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In Season and Transition Performance of Ryegrasses and Roughstalk Bluegrass under Golf Course Fairway Conditions


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IN SEASON AND TRANSITION PERF ORMANCE OF RYEGRASSES AND ROUGHSTALK BLUEGRASS UNDER GOLF COURSE FAIRWAY CONDTIONS By ASA JOEL HIGH A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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This work is dedicated to my family: my mother for her never-ending encouragement and support of my education, my father for teachi ng me to respect and enjoy life, and to my brother for always being there when I really needed him.

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iii ACKNOWLEDGMENTS I would like to thank Dr. Grady L. Miller, chair of my committee, for his support and guidance while I completed this work. I must also th ank him for taking a chance on me and allowing me the opportunity to be the resident at the Envirotron Turfgrass Research Facility while pursuing my master’s de gree. I am also grateful for the help and support of my other committee members Dr. Phil Harmon, Dr. Kevin Kenworthy, and Dr. Carol Stiles. Also, I would like to thank Jason Haugh and Jan Weinbrecht for their friendship, support, and willingness to help in all aspects of this project. Special thanks go to Todd Wilkinson, Golf Course Superintendent, a nd his assistant, John Drouse, for their assistance and for use of their f acility to conduct this research. I would also like to thank the Natio nal Turfgrass Evaluation program in conjunction with the United States Golf Asso ciation and the Golf Course Superintendents Association of America for fundi ng portions of this research.

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iv TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES.............................................................................................................vi LIST OF FIGURES..........................................................................................................vii ABSTRACT.....................................................................................................................vi ii CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................3 Overseeding Culture.....................................................................................................3 Annual Ryegrass....................................................................................................5 Intermediate Ryegrass...........................................................................................6 Perennial Ryegrass................................................................................................6 Roughstalk Bluegrass............................................................................................7 Spring Transition...................................................................................................8 Heat Stress and Turfgrass Physiology........................................................................10 Turf Growth and Transition Modeling.......................................................................11 Heat Unit (Degree Day) Modeling......................................................................11 Cumulative Growth Potential..............................................................................12 Percent Ryegrass Disappearance.........................................................................13 National Turfgrass Evaluation Program.....................................................................13 Turfgrass Evaluation Methods....................................................................................14 Visual Evaluation of Turfgrasses........................................................................14 General Methods.................................................................................................14 Turfgrass Quality.................................................................................................15 Genetic Color.......................................................................................................15 Turfgrass Density................................................................................................15 Percent Living Ground Cover.............................................................................15 Turfgrass Texture................................................................................................16 Digital Image Analysis........................................................................................16

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v 3 AN EVALUATION OF TURF GRASSES FOR OVERSEEDING BERMUDAGRASS FAIRWAYS..............................................................................17 Introduction.................................................................................................................17 Materials and Methods...............................................................................................18 Results and Discussion...............................................................................................21 2004-2005 Turf Establishment, Qualit y, and Transition Performance...............24 2005-2006 Turf Establishment, Qualit y, and Transition Performance...............29 2004-2006 Overseed Density and Texture..........................................................31 Visual and Digital Color Analysis.......................................................................33 Disease Incidence................................................................................................34 Shear Strength.....................................................................................................34 Conclusions.................................................................................................................35 4 AN EVALUATION OF THREE MOD ELS TO PREDICT TURFGRASS OVERSEED TRANSITION......................................................................................37 Introduction.................................................................................................................37 Materials and Methods...............................................................................................38 Turf and Weather Data Sets................................................................................38 Florida Turfgrass Transition Model....................................................................39 Cumulative Growth Potential and Ryegrass Disappearance Models..................39 Results and Discussion...............................................................................................40 Soil Temperature and Days After Seeding Variables..........................................40 Growth Potential Model......................................................................................41 Ryegrass Disappearance......................................................................................43 Conclusions.................................................................................................................45 5 SUMMARY AND CONCLUSIONS.........................................................................47 APPENDIX A 2004-2006 ON-SITE TESTING GRASSES, SPECIES, AND COMPOSITION......49 B DENSITY RATINGS FOR 2004-2005 AND 2005-2006 GROWING SEASONS...50 C CULTIVAR VISUAL AND DGCI COLOR MEANS..............................................51 REFERENCES..................................................................................................................52 BIOGRAPHICAL SKETCH.............................................................................................55

