA 328 61 26 59 TAES 5306 45 96 78 19 DALZ 8516 54 21 59 TAES 5331 34 94 64 32 TAES 5330 23 46 15 59 TAES 5332 52 87 57 32 Emerald 85 32 62 Empire 90 57 38 BA 167 71 25 65 BA 182 86 49 44 BA 182 72 25 66 BA 306 92 51 44 TAES 5256 20 77 27 67 BA 358 96 44 54 TAES 5300 44 15 67 BA 402 96 43 55 TAES 5337 2 69 18 67 TAES 5307 1 80 31 58 BA 356 51 18 69 TAES 3363 97 39 60 BA 422 69 21 69 TAES 5269 24 98 38 61 TAES 3363 64 20 71 JaMur 85 32 61 BA 375 52 13 72 BA 483 93 35 61 TAES 1567 56 13 72 Shadow Turf 99 36 64 TAES 5309 23 38 10 73 TAES 5288 95 32 66 BA 336 69 19 73 DALZ 8516 98 32 67 BA 306 60 14 73 TAES 5300 98 32 67 Shadow Turf 60 14 74 TAES 5333 53 94 30 68 TAES 5337 46 39 9 74 Zorro 92 29 69 TAES 4360 74 19 75 Diamond 94 30 69 TAES 5335 3 63 16 76 123 97 30 69 TAES 5307 16 47 10 77 BA 328 99 31 69 TAES 5330 38 49 9 77 TAES 5309 23 97 29 70 BA 152 64 12 79 TAES 5309 35 88 25 70 TAES 5305 48 58 11 79 TAES 2430 96 29 70 TAES 5331 34 41 8 80 TAES 5283 5 97 29 70 TAES 5288 68 11 81 PristineFlora 93 26 72 TAES 5333 53 58 11 81 TAES 5275 2 95 27 72 BA 402 71 11 81

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64 Table 2 15 Continued 2010 Percent Green Cover 2011 Percent Green Cover Entry Initial x Final y % Difference Entry Initial Final % Difference TAES 1543 93 26 72 Empire 41 6 81 Palisades 96 26 72 BA 358 65 10 82 TAES 5335 3 96 26 73 BA 332 57 10 82 TAES 5332 53 94 26 73 BA 463 62 10 84 TAES 5331 23 94 25 73 Diamond 86 14 84 TAES 5257 8 98 26 74 BA 374 63 9 85 BA 463 99 26 74 TAES 5275 2 49 7 85 TAES 5343 52 96 25 74 TAES 5306 45 36 6 85 BA 167 96 24 75 UFZ10 69 10 85 TAES 1567 92 23 76 TAES 5309 12 53 8 85 TAES 5337 46 96 23 77 Zeon 58 7 86 BA 356 97 22 77 BA123 58 8 87 Emerald 92 21 78 TAES 5257 8 61 7 87 BA 309 87 19 78 TAES 5309 35 65 9 88 BA 336 91 18 78 TAES 3588 74 9 88 BA 332 99 21 79 PristineFlora 53 6 88 Meyer 79 16 79 BA 309 62 7 88 UFZ02 95 20 79 BA 252 56 6 88 Zeon 94 20 79 BA 188 63 7 88 BA 152 98 20 80 TAES 5332 52 65 7 88 TAES 5256 20 93 18 81 JaMur 58 6 90 TAES 5337 2 98 18 81 TAES 5332 53 72 7 90 TAES 5307 16 97 18 82 TAES 5269 24 73 7 90 UFZ10 98 17 82 TAES 5307 1 61 6 90 TAES 5309 12 97 17 83 BA 483 82 8 91 BA 422 98 16 83 Ultimate 36 3 91 TAES 5330 38 92 13 85 TAES 5283 5 79 7 91 TAES 5330 23 89 11 87 Zorro 74 7 91 BA 357 99 13 87 TAES 5343 52 66 6 91 UltimateFlora 93 11 87 BA 357 68 5 93 LSD z 11 19 20 18 12 24 Initial estimates were conducted on 6 September and 7 May at PSREU in 2010 and 2011 respectively before drought stress, where percent green cover= 100% Data are the averages of ((final ratings initial ratings)/initial ratings)*100. Z LSD= least significant difference for comparison of means with in columns.

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65 Table 2 16 Initial, final, and percent difference leaf firing ratings for 65 zoysiagrass genotypes at PSREU, Citra, FL for 2011. Leaf firing 2011 Entry Initial x Final y % Difference TAES 5283 5 5.8 4.8 12 BA 336 6.6 5.0 24 PristineFlora 6.6 5.0 24 BA 123 7.0 5.2 25 Zeon 6.2 4.4 26 TAES 5330 23 7.4 5.2 27 BA 357 7.2 5.2 28 TAES 8516 7.8 5.4 30 BA 152 6.6 4.6 30 BA 375 6.2 4.2 30 BA 188 7.8 5.4 31 BA 358 6.6 4.4 32 BA 182 8.0 5.4 32 BA 332 6.4 4.2 33 BA 463 6.4 4.2 34 TAES 3363 8.0 5.2 35 JaMur 7.8 5.0 35 BA 374 6.4 4.2 35 Shadow Turf 7.6 4.8 36 TAES 5256 20 8 .0 5 .0 36 BA 422 6.4 4.0 37 BA 306 7.0 4.4 37 BA 356 7.0 4.4 37 Diamond 6.6 4.2 37 TAES 5331 23 6.8 4.2 38 TAES 5309 23 7.4 4.4 39 TAES 1543 7.6 4.6 39 TAES 5335 3 7.6 4.6 39 Emerald 7.2 4.2 40 Zorro 5.4 3.2 40 UltimateFlora 8.4 5.0 41 BA 167 5.8 3.4 41 TAES 2430 7.8 4.6 41 BA 252 7.0 4.0 42 BA 309 7.0 4.0 42

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66 Table 2 16 Continued Leaf firing 2011 Entry Initial x Final y % Difference BA 483 7.2 4.0 44 BA 402 7.6 4.2 44 UFZ10 8.0 4.4 44 TAES 5309 35 8.0 4.4 44 Meyer 8.6 4.8 44 TAES 5343 52 7.2 3.8 45 TAES 5337 2 7.8 4.2 45 TAES 5300 8.4 4.6 46 TAES 5305 48 7.8 4.2 46 TAES 3588 7.4 4.0 46 TAES 5330 38 7.4 4.0 46 TAES 5269 24 7.2 3.8 46 Empire 7.6 4.0 47 TAES 1567 6.6 3.4 47 TAES 5309 12 7.0 3.6 49 TAES 5332 53 7.0 3.6 49 TAES 5275 2 7 .0 3.4 49 TAES 5337 46 6.8 3.4 50 BA 328 5.8 2.8 51 TAES 4360 8.4 4.0 53 TAES 5331 34 7.2 3.4 53 TAES 5307 16 7.8 3.6 54 Palisades 8.2 3.8 54 TAES 5288 8.6 3.8 55 UFZ02 8.2 3.6 56 TAES 5333 53 7.2 3.2 56 TAES 5306 45 8.8 3.6 59 TAES 5332 52 8.0 3.0 61 TAES 5307 1 8 .0 3 .0 62 LSD z 1.1 1.4 22 imates were conducted on 7 May at PSREU in 2011 before drought stress, where leaf firing of 9 = no leaf firing; 1 = all leaves fired imates were conducted on 27 May at PSREU 2011. initial ratings)/initial ratings)*100. Z LSD= least significant difference for comparison of means with in columns.