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vi LIST OF TABLES Table page 3-1 Germination and seed count data for each of the cultivars in the evaluation...........22 3-2 Mean square from combined analyses of variance for cove r and quality ratings of the cool-season overseed turfgrasses...................................................................25 3-3 Percent cover of overseeded grasses f our and six weeks after seeding for the 2004-2005 trial.........................................................................................................26 3-4 Quality ratings of overseeded grasses for the 2004-2005 season.............................28 3-5 Percent cover of overseeded grasses f our and six weeks after seeding for the 2005-2006 trial.........................................................................................................30 3-6 Quality ratings of overseeded grasses for the 2005-2006 season.............................31 3-7 Mean square from combined analyses of variance for density and texture ratings of the cool-season overseed turfgrasses...................................................................32 3-8 Mean square from combined analyses of variance for color analysis using visual ratings and digital analysis of DGCI........................................................................33 3-9 Mean square from analysis of vari ance for dollar spot centers during 2004-2005 growing season.........................................................................................................34 3-10 Mean square from analysis of variance for in situ shear strength (kg force) for both years.................................................................................................................35 4-1 Comparison of r values for Ryegra ss Disappearance (RD) Model (Horgan and Yelverton, 2001) and the Florida Ry egrass Disappearance Model (FRD)..............43 A-1 On-Site testing grasses, species, and composition...................................................49 B-1 Density ratings for 2004-2005 and 2005-2006 growing seasons.............................50 C-1 Visual and DGCI color rati ngs for both growing seasons.......................................51

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vii LIST OF FIGURES Figure page 3-1 Average weekly soil temperatures taken 10cm below soil surface for the 20042005 evaluation........................................................................................................23 3-2 Average weekly soil temperatures taken 10cm below surface for the 2005-2006 evaluation.................................................................................................................24 4-1 Graphical comparison of Percent Grow th Potential (Gelernter and Stowell, 2005) and actual percent cover data from two years of overseed evaluation trials.42 4-2 Graphical comparison of Ryegrass Disappearance (RD) Model (Horgan and Yelverton, 2001) and Florida Ryegrass Disappearance (FRD) Model....................44 4-3 Comparison of RD model (Horgan a nd Yelverton, 2001) and Florida Ryegrass Disappearance Model (FRD)...................................................................................45

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viii Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science IN SEASON AND TRANSITION PERF ORMANCE OF RYEGRASSES AND ROUGHSTALK BLUEGRASS UNDER GOLF COURSE FAIRWAY CONDITIONS By Asa Joel High August 2006 Chair: Grady L. Miller Major Department: Environmental Horticulture Overseeding sports turf areas provides aesthetically pleasing, year-round green turf in southern United States. Turfgrass mana gers are well aware of the influence that turfgrass selection and climate have on overseeding and the spring transition. Advancements in turfgrass breed ing and selection have led to the release of new cultivars for overseeding bermudagrass fairways each year Turfgrass managers constantly seek un-biased evaluations of thes e new turfgrasses for overseed applications. The objectives of this study were to evaluate cultivar s for overseeding bermudagrass fairways and evaluate spring transition using known mode ling techniques. Thirty-one cultivars and blends consisting of perennial ryegrass ( Lolium perenne L.), intermediate ryegrass ( Lolium hybridum L.), and roughstalk bluegrass ( Poa trivialis L.) were overseeded as a randomized complete block design on a bermudagrass ( Cynodon dactylon x C. transvalensis cv. ‘TifSport’) fairway at the Univer sity of Florida Golf Course in Gainesville, FL. The trial was established in early fall of 2004 and terminated in June of

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ix 2005, and repeated the following year with cu ltivars planted in the same location. Percent coverage, overall quality, genetic color, density, textur e, and ability to withstand environmental stresses under fairway conditions were evaluated. Mu lti-variate analysis was used to develop a model based on th e 2004-2006 overseed evaluation trial data to determine the appropriate variables for pr edicting overseed coverage. Historical overseed evaluation data from 2002-2006 were used to evaluate a cumulative growth potential (CGP) model and a ryegrass disa ppearance (RD) model using graphical and linear regression analysis, respectively. The evaluation of the grasses indicated that perennial ryegrass and ryegrass blends were quicker to establish, provided better cover, color, and turfgrass quality than intermedia te ryegrasses and rough stalk bluegrass. Intermediate ryegrass transitioned quickly while maintaining high turf quality. Roughstalk bluegrass was slow to establish and provided poo r coverage. Variation in establishment and cover among species also was observed. The Florida Transition Model was derived to describe overs eed coverage from average soil temperature and days after seeding. Results indicated th at the CGP model could be a valuable tool to turfgrass managers for further understanding the overs eeding process. Lin ear regression of 20022006 overseed coverage provided an accurate RD model for the rapidly increasing spring and summer temperatures of FL.

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1 CHAPTER 1 INTRODUCTION In most of the southern United States overseeding is a common practice used by turfgrass managers to maintain an aesthet ically pleasing green turfgrass year-round. Overseeding does more for sports-turf mana gers than provide year-round beauty. An overseeded turfgrass provides actively growing turf that can withstand traffic, improve playability, and prevent weed invasion bette r than brown, dormant bermudagrass turf. Actively growing turfgrass in winter months also can in crease golf courses profits by increasing the number of rounds played. For these reasons most turfgrass managers sow millions of pounds of seed in the southern re gion of the United States each fall (Morris, 2004). Turfgrass managers are aware that the su ccess of overseeding sports turf areas, especially during spring transition, is dependent on the weather and the proper species of overseed. Many other factors including soil and water quality, pr evious management, and expectations also play a role in the success of the overseeding practice. Turfgrass managers place an emphasis on understanding the climate of their region and making informed decisions when selecting a turfgrass for overseeding. Overseed selection can be difficult for tu rfgrass managers. Each year many new cultivars of overseed turfgrasse s are released. According to Golf Course Management magazine’s 2006 seed update, over fifty turfgr asses are to be rele ased in 2006 (Carson, 2006). Each new cultivar released varies in color, density, texture, vigor, and adaptation to various climates. Thus, it is difficult for tu rfgrass managers to select the most effective

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2 species and cultivar. This quest to impr ove overseed germplasm has created a need for un-biased evaluation of newly released turf grasses over a wide range of environmental conditions. Agronomists and other researchers have de veloped models that can help turfgrass managers deal with climate influenced events such as the timing of insect infestations, disease epidemics, and weed invasion (Geler nter and Stowell, 2005). However, there have been few models that have helped turfgrass managers to understand the climate influenced phenomena of spring transition. Because of the need for performance eval uations of new overseed cultivars and the need for additional research on modeling spri ng transition, two objectives were addresses with this research. The first objective was to evaluate 31 overseed cultivars for fairway use. The second objective was to ev aluate models for spring transition.

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3 CHAPTER 2 LITERATURE REVIEW Overseeding Culture Overseeding is the process of seeding onto an existing turfgrass stand. In fall and winter, cool-season turfgrasses are used to provide regenerative gr owth and green color during the dormant period of warm-season gras ses. When temperat ures drop below 15.5 C (60 F), bermudagrass shoots quit growing; when temperat ures drop below 9.9 C (50 F), bermudagrass loses its green color and ente rs winter dormancy (McC arty et al., 2001). In much of the southern United States ove rseeding golf courses pr ovides year round color on fairways, roughs, tees and putting greens. Common bermudagrass [ Cynodon dactylon (L.) Pers.] has been used extensively as a soil stabilizer, sports turf, and forage for many years in the south eastern United States (Duble, 1996a). Common bermudagrass is a warm-season perennial species widely adapted to both tropical and s ubtropical climates. It spreads by stolons and rhizomes and grows best in climates with high temperat ures, mild winters, and moderate to high rainfall. The bermudagrass adaptation range ex tends northward into the transitional zone of the United States where temperatures rare ly reach -12.2 C (10 F) (Duble, 1996a). Hybrid bermudagrasses ( Cynodon dactylon X C. transvaalenis Burtt-Davy) are used widely in warm climates for both fairways and putting green surfaces. When compared with alternative warm-season turfgrasses, hybrid bermudagrass possesses the best overall turfgrass charac teristics for fairway use and culture, providing an extremely dense, uniform, playing surface (Beard, 2002) Hybrid bermudagrass can withstand