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67 T able 2 17 Total t urf performance index of 65 zoysiagrass genotypes for 2010 and 2011 dry down s at PSREU, Citra, FL. 2010 2011 2010 2011 Entry C D Q P C D Q L P FPI £ C D Q P C D L P DPI TTPI BA 182 7 4 11 JaMur 6 4 10 DA LZ 8516 5 5 10 TAES 5331 34 5 4 9 TAES 5257 8 6 3 9 Meyer 5 4 9 UltimateF lora 5 3 8 BA 356 4 4 8 TAES 1543 4 4 8 Emerald 6 2 8 Palisades 4 4 8 TAES 2430 7 1 8 TAES 5256 20 6 2 8 BA 188 4 3 7 TAES 5305 48 4 3 7 TAES 5300 5 2 7 TAES 5330 23 4 3 7 TAES 3363 4 3 7 BA 252 3 3 6 TAES 5283 5 2 4 6 TAES 5306 45 3 3 6 TAES 5331 23 3 3 6 BA 375 3 2 5 Empire 3 2 5 TAES 5307 16 3 2 5 BA 374 3 2 5 BA 402 4 1 5 TAES 3588 2 3 5 TAES 5332 52 3 2 5 TAES 5343 52 2 3 5 Zeon 2 3 5 BA 328 2 3 5 PristineF lora 2 2 4 TAES 5309 12 3 1 4 TAES 5309 23 3 1 4

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68 Table 2 17 Continued 2010 2011 2010 2011 Entry C D Q P C D Q L P FPI £ C D Q P C D L P DPI TTPI BA 152 2 2 4 BA 332 2 2 4 BA 357 2 2 4 BA 358 2 2 4 TAES 4360 3 1 4 TAES 5269 24 2 2 4 TAES 5288 3 1 4 TAES 5335 3 3 1 4 TAES 5275 2 1 2 3 BA 463 2 1 3 BA 483 2 1 3 TAES 5307 1 2 1 3 TAES 5309 35 2 1 3 TAES 5332 53 2 1 3 UFZ10 3 0 3 TAES 5330 38 2 1 3 UFZ02 0 3 3 TAES 5337 2 1 2 3 BA 167 1 2 3 BA 422 1 2 3 BA 123 1 1 2 BA 306 1 1 2 BA 336 1 1 2 Shadow Turf 1 1 2 Zorro 1 1 2 Diamond 1 0 1 TAES 5337 46 0 1 1 BA 309 0 0 0 TAES 1567 0 0 0 TAES 5333 53 0 0 0 nt green cover; L= leaf firing £ FPI= final performance index. initial ratings)/initial ratings)*100. C= color; D= density ; Q= quality; P= percent green c over; L= leaf firing DPI= difference performance index TTPI= total turf performance; TTPI= (FPI + DPI) ; TTPI range = 0 11

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69 CHAPTER 3 SHADE RESPONSES OF 43 ZOYSI A GRASS GENOTYPES Background Light is a basic requirement for turfgrass growth and is described in terms of p hotosynthetical l y a ctive r adiation (PAR). Photosynthetical l y active radiation is the visible portion of light that falls between 380 and 70 0 nm that can be absorbed by leaves a nd used for photosynthesis (Beard 1997). Photosynthetical l y active radiation is often limiting in the landscape with an estimated 25 40% of planted turfgrass affected by shade (Qian and E n gelke, 1997). Within a shaded environment, both light quality and q uantity are reduced (Beard, 1997). Light quality refers to the ratios of different wavelengths present in a light environment. Shade results in a higher percentage of far red wavelengths (> 700 nm) and a decreased percentage of red light wavelengths respon sible for normal turf development (Anderson, 1964; Evans, 1939). An increase in far red wavelengths will lead to an increased stem extension rate for plants that typically require full sun environments. This is due to plants allocating more of their resources towards growing taller. This change in resource allocation is an attempt by the plant to gain a competitive advantage for sunlight when grown in shade By growing taller, the plant may be able to gro w above the canopy in order to obtain ade quate light (Morgan and Smith 1979 ). Reductions in light quality and quantity can lead to morphological changes in turfgrass within 4 to 7 days This has been attributed to reductions in blue irradiance and increas es in red irradiance (McBee, 1969). Different types of changes have been reported including decreased chloroplast number ( Huylenbroeck and Bockstaele, 2001; B ald win et al., 2008), a more vertical leaf orientation (Wherley et al. 2011, Tan and Qian, 2003; McBee and Holt, 1966) with

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70 leaves typically appearing thinner (Tan and Qian, 2003), reduced tillering and shoot density (McBee and Holt, 1966 ; Wherley et al., 2011 ) and reduced quality (Wherley et al., 2011; Baldwin et al., 2008). Reductions in chlorophyl l content can occur under shade and cause r eductions in photosynthesis and carbohydrate accumulation resulting in decreased turf performance and quality (Baldwin et al., 2008) A reduced level of available and stored carbohydrates bilities to tolerate wear and damaging i nsects and diseases in addition to their recuperative potential when damage does occur (Wilson 1997 ). Many warm season turfgrass species have proven to differ in their tolerance to reduced sunlight (Barrios et al., 1986). St. Augustinegrass ( Stenotaphrum secundatum [Walt.] Kuntze) zoysiagrass ( Zoysia spp.) and zoysiagrass ( Zoysia spp .) are considered to have good shade tolerance w hile bermudagrass ( Cynodon spp. ) and bahiagrass ( Paspalum notatum Flugge) are considered to have poor shade tolerance (Johnson et al., 1986). Slade k et al. (2009) compared shade responses between six zoysiagrass cultivars using plant diameter, percent cover, and overall turf quality ratings. Their results identified variation for shade responses among the cultivars studied. Wherley et al. (2011) conducted a three year study looking at zoysiagrass response s to shade for qual ity, density, color, vertical canopy height and lateral spread A turf performance index tables was constructed to rank c Grass plugs were planted under 89% shade provided by live oak ( Quercus virginiana ) trees Royal, Zorro, and Shadow T urf were ranked in the top statistical group most often for the above parameters In addition, the results suggested that Z. matrellas may be bet ter

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71 suited for shade than Z. japonicas T he objectives of this study were to 1) quantify the effects of 60% shade on t wo species of zoysiagrass and to 2) identify those experimental lines that perform similar in sun and shade environments Materials and Methods Thirty five experimental lines of Z. japonica and Z. matrella were selected in 2008 from larger replicated germplasm nurseries previously evaluated at the University of Florida Plant Scie nce Research and Education Unit (PSREU) located near Citra, F lorida (29.409395, 82.167993). The selected entries along with eight commercial cultivars (Table 3 1) were planted on 12 June 2010 using 10 cm plugs on 9 1 cm centers in a randomized complete block design with three rep lications in two environments: full s un and 60% shade. Data collection began in September 2010 and continued every three weeks through August 2011. Plots were irrigated 10 minutes, three times per week throughout the study to prevent drought stress, mowed once a week at 8.25 cm and fertilized using a 15 5 15 (N P 2 O 5 K 2 O ) mixture of a release polymer coated fertilizer Polyon Controlled Release Fertilizer Agrium Advanced Technologies, Lakeland, FL) and an immediate release Carpetmaker fertilizer ( Southern States Coo perative, Richmond, Virginia) at a N rate of .4 9.0 kg N/ ha 1 every 60 days during the growing season for a total of three applications during the growing season Procedure Data collection included measures of percent plot establishment (PPE), relative c hlorophyll content (RCC) leaf orientation, and p ercent green cover (PGC) P ercent plot establishment was determined using a grid. T he grid was constructed to have the same dimensions as the pl ot s (1.86 m 2 ). The grid contained 64 separa te squares each measuring 7.6 x 7.6 cm and each square represented ~1.5% of the entire plot. When