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4 frequent low mowings and recuperates quickly from injury. The most common problems faced by those managing hybrid bermudagra ss are thatch accumulation, poor shade tolerance, and a susceptibility to certain pests (Beard, 2002). Overseeding bermudagrass golf greens a nd fairways has many advantages. Overseeding provides a more aesthetically pl easing golf course, and the growing turf is more tolerant to golf cart traffic, divots, a nd weed invasions (Morri s, 2004). Many resort courses in the south receive their heaviest play during th e fall, winter, and spring; therefore, overseeding can l ead to an increase in reve nue (McCarty et al., 2001). Although there are many advantages, overs eeding has some disadvantages. Weed pressure can increase because annual bluegrass ( Poa annua L.) is hard to control when courses are overseeded consecutively for more than a few years (McCarty et al., 2001). Other problems relate to delayed seed germ ination or distributi on during planting and result in clumps of unsightly ryegrass that are difficult to control. The cool-season grasses also can compete aggressively with bermudagrass well into the summer months thus delaying transition, green-up, and fill-in of the bermudagrass (McCarty et al., 2001). Overseeding can lead to an increase in revenue, but estimated costs of overseeding including seed, water, labor and pesticides make up to 20% of an annual budget on southern golf courses (Ostmeyer, 2004). In St. Augustine, Florida, costs may be as high as $45,000 to $50,000 annually to overseed an entire 18-hole golf course (Ostmeyer, 2004). Turfgrass selection is perhaps the mo st important step when beginning the overseeding process. Prior to 1960 the most common species used for overseeding was annual ryegrass ( Lolium multiflorum Lam.). Seeding rates were as high as 480.6 kg ha

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5 (60 lb 1000 ft) (Turgeon, 2002). These rates are high by today’s standard, but were necessary because of poor quality seed and poor germination among early annual ryegrass cultivars. In addition, annual ry egrass exhibited poor h eat tolerance when mowed low and transitioned quickly leavi ng a poor stand of bermudagrass (Turgeon, 2002). During the 1960’s mixtures and blends of seed were used frequently for overseeding (Turgeon, 2002). It was not uncommon to find mixt ures and blends of fine fescue ( Festuca spp.), bentgrass ( Agrostis spp.), roughstalk bluegrass ( Poa trivialis L.), Kentucky bluegrass ( Poa pratensis L.) and perennial ryegrass ( Lolium perenne L.) (Turgeon, 2002). Mixtures and blends pr ovided enhanced germination, better frost tolerance, greater disease resistance, reduced seeding rates, and smoot her transitions than a single cultivar (Turgeon, 2002). Blends and mixtures continue to be popular choices for many turfgrass managers. Advances in breeding programs have provided turfgrass managers with cultivars of turf-type perennial ryegrasses with qualities early annual ryegrasses lacked (Turgeon, 2002). Turf-type overseeding grasses can be defined as cultivars that have greater cold tolerance, wear tolerance, disease resistance, and persistence than non-turf type cultivars (Dubl e, 1996b). These turf-type cultivars exhibit finer texture, greater density, darker colo r, and better mowing qualities according to Duble (1996b). The overseeding and transiti on processes can be f acilitated greatly by proper turfgra ss selection. Annual Ryegrass Annual ryegrass has lost importance as an overseed the last two decades due to a coarser, more open, growth habit compared to perennial ryegrasses (McCarty et al., 2001). According to McCarty et al. (2001), annu al ryegrass exhibits poor heat and cold tolerance and early death in th e spring that leads to poor transition. Unlike some of the

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6 heat resistant perennial ryegrasses, annual ryegrass will die quickly with warm spring temperatures leaving thin areas of dorm ant bermudagrass (Turgeon, 2002). However, annual ryegrass does have some positive characteristics for overseeding. Annual ryegrass is quicker to germinate than other ryegrasses and is acceptable for fairways and less important areas where color is needed (McCar ty et al., 2001). This is especially true when budget constraints exist (McCarty at al ., 2001). Annual ryegrass is cheaper than perennial ryegrass, and because it is less heat tolerant than perennial ryegrass, it will often transition at a fa ster rate (Han, 2004). Intermediate Ryegrass Intermediate ryegrass ( Lolium hybridum Hausska.) is a hybrid of annual and perennial ryegrasses. Similar to annual ryegra sses, intermediate ryegrasses are quick to germinate but lack heat tolera nce (McCarty et al., 2001). Th ey have a medium texture, are lighter green in color, and have redu ced shoot growth when compared to other ryegrass species (McCarty et al., 2001). Unlike many of the pe rennial ryegrasses, intermediate ryegrasses will usually disappe ar quickly, with increasing temperatures, once bermudagrass begins to grow in the sp ring (McCarty et al., 2001). Morris (2004) found that intermediate ryegrasses had slight ly lower quality ratings than perennial ryegrasses, but they did tran sition faster in the 1999-2001 National Turfgrass Evaluation Program’s on-site fairway trials. Perennial Ryegrass Traditionally, perennial ryegrass is the pr eferred grass for overseeding fairways and roughs. Current cultivars germinate quickly, us ually 5 to 7 days, and have excellent dark green color, superior texture, and better dise ase and traffic resistance compared to annual ryegrass (McCarty et al., 2001). Many cultiv ars of perennial ryegrasses are available for

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7 overseeding. Oregon is the world's major pr oducer of cool-season forage and turfgrass seed. Oregon produces almost two-thirds of the total U.S. cool-s eason grass seed (Young, 1996). Nearly 78,086 ha (192,950 acre) of perennia l ryegrass was harvested for seed in Oregon in 2005 (Young, 2005). Average seed yield is 1,555 kg ha (1,387 lbs acre) (Young, 2005). Most seed produced in the USA is of turf-type cultivars (Young, 1996). A blend of perennial ryegrass cultivars is recommended to provide greater performance over a wide range of conditions (McCarty et al., 2001). Many new turf-t ype cultivars of perennial ryegrass have improved heat tolerances and are more competitive during spring transition than previously used cultivars (McCarty et al., 2001). Many persist well into May, June, and July (McCarty et al., 2001). In Florid a, the recommended seeding rate for perennial ryegrass in fairways is 244 to 732 kg ha (5 to 15 lb 1000 ft) (McCarty et al., 1993). Roughstalk Bluegrass Roughstalk bluegrass is known for having a finer texture and higher density due to a seed count of approximately 8 to 1 by wei ght when compared to perennial ryegrass (McCarty et al., 2001). Primarily used to overs eed greens because of its seed size, in the last five years the National Turfgrass Eval uation Program (NTEP) also has been testing cultivars in fairway situations Rough stalk bluegrass is ge nerally lighter in color, and slower to establish and develop into a dense st and of turf than ryegrass (Morris, 2004). This slower establishment may limit its use as a stand alone species on fairways (Morris, 2004). Rough stalk bluegrass tolerates poorly drained soils and ha s good shade tolerance making it a good choice for tree-lined fairways lacking drainage from heavy native soils (McCarty et al., 2001). It is generally quick er to transition in the spring because it has lower heat tolerance than perennial ryegra ss (McCarty et al., 2001) However, Morris

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8 (2004) found that in Florida and California trials, roughstalk bl uegrass was actually slower to transition than pere nnial ryegrasses. The quickness of roughstalk bluegrass to transition can leave thin dormant bermudagra ss. However, if the roughstalk bluegrass persists, as described by Morris (2004), it may out-compete the underlying bermudagrass. Spring Transition Turfgrass managers who overseed are well aw are of the influence weather can have on the success or failure of overseeding and transition programs (Gelernter and Stowell, 2005). Weather is always the driving force when it comes to the success of overseeding and the spring transition. If cool-season gr asses transition too quickly the warm-season grasses may be weak and unsightly. However, if the cool-season grasses persist they compete with the warm-season grasses for vital light, water, and nutri tion that are needed for a successful spring transition (Gelernter and Stowell, 2005). This problem can be compounded by long term poly-stands of cool-season and warm-season grasses (Gelernter and Stowell, 2005). Superintendents are constantly looking for better ways to transition from cool-season to warm-season grasses. Over the past years several cultural me thods have been employed to enhance the transition process. It is believed among many superintendents that vertical mowing, aeration, and topdressing lead to a successful transition. However, Mazur and Wagner (1987) reported high-intensity vertical mowing and topdressing for overseeded bermudagrass are not effective in promoting bermudagrass emergence in the spring. In fact, vertical mowing was actua lly found to delay the emerge nce of bermudagrass (Mazur and Wagner, 1987; Johnson, 1986). Horgan a nd Yelverton (2001) found that cultural practices did affect perennial ryegrass c overage, but did not hasten its ultimate disappearance. Also, it was found that pl ots receiving core cultivation had lower