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72 the grid was plac ed upon the plot, PPE was determined by the number of squares with in the grid that were fully established. Relative chlorophyll content was determined using a FieldScout CM 1000 chlorophyll meter ( Spectrum Technologies, Plainfield, IL ) This point and shoot device uses ambient light reflected between 700nm and 840nm from the turf canopy to calculate relative chlorophyll content using an index value (0 999). Use has been reported for seashore paspalum ( Paspalum vaginatum O. Swartz) for tolerance of low light conditions (Jiang et al., 2004). Leaf orientation was determined visually using a 1 3 scale (1= prostrate and 3= vertical). Percent green cover was determined through the use of a light box and digital image analysis as described by Karcher and Richardson (2003 ) and Richardson et al. (2001). Images were collected using a digital camera placed inside a light box m easuring ~ 0.3 m x 0.3 m x 0.3m. The light box contained an internal light source (Compact fluorescent light, Longstar Lighting Co., Fujian, China) to simulate natural lighting powered by a portable battery. The light box provided a consistent light source to eliminate image differences that might result from taking pictures under natural daylight Statistical Analysis Data were analyzed using the SAS statistical package for Windows (SAS Systems for Windows Version 9.2, SAS Institute Inc Cary, NC, USA) usi ng the PROC GLM procedure. The sources of variation included for the analysis of variance were species, genotype within species and environments. Least square means were estimated and tested for significant differences between sun and shade environments an d between genotypes within the shade environment using differences at an alpha level of 0.05 to make comparisons between species a n d environments for the evaluated parameters. Orthogonal contrasts were conducted to

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73 compare each genotypes shade vs. sun performance. A total t urfgrass p erformance i ndex (T TPI ) table (Wherley et al. 2011) was generated to identify those genotypes whose performance was similar for the evaluated paramet ers between sun and shade environment s and to evaluate genotype performance with in the shade environment Results and Discussion Percent Plot Establishment Species In 2010 under full sun Z. japonica exhibited faster percent plot establishment (PPE) compared to Z. matrella (Figure 3 2). In 2011, the species did not differ except in June when Z. matrella on average had greater PPE. Under shade the species did not differ during any dates for both years. The PPE of Z. japonica and Z. matrella grown in full sun was always greate r than when both species were under 60 percent shade (Figure 3 2) Therefore, the majority of differences observed for PPE were due to the light environment (full sun vs. 60 % shade) rather than species At the conclusion of the study p ercent plot establish ment in full sun ranged from 52 % to 99 % for Z. japonica and from 50 % to 98 % for Z. matrella (Table 3 2 ). Within 60% shade, PPE ranged from 13% to 92 % for Z. japonica and from 33% to 74 % for Z. matrella (Table 3 2). Others have reported that Z. japonica will e xhibit faster plot coverage than Z. matrella ( Forbes and Ferguson, 1947; P atton et al., 2007 ). This has been shown to be due to dry weight partitioning differences between the species; whereby, Z. japonica will partition more energy into stems compa red to Z. matrella partitioning more energy into leaf development (Patton et al., 2007). In this study, Z. japonica entries were establishing faster in 2010; however, in 2011 the species did not differ as expected for PPE. A possible reason for Z. matrella having equal or better PPE in 2011 in both light

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74 environments may be because Z. matrella maintained more green color and cover (Figures 3 3 and 3 5) during cooler periods, and as a result, the Z. matrella entries actively grew (at a slow rate) through the mild Florida winter providing an advantage coming into the growing season compared to the more dormant Z. japonica entries. Genotypes Orthogonal contrasts used to compare genotypic performance between sun and shaded environments identified several genoty pes that were not different between sun and shade on several dates (Table 3 3 ). To identify those entries that were consistently not different between light environments a turf performance in dex ( TPI ) was utilized (Table 3 3 ). The TPI of each entry was th e number of dates that an entry did not differ for PPE during 2010 and 2011. The TPI values for PPE ranged from 0 to 11. Z oysia matrella entries BA 306, BA 361, BA 422 and Diamond ; and Z. japonica entries TAES 4360, TAES 5269 24, and Empire were the most similar genotypes for PPE between the two environments (Table 3 3 ) These entries were not di fferent between full sun and 60% shade on a single date in both years ( TPI = 11). The mean genotype PPEs under shade for Nov. 2010 (prior to the on set of dormancy) and late Aug. 2011 (termination of study) are found in Table 3 4. Significant differences occurred between genotypes on both dates The genotype means ranged from 6% to 40 % in 2010 and 13% to 92 % in 2011 indicating that some zoysiagrasses spread very well in the shade while other s spread much slower Previous research ( Sladek et al., 2009; Wherley et al., 2011) comparing the establishment of zoysiagrass species reported that Z. matrella genotypes exhibit bett er establishment in the shade. I n this study, there were more Z. japonica genotypes in the top statistical group for PPE. This may be due to the mowing height used in this study It was 8 .25 cm and much

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75 taller than the recommended height of 5.08 cm for zoysiagrass (Christians, 1998) Under shade, carbohydrate synthesis and allocation is a major factor influencing turfgrass performance (Burton et al., 1959) Under typical mowing heights for zoysiagrass there may be too much leaf area removal for Z. japonicas to maintain normal growth i n the shade. Sladek et al. (2009), mowed at a height of 1.9 cm In our study the taller mowing height could have provided more carbohydrate synthesis and the plant could have better allocated its carbohydrates allowing the Z. japonicas to competitively establish compared to the slower growing Z. matrellas Three genotypes in the top statistical group for PPE in the shade were also mentioned above as not differ ing in PPE between the two environments. These included two Z. matrella entri es, BA 361 and BA 422 and Z. japonica entry TAES 5269 24 Chlorophyll Content Species Relative chlorophyll contents (RCC) in full sun ranged from 174 to 270 and from 174 to 321 for Z. japonica and Z. matrella respectively. Under 60% shade, RCC ranged fro m 144 to 295 for Z. japonica and 183 to 268 for Z. matrella (Table 3 2 ) During the 2010 growing season Z. matrella grown in full sun had higher RCC than all other treatment combinations except Z. japonica grown in full sun on two dates (Figure 3 3 ). C hlorophyll contents between species were not different in full sun for all of 2011. In early 2011 (March and April), few differences were found between environments and species. During March, Z. matrella under 60 percent shade had higher RCC than Z. japoni ca grown in full sun. From May through 24 Aug. differences between environments and species occurred The majority of differences were observed during

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76 May when the RCC of Z. japonica under shade was less than all other treatment combinations. In addition, both Z. japonica and Z. matrella in full sun had greater RCC than Z. matrella under shade. From June through August (four dates of data collection), comparisons between species and environments were more variable. Consistent observation s during this perio d included: 1) Z. japonica in the shade had less RCC than Z. matrella in the sun (3 of 4 dates) and less RCC than Z. matrella in the shade (2 of 4 dates); 2) Z. japonica in full sun and Z. matrella under shade di d not differ for their RCC; and 3) relative chlorophyll contents compared between environments differed within Z. japonica in July and early August. Genotypes Orthogonal contrasts used to assess genotype comparisons between light environments indicated that RCC differences existed for some genotypes when grown in full sun versus 60 percent shade (Table 3 5 ). More genotypes were different during Oct. and Nov. 201 0 and May 2011. As described above a TPI index was developed to rank cultivars based on the number of dates a cultivar was not different between environments. Relative chlorophyll content TPI values ranged from 6 to 11. TPI value indicating that it produces less chlorophyll under shade versus its levels in full sun. Genotypes with TPI values of 11 were not different for chlorophyll content between light environments for all dates of data collection. Th e se include d Z. m atrella entri es BA 332, BA 361, BA 422 Diamond and Zorro ; and Z. japonica entries TAES 1543 TAES 5269 24, TAES 5335 3, TAES 5337 2 Empire and UltimateFlora (Table 3 5) In addition, there were sevent een genotypes with a TPI value of 10. Therefore, the RCC of the majority of genotypes was not highly affected by the light environments.

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77 Mean separation of genotypes on the last dates of data collection in both years (described above) showed that e nt r i es differed for their RCC at the end of 2010 but not in late August of 2011 (Table 3 6). The RCC g enotype means ranged from 93 to 180 in 2010 and 144 to 2 95 in 2011. Similarly, Baldwin et al. (2008) reported that relative chlorophyll content was shown to vary among forty two bermu dagrass cultivars under shaded conditions when measured using a spectrophotometer. Huylenbroeck and Bockstaele (2001) measured chlorophyll content under shade for several cool season grasses They observed that chlorophyll content increased in perennial ryegrass ( Lolium perrene L.), decreased in smooth stalked grass ( Poa pratensis L.) and crested hairgrass ( Koeleria macrantha [Ledeb.] Schultes), and remained unchanged in red fescue ( Festuca rubra L.) From the previously mentioned genotypes that did not d iffer between the sun and shade environments (Table 3 5) three genotypes had high RCC values under shade at the end of the experiment in 2011 (Table 3 6). Those genotypes included one Z. m atrella entry Zorro and two Z. japonica entries TAES 5337 2 and Empire Zorro has previously been reported to be adapted to shaded growing conditions (Wher l ey et al., 2011). Leaf Orientation, Sun vs. Shade Species Figure 3 4 provides both within and among species and light environment comparisons for leaf orientation ratings for 2010 and 2011. In the sun l eaf orientation ranged from 1.0 to 1.7 for Z. matrella and 1.0 to 2 .0 for Z japonica Within shade, the l eaf orientation ranged from 1.3 to 2 .0 for Z. matrella and 1.7 to 3.0 for Z. japonica (Table 3 3) Differences between species within environments were as expected with Z. matrella consistently having lower leaf angles (more horizontal leaves) than Z. japonica in both full sun and 60% shade (Figure 3 4) Comparison of species

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78 between environments indica ted that Z. japonica in the shade will have more upright leaf angles than Z. matrella under full sun (both years); however, leaf angles were consistently not different in 2011 (different in 2010) for Z. japonica in the sun and Z. matrella under 60% shade. The impact of shade on growth responses in both species was obvious; whereby, shade clearly resulted in more upright leaf angles for both Z. japonica and Z. matrella An increase in leaf orientation under shade has been observed in previous research for f our bermudagrass genotypes ( McBee and Holt, 1966). They suggested that upright leaves were due to altered growth of lateral stems that tended to grow more upright in simulated shade I ncrease d (more upright) leaf orientation is a product of restrictions in lateral stem development because of reduced photosynthesis ( Beard, 1997 ) and elongation of already existing stems and leaves as a shade avoidance mechanism These morphological changes produce thin, upright elongated leaves which will often be removed b y mowing (Tan and Qian, 2003 ) and result in reduced rooting, tillering, and over all turf quality (Qian et al., 1998). Genotypes Orthogonal contrasts were used to compare the leaf orientation of each genotype between full sun and 60% shade (Table 3 7 ). Results show that leaf angles of some entries were different on some dates between environments. A turf performance index ( TPI ) was used to rank cultivars for their ability to maintain similar leaf angles between environments. The majority of differences b etween environments occurred later in the year for both 2010 and 2011 Turf p erformance i ndex values in Table 3 7 range d from 4 to 11. Z oysia matrella entries that did not differ ( TPI = 11) between environments were BA 252 and Zorro; and Z. japonica entries were BA 182,

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79 TAES 4360, TAES 5257 8, TAES 5269 24, TAES 5306 45, and TAES 5337 2. E ntries with the lowest TPI values were predominantly Z. matrella and entries with the highest TPI values were mostly Z. japonica This is likely because Z. japonica leaves tend to be more upright in the sun; and therefore, changes in leaf orientation in altered light conditions will not be as obvious as they might be for the more prostrate leaves of Z. matrella Visual ratings for leaf orientation under shade identifi ed difference s among genotypes at the end of the study (Table 3 8). The genotype means ranged from 1. 7 to 3.0 i n late August of 2011. Opposite from the TPI values (Table 3 7) the majority of entries in the top statistical group (those with prostrate leaves) were Z. matrella entries. Therefore, despite the impact of shade on leaf angles (making plants more upright) Z. matrella will still have lower leaf angle s on average than Z. japonica under shade. Additionally, extensive documentation exists to show the overall good shade tolerance of Z. matrella cultivars (Diamond, Zorro, Cavalier Royal, S hadow T urf) compared to Z. japonica cultivars (Qian and Engelke 199 9a ; 1999b ; Qian et al., 1998; Okeyo et al., 2011; Wher l ey. et al., 2011; and Sladek et al., 2009). From the previously mentioned genotypes that did not differ between the sun and shade environments (Table 3 7) four genotypes were also in the best statist ical group (prostate leaf angles) at the end of the experiment in 2011(Table 3 8). Those genotypes included two Z. japonica entries TAES 4360 and TAES 5257 8 and two Z. matrella entries BA 252 and Zorro. Percent Green Cover Species Percent green cover (PGC) provided by digital image analysis did not result in many consistent differences between zoysiagrass species an d light

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8 0 environments (Figure 3 5 ). Overall PGC declined rapidly near the end of 2010 in both environments, but was more evident under 60 percent shade. As temperatures increased during spring 2011 PGC also increased for both species in both environments. Percent green cover (across species) peaked in Aug 2011 and ranged from 67% to 88 % for Z. japonica and 77% to 94 % for Z. matrella in full sun (Table 3 3 ) and from 68% to 89 % for Z. japonica and 55 % to 93 % for Z. matrella when grown under 60% shade. The most consistent comparisons were between Z. matrella under full sun and both species grown under shade. For both, Z. matrella had hi gher PGC. Additionally, in July and Aug 2011, Z. matrella in the sun had greater PGC than Z. japonica under full sun (Figure 3 5 ). Huylenbroeck and Bockstaele (2001) found similar reductions in green cover of cool season turfgrass when comparing between sh aded and full sun environments. They determined that visual seedling coverage of perennial ryegrass ( Lolium perenne L.), red fescue ( Festuca rubra L.), smooth stalked meadowgrass ( Poa pratensis L.) and crested hairgrass ( Koelena macrantha [Ledeb.] Schultes ) was reduced by shade. Genotypes As noted for the above characteristics, light environments resulted in PGC differences for most genotypes (Table 3 5) on one o r more dates in 2010 and 2011. Again genotypes were ranked according to a performance index ba sed on the number of days that a genotype did not differ for PGC between light environments. The TPI values for PGC ranged from 5 to 11 (Table 3 9) Z oysia matrella entry BA 422 and Z. japonica entries TAES 1543 TAES 3363, TAES 5300, TAES 5305 48, and TAE S 5332 53 had the highest TPI values.