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9 bermudagrass shoot density at the end of th e transition period (Horgan and Yelverton, 2001). This was due to the physical remova l of bermudagrass shoots and the stress of coring each treatment duri ng the hot summer months (H organ and Yelverton, 2001). Selective herbicides have successfully re moved cool-season grasses. Chemical transition allows the superint endent to remove cool-seas on grasses quickly without as much concern for weather related issues, a nd the bermudagrass does not have to compete for sunlight, water, and nutri ents (Gelernter and Stowell, 2005). This allows the bermudagrass a chance to become better established early in the normal growing season. Burt and Gerhold (1970) observed that pronamide [3,5-dichloroN -(1,1-dimethyl-2propynyl)-benzamide] completely eliminated or injured most cool-season grasses without affecting the warm-season grasses. Sulfonylur ea herbicides have made transition more predictable, more manageable, and more be neficial for the growth of bermudagrasses (Gelernter and Stowell, 2005). Umeda a nd Towers (2004) tested seven different sulfonylurea herbicides for removing cool-sea son grasses from overseeded bermudagrass. They found applications made at the higher la beled rates effectively removed cool-season grasses from bermudagrass in April a nd May. The products tested included flazasulfuron1, foramsulfuron2, rimsulfuron [N-((4,6-dimethoxypyrimidin-2-yl) aminocoarbonyl)-3-(ethylsulfonyl)-2 pyridin esulfonamide], trifloxysulfuron [2pyridinesulfonamide,[ N-[[(4,6-dimet hoxy-2-pyrimidinyl)amino]carbonyl]-3-(2,2,2trifluoroethoxy)-,monosodium salt, monohydrat e salt, monohydrate]], and chlorsulfuron [2-chloro-N-[(4-methoxy-6-methyl-1 ,3,5-triazin-2-yl) aminiocarbonyl] 1 Chemical name protected by U.S. Patent No 5,922,646. 2 Not currently labeled.

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10 benzenesulfonamide] (Umeda and Towers, 2004). Heat Stress and Turfgrass Physiology In order to fully understand the transiti on of cool-season to warm-season grasses it is important to understand the physiology of the grasses involved in transition and how they react to light and temper ature stress. It was not fu lly understood why cool-season grasses and warm-season grasses differed in th eir ability to handle environmental stresses until the Calvin-Benson or C3 and the Hatch and Slack or C4 carbon fixation cycles were discovered in the 1950’s and 1960’s, respectiv ely (McCarty and Miller, 2002). The discovery of the two carbon fixation methods helped explain why warm-season and coolseason grasses perform differently. The C4 or warm-season grasses are able to withstand higher light intensities and warmer temperatur es than C3 grasses (McCarty and Miller, 2002). Warm-season grasses grow best when expos ed to full sunlight, because C4 plants exhibit a non-saturated growth curve at light intensities f ound in nature (McCarty and Miller, 2002). Cool-season grasses become st ressed because growth curves plateau at one-half full sunlight (McCarty and Miller 2002). Once this occurs, photosynthesis decreases and photorespiration increases. In the spring and summer growth of coolseason plant slows because of light satura tion and high temperatures. During these periods when temperatures increase bermuda grass metabolism changes and dormancy is broken. Cool-season grasses compete for the sunlight needed by be rmudagrass to begin growth in spring. When the cool-season overseeded grasses persist well into spring or summer bermudagrass growth is hindered. A slow transition can lead to bermudagrass death. This is why transition modeling to better understand the role that light and temperature play in spring transition could greatly help turfgrass managers make management decisions.

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11 Turf Growth and Transition Modeling Heat Unit (Degree Day) Modeling Growing degree days, or heat accumulation uni ts, can be used to measure or predict the effect of temperature on bi ological processes (Baskerville and Emin, 1969). The heat accumulation concept has been an excellent resource for many agricultural researchers and is commonly used for modeling plant gr owth (Gbur et al., 1979). Research has shown that understanding the relationship between plant growth and temperature can be helpful for many aspects of agricultural pr oduction (Unruh et al., 1996). Degree day models have helped turfgrass managers schedu le pesticide applications for insects (Tolley and Robinson, 1986), disease (Danneberger, 1983; Danneberger and Vargas, 1984), and weed control (Throssell et al., 1990). Degree day modeling has been used to time plant growth regulator appl ications (Danneberger et al ., 1987; Branham and Danneberger, 1989). The correlation between growth and te mperature in degree day modeling can predict when plants will germinate, mature, or even die (Mullen, 1996). These events in plant development can be measured in “Heat Units” (Mullen, 1996). A heat unit can be defined as the daily minimum temperature pl us the daily maximum temperature minus a previously determined base temperature for the plant species in question (Mullen, 1996). Unruh et al. (1996) defines the base temperat ure as the temperature above which growth takes place and below which the plant is dormant. Limits are often placed on the daily maximum and minimum temperatures, and th ese are called “Growing Degree Days” or degree days (Mullen, 1996). Degree day un its accumulate over a growing season, and thus provide an index of growth (Mulle n, 1996). Degree day modeling has not been applied to the transition of ove rseeded cool-season grasses.