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81 More differences between environments occurred during the 2010 2011, fall, winter, and spring months with very few differences noted from the end of May through the completion of the study Differences during this period were possibly attributable to the onset of cool temperatures resulting in an interaction between temperatures and light environments. An additional consideration should be the differing abilities of genotypes to retain green cover during the cooler months. This three way intera c tion (genotype*light*temperature) was not specifically assessed; however, PGC genotype means were compared at the end of the growing season in 2010 and the end of data collection in 2011 (Table 3 10) Those genotypes with more green cover during Nov. 2010 may have value as a germplasm that retains cover during periods of reduced temperatures and light quality, thus addressing the three way interaction. Genotypes that retained green cover in Nov. 2010 and were among those with t he highest TPI values were Zoysia matrella entry BA 422 and Z. japonica entries TAES 1543, TAES 3363, TAES 5300, TAES 5305 48, and TAES 5332 53 Significant differences did exist under shade in Nov. 2010 and at the end of data collection Aug ust 2011 (Tabl e 3 10) The genotype means ranged from 33% to 75% in November 2010 and 55% to 93 % in late August of 2011. From the previously mentioned genotypes that did not differ between the sun and shade environments (Table 3 9) Zoysia matrella entry BA 422 and Z. j aponica entries TAES 1543, TAES 5300, TAES 5305 48, and TAES 5332 53 performed well at the end of the experiment in 2011(Table 3 10) Summary Several methods have been used in previous research in an attempt to quantify the effects of variable levels of shade on different turfgrass species. Those methods

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82 have included chlorophyll number and content (Baldwin et al., 2008; Huylenbroeck and Bockstaele, 2001), quality (Baldwin et al., 2008; Wherley et al., 2011), shoot density (McBee and Holt, 1966; Wherley e t al., 2011), shoot elongation (Tan and Qian, 2003), vertical canopy height (Wherley et al., 2011), and root length and biomass (Baldwin et al. 2008 ). The methods described here adequately identified differences between 4 3 genotypes and two species of zoy siagrass. In general shade within a species resulted in reduced values for PPE, RCC, PGC and more upright leaf angles for both Z. japonica and Z. matrella Individual genotypic performance was assessed using orthogonal contrast s at each date of data collection. These results were then used, as previously described by Wherley et al. (2011), to develop a turf performance index (TPI) to identify those genotypes that maintained similar performance in PPE, RCC, leaf orientation, and PGC across light environments. Genotypes were identified for each parameter that did not differ between environments for a ny date of data collection. A summative TPI table (Table 3 11) was then developed to provide a total turf performance index (TTPI) val ue for each genotype a cross all parameters. Diamond had the highest TTPI value (42) and only differed between sun and shade environments on two dates for all evalu ated parameters. There were five additional genotypes (TAES 1543, TAES 5269 24, TAES 5337 2, TAES 4360 and TAES 5332 53) that had TTPI values 40. It is important to understand that this information simply illustrates those genotypes that varied less between environments than other genotypes. While this is valuable information, it does not indicate if a genotype performed well.

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83 The best genotypes wo uld be those with high TTPI values and were competitive against other genotypes for the studied parameters. Genotypic comparisons for the six entries that had TTPI values of 40 or more were as follows: TAES 5332 53 and Di amond were in the top statistical c ategory three of four parameters studied TAES 4360 was 2/4, TAES 5269 24 TAES 1543 and TAES 5337 2 were all 1 /4 (should be noted that TAES 5269 24 had one of the lower leaf angles for a Z. japonica ) Since genotypes with high TTPI were not necessarily c ompetitive, it is important to consider both comparisons when selecting germplasm to use in a breeding program for improved shade tolerance. Zoysia matrella entries that were competitive and had relatively high TTPI values ( 32) were BA 422, Zorro, BA 3 58 BA 152, BA 252, and BA 356 A n example of a Zoysia matrella entriy with high TTPI values but was less competitive was BA 3 06 Zoysia japonica entries that were competitive and had relatively high TTPI values ( 32) were TAES 5332 53, Empire, UFZ10, TAES 5300, and TAES 5257 8. Zoysia japonica entries that had high TTPI values but were less competitive included TAES 1543, TAES 5269 24, TAES 5337 2, TAES 5306 45 and TAES 5335 3. Among these genotypes, BA 422 Zorro ( both Z. matrella ) and TAES 5332 53 TAES 5300, and TAES 5257 8 (all Z. japonica ) were competitive genotypes and near the top for TTPI. These genotypes might be suitable for release (experimental lines) as shade tolerant cultivars that would outperform other cultivars with docum ented shade tolerance such as Diamond (Wherley et al., 2011; Sladek et al., 2009; Patton et al., 2007; Qian and Engelke, 1999a; 1999b; Okeyo et al., 2011). Zorro and Diamond released from Texas A&M University did well in this study and has pe r formed well in several shade studies (Wherley et al., 2011; Okeyo et al., 2011; Sladek et al., 2009).

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84 This study showed variability in responses to shade and between full sun and 60 percent shade for both Z. japonica and Z. matrella Overall, this study provided evid ence that potential exists for the breeding of zoysiagrass with improved shade tolerance.

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85 T able 3 1 Zoysiagrass species and entries studied for their comparative performance in full sun and 60 % shade, Citra, FL. Zoysia japonica Zoysia matrella JaMur* UltimateFlora* Empire BA 182 BA 188 BA 402 TAES 1543 TAES 2430 TAES 3363 TAES 4360 TAES 5300 TAES 5257 8 TAES 5335 3 TAES 5337 2 TAES 5269 24 TAES 5305 48 TAES 5306 45 TAES 5330 23 TAES 5331 34 TAES 5332 52 TAES 5332 53 TAES 5333 53 UFZ03 UFZ10 Shadow Turf* PristineFlora* Diamond* Zorro* BA 152 BA 252 BA 306 BA 309 BA 328 BA 332 BA 336 BA 356 BA 357 BA 358 BA 361 BA 422 TAES 1567 TAES 3588 *Commercially available cultivars. Z. japonica x Z pacifica [ Goudsw .] ) zoysiagrass

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86 Table 3 2. Minimum, maximum and average performance values of Z. matrella and Z. japonica grown under full sun and 60% shade in 2011 Z. matrella Z. japonica Sun Shade Sun Shade PPE min 50 33 52 13 max 98 74 99 92 avg 83 55 82 55 RCC min 174.0 183.0 174.3 144.0 max 321.5 268.5 270.3 295.0 avg 219.8 212.1 214.0 211.1 Leaf Angle min 1.0 1.3 1.0 1.7 max 1.7 2.0 2.0 3.0 avg 1.0 1.7 1.8 2.6 % Green Cover min 77 55 67 68 max 94 99 88 89 avg 85 79 77 81 100%) 999) = percent green cover (0 100%)

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87 Table 3 3 Turf Performance Index for sun vs. shade genotype c omparisons for percent plot establishment for 44 zoysiagrass genotypes in 2010 and 2011, Citra, FL. 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI BA 306 11 BA 361 11 BA 422 11 TAES 4360 11 TAES 5269 24 11 Diamond 11 Empire 11 TAES 1543 10 TAES 5332 53 10 TAES 5337 2 10 UFZ10 ** 10 BA 152 9 TAES 5335 3 9 BA 358 8 TAES 5305 48 ** 8 TAES 5331 34 8 TAES 5333 53 ** ** 8 Zorro ** 8 BA 188 7 BA 336 ** ** ** 7 TAES 5257 8 7 TAES 5306 45 ** 7 TAES 5332 52 ** 7 UltimateFlora ** 7 BA 252 ** ** ** ** 6 BA 356 ** ** 6

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88 Table 3 3 Co ntinued 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI TAE S 5300 ** ** 6 TAES 5330 23 ** ** ** ** ** 6 BA 309 5 BA 357 5 BA 402 ** 5 JaMur ** 5 UFZ03 ** 5 BA 182 ** 4 BA 332 ** 4 PristineFlora ** 4 Shadow Turf ** ** ** ** 4 BA 328 ** 3 TAES 1567 ** ** ** 2 TAES 2430 ** ** 2 TAES 3363 ** ** ** ** ** 2 TAES 3588 ** 2 Emerald ** ** ** ** ** 0 *, ** Sun versus shade environments were different within an entry at p < 0.05 and p < 0.01 respectively. TPI = Performance Index and is the number of dates that an entry was not different for percent cover between sun and shade enviro nments. TPI range = 0 11

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89 Ta ble 3 4 Zoysiagrass genotypes mean percent plot establishment under 60% shade for Nove mber 2010 and late August 2011 Citra, FL. Entry 2010 2011 £ TAES 5269 24 18 92 UltimateFlora 34 85 UFZ03 12 75 BA 252 31 74 TAES 5300 22 73 UFZ10 40 73 BA 328 12 72 BA 336 21 72 TAES 5332 52 11 72 BA 152 19 71 BA 332 13 71 TAES 5257 8 25 71 TAES 5332 53 23 70 Zorro 16 68 BA 402 15 67 BA 422 28 67 BA 361 23 64 BA 188 29 62 BA 357 18 60 BA 182 14 58 Diamond 12 57 Empire 28 52 BA 306 21 51 TAES 5333 53 24 49 TAES 3363 16 48 PristineFlora 10 47 JaMur 19 46 TAES 4360 19 44 Shadow Turf 16 43 BA 309 14 42 TAES 1567 13 42 TAES 5306 45 13 42 TAES 5331 34 13 42 TAES 5337 2 19 42 BA 356 12 41 Emerald 6 40 TAES 1543 17 36 BA 358 13 34 TAES 3588 12 33 TAES 2430 10 31 TAES 5305 48 10 31 TAES 5335 3 13 24 TAES 5330 23 13 13 14 38 £ 2011 genotype means are based upon 24 Aug. data.

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90 Table 3 5 Turf Performance Index for sun vs. s had e genotype c omparisons for relative chlorophyll c ontent 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI BA 332 11 BA 361 11 BA 422 11 TAES 1543 11 TAES 5269 24 11 TAES 5335 3 11 TAES 5337 2 11 Diamond 11 Empire 11 UltimateFlora 11 Zorro 11 BA 357 ** 10 Shadow Turf 10 BA 182 ** 10 BA 252 10 BA 306 10 BA 309 10 BA 328 ** 10 BA 356 ** 10 BA 358 10 TAES 1567 10 TAES 2430 10 TAES 4360 10 TAES 5300 10 TAES 5305 48 10

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91 Table 3 5 Continued 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI TAES 5 330 23 10 TAES 5332 52 10 TAES 5332 53 10 TAES 5257 8 9 TAES 5306 45 ** 9 TAES 5333 53 9 PristineFlora 9 UFZ03 ** 9 UFZ10 ** 9 BA 152 ** 8 BA 336 ** ** 8 TAES 5331 34 ** 8 BA 188 7 BA 402 ** 7 TAES 3363 7 TAES 3588 7 JaMur ** 7 Emerald ** ** 6 *, ** Sun versus shade environments were different within an entry at p < 0.05 and p < 0.01 respectively. TPI = Performance Index and is the number of dates that an entry was not different for percent cover between sun and shade enviro nments TPI range= 6 11

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92 Tab le 3 6 Zoysiagrass genotype mean relative chlorophyll content under 60% shade for November 2010 and August 2011, Citra, FL. Entry 2010 2011 £ TAES 5332 53 135.0 295.0 BA 332 179.7 267.7 TAES 5305 48 110.3 257.0 UFZ10 117.3 253.0 UFZ03 106.3 249.7 BA 358 115.0 246.0 TAES 3363 120.3 241.3 PristineFlora 180.7 239.0 TAES 5300 125.7 236.3 TAES 5335 3 115.0 233.7 Zorro 164.3 232.3 Empire 123.3 232.0 TAES 5331 34 100.3 229.0 BA 356 131.3 224.7 TAES 5257 8 114.3 223.3 BA 152 137.3 222.0 Shadow Turf 173.0 221.0 Emerald 129.7 219.7 BA 328 168.0 218.7 TAES 5306 45 124.0 214.7 BA 309 156.3 214.3 BA 422 129.7 214.0 BA 306 93.0 206.3 TAES 2430 121.0 206.0 JaMur 128.0 204.0 BA 361 157.0 203.0 BA 336 132.3 197.0 BA 357 157.0 197.0 TAES 1543 159.0 196.3 BA 252 143.7 195.3 TAES 5269 24 126.0 193.0 TAES 4360 149.7 192.3 TAES 3588 95.0 186.7 Diamond 136.7 183.0 UltimateFlora 170.3 179.3 TAES 5337 2 115.3 173.7 BA 188 115.7 173.3 TAES 5332 52 158.0 173.0 BA 402 107.7 168.7 BA 182 111.0 167.0 TAES 5330 23 153.0 160.0 TAES 5333 53 136.7 149.7 TAES 1567 122.7 144.0 48.1 7 0.5 £ 2011 genotype means are based upon 24 Aug. data.

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93 Table 3 7 Turf Performance Index for sun vs. shade genotype comparisons for leaf o rientation 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI BA 182 11 BA 252 11 TAES 4360 11 TAES 5257 8 11 TAES 5269 24 11 TAES 5306 45 11 TAES 5337 2 11 Zorro 11 BA 356 ** 10 BA 358 ** 10 TAES 3363 ** 10 TAES 5305 48 ** 10 TAES 5332 52 ** 10 Diamond ** 10 Emerald ** 10 PristineFlora ** 10 UFZ03 ** 10 BA 152 ** ** 9 BA 188 ** ** 9 BA 306 ** 9 BA 357 ** ** 9 BA 402 ** ** 9 TAES 1543 ** ** 9

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94 Table 3 7 Continued 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI TAES 3588 ** 9 TAES 5300 ** ** 9 TAES 5332 53 ** 9 JaMur ** ** 9 UFZ10 ** ** 9 TAES 1567 ** ** 8 TAES 2430 ** ** ** 8 TAES 5330 23 ** ** ** 8 TAES 5331 34 ** ** ** 8 TAES 5333 53 ** ** ** 8 Empire ** ** ** 8 UltimateFlora ** ** ** 8 BA 336 ** ** ** 7 TAES 5335 3 ** ** ** 7 BA 361 ** ** ** 6 BA 422 ** ** ** ** 6 Shadow Turf ** ** ** 6 BA 309 ** ** 5 BA 332 ** ** 5 BA 328 ** ** ** 4 *, ** Sun versus shade environments were different within an entry at p < 0.05 and p < 0.01 respectively. TPI = Performance Index and is the number of dates that an entry was not different for percent cover between sun and shade enviro nments. TPI range = 4 11

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95 Table 3 8. Zoysiagrass genotypes mean leaf orientation under 60% shade for August 2011, Citra, FL. Entry 2011 £ BA 306 1.3 Diamond 1.3 Emerald 1.3 TAES 3588 1.3 BA 152 1.7 BA 252 1.7 BA 356 1.7 BA 357 1.7 BA 358 1.7 PristineFlora 1.7 TAES 1567 1.7 TAES 5257 8 1.7 BA 309 2.0 BA 328 2.0 BA 332 2.0 BA 336 2.0 BA 361 2.0 BA 422 2.0 Shadow Turf 2.0 TAES 4360 2.0 Zorro 2.0 TAES 3363 2.3 TAES 5269 24 2.3 TAES 5305 48 2.3 UFZ03 2.3 BA 182 2.7 BA 188 2.7 BA 402 2.7 TAES 5332 52 2.7 TAES 5332 53 2.7 TAES 5333 53 2.7 TAES 5337 2 2.7 Empire 3.0 JaMur 3.0 TAES 1543 3.0 TAES 2430 3.0 TAES 5300 3.0 TAES 5306 45 3.0 TAES 5330 23 3.0 TAES 5331 34 3.0 TAES 5335 3 3.0 UFZ10 3.0 UltimateFlora 3.0 0.05) 0. 8 £ 2011 genotype means are based upon 24 Aug. data.