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12 Cumulative Growth Potential Gelernter and Stowell (2005) condsidered the growth requirements for both warmseason and cool-season turfgrasses and devel oped a model to help understand and explain the variable nature of overs eeding programs. The model is based on cumulative growth potential which is a concept to help illustr ate the interaction betw een weather and turf performance (Gelernter and Stowell, 2005). Like degree day modeling the cumulative growth potential model takes into account te mperature data. The growth potential is calculated by the following equation: 2 esd ) optT obsT ( 2 11 100 GP [eq. 1] Where GP = growth potential; obsT = obser ved temperature (C); optT = optimal temperature (C); sd = standard deviation of the distribution (sd warm-season turf = 12; and sd cool-season turf = 10), and e = natura l logarithm base (Gel ernter and Stowell, 2005). According to Gelernter and Stowell (2005) when the growth pot ential is at 100% the turfgrass has reached its optimal growth because temperatures are ideal for the particular turf species. Turf growth is still generally good until 50% because stress is minimal (Gelernter and Stowell, 2005). Once the growth potential falls below 50% the growth is limited, and as it nears 0% growth is halted (Gelernter a nd Stowell, 2005). The percent growth potential can be graphed over time and by overlapping the graphs of warm-season and cool-season turfgrasses a m odel can be constructed for a growing season including the transition peri ods of overseeded bermudagrass.

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13 Percent Ryegrass Disappearance Horgan and Yelverton (2001) found that increased relative humidity and air temperature in Raleigh, NC, accelerate natu ral ryegrass disappearance. Using two cultivars of perennial ryegra sses, ‘Derby Supreme’ and ‘Gat or’, it was found that percent ryegrass disappearance could be modeled with linear regression over two growing seasons (Horgan and Yelverton, 2001). In fi nding that both relative humidity and air temperature were significant in the disappearance of ryegrass, it was noted also that there was no difference between the heat tolerance of the two varieties (Horgan and Yelverton, 2001). The equations used to model the disappe arance of the ryegrasses were as follows: RD = -37.01+3.41(airT) [eq. 2] and RD = -274.7+4.31(RH) [eq. 3] Where RD = ryegrass disappearance; airT = air temperature (C); and RH = relative humidity (Horgan and Yelverton, 2001). National Turfgrass Evaluation Program The National Turfgrass Evaluation Program commonly referred to as NTEP, is designed to coordinate unifor m evaluation trials of turfgr ass varieties and promising selections in the United States and Cana da (Morris and Shearman, 2000). The worldwide turfgrass community has relied heavily on the evaluation of information collected and summarized by NTEP since the early 1980’ s. NTEP is a partnership between the USDA’s Agricultural Research Service, land -grant universities, and turfgrass seed companies (Morris and Shearman, 2000). NTEP is sponsored by the National Turfgrass Federation and the United States Departme nt of Agriculture (Morris and Shearman, 2000). In most cases, NTEP evaluation trials are one of the first steps a new cultivar,

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14 blend, or mixture will go through before bei ng released on the mark et. New turfgrasses should be well adapted for their intended appl ications. To accomplish this goal NTEP has designed trials to collect unbiased cultivar data using very consistent methods over a large range of environmental conditions. Turfgrass Evaluation Methods Visual Evaluation of Turfgrasses The evaluation of turfgrasses is a diffi cult and complex issue (Shearman, 1998). Unlike agricultural crops, it is unreasonable to evaluate turfgrasses us ing methods such as a measure of yield or nutritive value (Shear man, 1998). Turfgrass quality is a subjective measure based on visual estimates of aesthetic qualities such as genetic color, stand density, leaf texture, uniformity, smoothne ss, and growth habit (Shearman, 1998). Trained observers can indeed effectively discer n slight differences in turfgrasses using a visual rating system (Karcher et al., 2001; Karcher and Richardson, 2003; Shearman, 1998). Shearman (1998) and NTEP have created the following guidelines and suggestions for the evaluation of turfgrasses. General Methods Visual ratings require consistency to en sure merit. One person should take the data for a study over the entire duration of a study. Before taking data, a study should be observed. The investigator should walk around the treatments and id entify the range of differences that occur. This process allows the investigator to establish a rating range each time treatments are evaluated and keeps the ratings consistent. NTEP protocol suggests turfgrasses are rated on a one to nine scale and should only be rated in whole numbers. Ideally, evaluations should be made between mi d-morning to early afternoon, when shadows and reflections are minimal. (Shearman, 1998)