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96 Table 3 9 Turf Performance index for sun vs. shade genotype comparisons for percent green c over 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI BA 422 11 TAES 1543 11 TAES 3363 11 TAES 5300 11 TAES 5305 48 11 TAES 5332 53 11 BA 402 ** 10 TAES 5330 23 10 Diamond ** 10 Shadow Turf 10 UFZ10 10 BA 306 9 BA 336 ** ** 9 BA 361 ** 9 TAES 1567 ** 9 TAES 5306 45 ** 9 TAES 5332 52 9 TAES 5335 3 9 TAES 5337 2 9 Empire ** ** 9 UFZ03 ** 9 UltimateFlora ** 9 BA 182 8

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97 Table 3 9. Continued 2010 2011 Entry 21 Sep 12 Oct 8 Nov 27 Mar 17 Apr 7 May 30 May 22 Jun 7 Jul 4 Aug 24 Aug TPI BA 188 ** 8 BA 309 ** 8 BA 357 8 BA 358 ** 8 TAES 2430 ** 8 TAES 4360 ** 8 TAES 5257 8 ** 8 TAES 5269 24 ** ** 8 TAES 5331 34 ** 8 JaMur 8 Zorro ** 8 BA 152 ** 7 BA 328 ** ** 7 BA 332 7 TAES 3588 7 TAES 5333 53 ** 7 PristineFlora ** 7 BA 252 ** 6 BA 356 ** 6 Emerald ** 5 *, ** Sun versus shade environments were different within an entry at p < 0.05 and p < 0.01 respectively TPI = Performance Index and is the number of dates that an entry was not different for percent cover between sun and shade enviro nments. TPI range= 5 11

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98 Table 3 10. Zoysiagrass genotype mean percent green cover under 60% shade for November 2010 and August 2011, Citra, FL. Entry 2010 2011 £ BA 252 55 93 TAES 5300 51 89 TAES 5332 53 61 89 TAES 5306 45 43 88 BA 358 55 87 TAES 1567 43 87 TAES 5257 8 60 87 TAES 5330 23 38 87 UltimateFlora 60 87 Emerald 57 86 BA 328 64 84 TAES 5333 53 48 84 BA 356 65 83 Empire 53 83 TAES 5305 48 53 83 BA 188 55 82 BA 332 64 82 BA 357 53 82 BA 422 57 82 TAES 5332 52 54 82 BA 182 43 81 BA 336 48 81 TAES 2430 43 81 TAES 4360 45 81 BA 152 63 80 BA 309 60 80 PristineFlora 65 80 TAES 1543 75 80 TAES 5331 34 59 79 TAES 5337 2 67 79 Diamond 54 78 TAES 3588 48 77 UFZ10 47 77 JaMur 53 76 TAES 3363 69 76 Zorro 59 76 TAES 5269 24 56 75 UFZ03 50 75 BA 306 52 74 TAES 5335 3 57 73 BA 402 34 71 Shadow Turf 57 68 BA 361 56 55 LSD (p 0.05) 25 1 5 £ 2011 genotype means are based upon 24 Aug. data.

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99 Table 3 11. Total turf performance index of zoysiagrass genotypes Genotype PPE RCC LA PGC TTPI Diamond 11 11 10 10 42 TAES 1543 10 11 9 11 41 TAES 5269 24 11 11 11 8 41 TAES 5337 2 10 11 11 9 41 TAES 4360 11 10 11 8 40 TAES 5332 53 10 10 9 11 40 BA 306 11 10 9 9 39 BA 422 11 11 6 11 39 Empire 11 11 8 9 39 TAES 5305 48 8 10 10 11 39 UFZ10 10 9 9 10 38 Zorro 8 11 11 8 38 BA 361 11 11 6 9 37 BA 358 8 10 10 8 36 TAES 5300 6 10 9 11 36 TAES 5306 45 7 9 11 9 36 TAES 5332 52 7 10 10 9 36 TAES 5335 3 9 11 7 9 36 TAES 5257 8 7 9 11 8 35 UltimateFlora 7 11 8 9 35 TAES 5330 23 6 10 8 10 34 BA 152 9 8 9 7 33 BA 182 4 10 11 8 33 BA 252 6 10 11 6 33 UFZ03 5 9 10 9 33 BA 356 6 10 10 6 32 BA 357 5 10 9 8 32 TAES 5331 34 8 8 8 8 32 TAES 5333 53 8 9 8 7 32 BA 188 7 7 9 8 31 BA 336 7 8 7 9 31 BA 402 5 7 9 10 31 PristineFlora 4 9 10 7 30 Shadow Turf 4 10 6 10 30 TAES 3363 2 7 10 11 30 JaMur 5 7 9 8 29 TAES 1567 2 10 8 9 29 BA 309 5 10 5 8 28 TAES 2430 2 10 8 8 28 BA 332 4 11 5 7 27 TAES 3588 2 7 9 7 25 BA 328 3 10 4 7 24 Emerald 0 6 10 5 21 TTPI = total turf performance index, combining individual TPI values from PPE (percent plot) establishment), RCC (relative chlorophyll content), LA (leaf angles), and PGC (percent green cover)

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100 CHAPTER 4 CONCLUSIONS Water availability and shade are both abiotic stresses that can cause major reductions in turfgrass quality and functionality. The methods used in the current studies adequately identified differences between both genotypes and species of zoysiagrass for their responses to these stresses in 2010 and 2011. In the dry down study, 65 total entries were planted in t wo locations. The Agronomy Forage Research Unit (AFRU) plots located in Hague, FL were planted under a permanent rainout shelter while the Plant Science Research and Education Unit (PSREU) plots located in Citra, FL were not. The AFRU location did not prov ide useful information in determining differences between genotypes and species of zoysiagrass. The presence of an impermeable soil l ayer allowed for subsurface movement of water into the rainout shelter which prevented adequate dry down response. The PSREU lo cation allowed for the observation of differential responses between genotypes and species for color, density, quality, leaf firing, and percent green cover (PGC), although mole cricket damage may have impacted 2011 results. In the shade study, 43 entries were planted in PSREU under a shade house constructed of 60% shade cloth. With differences in amount of entries, several genotypes included in the dry down study were not selected for evaluation in the shade study. In the dry down study, Z. matrellas entri es showed reductions in color, quality, and increased leaf firing quicker than Z. japonicas entries The shade study showed that shade within a species generally resulted in reduced values for percent plot establishment (PPE), relative chlorophyll content (RCC), PGC and more upright leaf angles for both Z. japonica and Z. matrella Though all these para meters provided

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101 valuable information, RCC did not provide a clear trend therefore, it may be beneficial to select an alternate parameter to observe under shaded co nditions in future research. A total turf performance index table (TTPI) was constructed for both dry down and shade studies to evaluate responses to stress on a genotypic level. The TTPI for the drought study gave a clear representation of which genotypes were able to able to avoid drought induced damage by either maintaining a higher rating thro ugh dry down for a given parameter, by minimizing percent change of a parameter through dry down or a combination of both. Experimental line BA 182 had the highest TTPI value (11) and five JaMur DALZ 8516, TAES 5331 34, TAES 5257 8, and Meyer This study provided evidence of genotypic advantages which may be attributed to deep rooting and evapotranspiration (ET) control; however, ET control may lead to greater water savings. Thus both rooting an d ET should be utilized when selecting for drought responses in future research. Originally for the shade study, a turf performance index (TPI) table was generated to evaluate genotype performance between sun and shade environments; however; it was necessa ry to evaluate competitiveness with in only the shade environment Therefore, a TTPI table was generated to evaluate each genotypes performance between light environments and within the shade alone. Diamond had the highest TTPI value (42) with a maximum po ssible TTPI value of 44. Five additional genotypes had 24, TAES 5337 2, TAES 4360, and TAES 5332 23. This study showed variability in responses to shade alone and between full sun and 60 percent shade for both Z. japonica and Z. matrella. The results

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102 suggest that the potential exists for the breeding of zoysiagrass with improved shade tolerance in future research. To determine overall genotype performance across both studies, TTPI values fro m both experime nts were grouped to give a combined total turf performance index value (CTTPI) with a maximum value of 55. Ten of the 12 genotypes that were previously mentioned for having the highest TTPI values in the presence of drought and shade stress had CTTPI value followed by TAES 5269 24 with a CTTPI value of 45, BA 182, TAES 4360, TAES 5257 8, and TAES 5337 2 with a CTTPI of 44, and Diamond and TAES 5332 53 with a CTTPI value of 43. Those genotypes with either hi gh dry down or shade TTPI values that had a 34 and JaMur with a CTTPI value of 41 and 39, respectively. mentioned as having high TTPI value s for either dry down or shade stress. They included TAES 5305 48, Empire and TAES 5300 with CTTPI values of 46, 44, and 43, respectively. Genotypes DALZ 8516 and Meyer where two genotypes that had high TTPI values in the dry down study but were not inclu ded in the shade study. Therefore, no CTTPI values were calculated for these genotypes. The methods used in these two studies adequately identified differences between genotypes and species of zoysiagrass for response to dry down and shade stress and thus certain zoysiagrass species may be better suited for a particular abiotic stress or stresses. In addition variation existed between genotypes for both dry down and shade responses allowing for further selection and improvement of zoysiagrass genotypes.

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103 A) B) Figure 3 1. Shade e xperiment. A) Full sun treatment. B) 60% s hade treatment

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104 *, Treatments were different at p < 0.05 respectively. Figure 3 2. Species sun vs. s hade c omparisons for p ercent p lot e stablishment

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105 *, Treatments were different at p < 0.05 respectively. Figure 3 3. Species sun vs. shade c omparisons for r elative c hlorophyll c ontent

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106 *, Treatments were different at p < 0.05 respectively. Figure 3 4. Species s un vs. s hade c omparisons for l eaf o rientation

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107 *, Treatments were different at p < 0.05 respectively. Figure 3 5. Species s un vs. s hade c omparisons for p ercent g reen c over

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108 LIST OF REFERENCES Anderson, M.C. 1964. Studies of the woodland light climate. II. Seasonal variations in the light climate. J. Ecol. 52:643 663. Anderson, S.J. 2000. Taxonomy of Zoysia (Poaceae) morphological and molecular variation. Doctor al Dissertation. Texas A&M University, USA. Anonymous. 1994. Zoysia matrella Timely Turf Topics. USGA Green Section, Beltsville, MD. 4. Baldwin, C.M., H. Liu, a nd L.B. McCarty. 2008. Diversity of 42 bermudagrass cultivars in a reduced light environment. II International Conference on turfgrass science and management for sports f ields. Acta Hort. (ISHS) 783: 147 158. Barrios, E.P., F.J. Sundstrom, D. Babcock, a nd L. Leger. 1986. Quality and yield response of four warm season lawngrasses to shade c onditions. Agron. J. 78:270 273. Beard, J.B. 1973. Turfgrass: Science and culture. Engelwood Cliffs, NJ: Prentice Hall. Beard, J.B. 1997. Shade stresses and adaptation mec hanisms of Turfgrasses.International Turfgrass Society. 8: 1186 1195 Beard, J.B. 2012. Origin, Biogeographical Migrations, and Diversifications of Turfgrasses. Turfgrass History and Literature. SR130. Beard, J.B., and R.L. Green. 1994. The role of turfgrasses in environmental protection and their benefits to humans. J. Environ. Qual. 23:452 460. Beard, J.B., and S.I. Sifers. 1997. Genetic diversity in dehydration avoidance and drought resistance within the Cynodon and Zoysia species Turfgrass J. 8: 603 610. Bell, G.B and K. Danneberger. 1999. Managing creeping bentgrass in shade. Golf Course Management 56 60. Boyer, J.S.1970. Leaf enlargement and metabolic rates in corn, soybean, and sunflower at various leaf water potentials. Plant Physiol. 46:233 235. Braman, S.K., A.F. Pendley, R.N. Carrow, and M.C. Engelke. 1994. Potential resistance in zoysiagrass to tawny mole crickets. ( Orthoptera Gryllotalpidae ). Florida Entomologist. 77(3):301 305. Brede, D., and S. Sun. 1995. Diversity of turfgrass germplas m in the Asian rim countries and potential for reducing genetic vulnerability. Crop Sci. 35:317 321.

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109 Burton, G.W., J.E. Jackson, and F.E. Knox. 1959. The influence of light reduction upon the production, persistence and chemical composition of Coastal Berm udagrass, Cynodon d actylon Agron. J. 51:537 541. Carrow, R.N. 1996. Drought resistance aspects of turfgrasses in the Southeast: root shoot responses. Crop Sci. 36:687 694. Carrow, R.N., and D.D. Duncan. 2003. Improving drought resistance and persistence i n tur f type tall fescue. Crop Sci 43:978 984 Christians, N. 1949. Fundamentals of Turfgrass Management. Ann Arbor Press. Chelsea, Michigan. City of Tampa Water Management District, 2010. Water Conservation. Template [Online] http://www.tampagov.net/dept _water/files/WUR_and_Rate_Ordinances/Tampa_C ode_Sec26 97.pdf. Cockerham, S.T., S.B. Ries, G.H. Riechers, and V.A. Gibeault. 2002. Turfgrass growth response under restricted lights: growth chamber studies. California Turfgrass Culture 52:13 17. Cunningham, I.S. 1984. Frank N. Meyer: Plant hunter in Asia. Iowa State University Press, Ames IA Ebdon, J.S., and Petrovic, A.M. 1998. Morphological and growth characteristics of low and high water use Kentucky bluegrass cultivars. Crop Sci. 38:143 152. Engelke, M. C., and J.J. Murray. 1982. Zoysiagrass exploration in the Orient. Report to USGA Green Section, Far Hills, N.J. Evans, G.C. 1939. Ecological studies on the rain forest of southern Nigeria. II. The atmospheric environmental conditions. J. Ecol. 27:436 482. Evans, G.C. 1956. An area survey method of investigating the distribution of light intensity in woodlands, with particular reference to sunflecks. J. Ecol.44:391 427. Reporte r 15:7 9. Fu, J., J. Fry, and B. Huang. 2004. Minimum water requirements of four turfgrasses in the transitional zone. Hort Sci. 39:1740 1744. Fuentealba, M.P. 2010. Root depth development and transpiration response to soil drying of warm season turfgrass USA.

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115 BIOGRAPHICAL SKETCH Christian Thomas Christensen was raised by Tom and Brenda Christensen along with two sisters and a brother. He spent the majority of his life in Wellington, Florida, a city known for beautiful homes and landscaping. Thomas Christensen owned a family home constructio and plants. Christian pursued his love for plant biology and graduated from the University of Florida in 2009 with a Bachelor of Sciences degree in Botany. He then continued to work with D r. Kenworthy in the Agronomy department at the University of Florida specializing in turfgrass breeding and genetics. His experiences have built him into a better man and looks forwarding to continuing his education.