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15 Turfgrass Quality Quality ratings take into account the functi onal and aesthetic asp ects of turfgrass. They are based on a combination of color, density, uniformity, texture, and disease or environmental stress. Quality is based on nine being the best and one being the poorest. Quality values of nine are generally reserved for a perfect or ideal grass, while a rating of six is generally considered an acceptable turf. Investigators must keep this in mind when rating turfgrasses. (Shearman, 1998) Genetic Color Genetic color reflects the inherent color of a genotype. The vi sual rating is a one to nine scale, one being light green and nine being dark green. Chlorosis and browning from necrosis are not part of genetic color. Color charts, includi ng Munsell Color Charts for Plant Tissue (GreTagMacbeth LLC, New Windsor, NY), are useful in describing turfgrass color and help in ma intaining consistent visual color ratings. (Shearman, 1998) Turfgrass Density Turfgrass density is a visual estimate of liv ing plants or tillers per unit area. Dead patches in turf are excluded. A visual rating scale of one to nine is used and nine equals maximum density. Turfgrass density can be measured quantitatively by counting shoots in a specified area. However, this pro cess is extremely time consuming and labor intensive. Visual density ratings are highly correlated to counts and require less time and labor. (Shearman, 1998) Percent Living Ground Cover Percent living ground co ver is based on the surface ar ea covered by the originally planted species. Expressed from zero to100%, it is generally used to measure damage caused by insects, disease, environmental st resses and weed infestation. Ratings taken

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16 over a season enable tracking of turfgrass re sponse to various stresses during the growing season. (Shearman, 1998) Turfgrass Texture Turfgrass texture is a measure or estimate of leaf width. Th e visual rating of texture is based on a one to nine scale with one equaling coarse and nine equaling fine. Visual estimate of texture is difficult and less than preci se. However, actual physical measurement is tedious, time consuming and la bor intensive. Care must be taken to measure leaves of similar age and stage of de velopment. Visual ratings of texture can successfully separate cultivars within species. Actual visual estimations of texture should be completed when the turfgrass is activel y growing and not under stress. (Shearman, 1998) Digital Image Analysis Color is a key component of the aesthe tic properties of turfgrass and a good indicator of water and nutrient stress (Beard, 2002). Digital analysis has been shown to quantify color differences among standard Muns ell Plant Tissue color chips, zoysiagrass and creeping bentgrass receiving various N fertility treatments, and bermudagrass varying in genetic color (Kar cher and Richardson, 2003). A Dark Green Color Index DGCI was created from the hue, saturation, a nd brightness values obtained from digital image color analysis for comparison with va lues from subjective visual ratings. DGCI variance is significantly lower than the vari ance when compared to visual ratings of genetic color (Karcher and Richardson, 2003). The accuracy of digital image analysis allows turfgrass researchers to record refl ected turfgrass color on a standardized scale rather that using arbitrary color values (Karcher and Richards on, 2003). This enables valid comparisons of color data to be made across researchers, locations, and years.

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17 CHAPTER 3 AN EVALUATION OF TURFGRASSES FOR OVERSEEDING BERMUDAGRASS FAIRWAYS Introduction In the southern United States oversee ding bermudagrass fairways is a common practice. Overseeding provides an aesthetic ally-pleasing and func tional playing surface during winter months when temperatures drop below 9.9C (50F), and bermudagrass has lost its green color due to winter dormancy (McCarty a nd Miller, 2002). The actively growing turfgrass provided by overseed is more tolerant of traffic, divoting, and weed invasions than dormant bermudagrass (Morris, 2004). Having overseeded turf can add to a golf course’s revenue by increasing the num ber of rounds played during cooler months (Morris, 2004). However, overseeding can add significant costs to a golf course’s budget (McCarty et al., 2001). Costs include seed, water, labor, a nd pesticides and make up to 20% of an annual budget on southern golf courses (Ostmeyer, 2004). Another disadvantage of overseeding is that the persistence of overs eeded turfgrasses into late spring and summer months can have detrim ental effects on the underlying bermudagrass as they compete for light, moisture, and nut rients (Gelernter and Stowell, 2005). Thus, transition, bermudagrass green-up, and fill-in ar e delayed (McCarty et al., 2001). This problem can be combated with the proper sel ection of overseed species and cultivars. Turfgrass managers desire grasses that establish quickly, provide excellent playability, transition appropriate ly, require fewer inputs, and are aesthetically pleasing. Breeding programs have led to the release of many new overseed cultivars each year.

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18 The quest to improve turfgrass performan ce under stressful environmental conditions requires breeding and selecting new germplasm. In addition to breed ing and selection of new cultivars, each year seed companies formulate new mixtures and blends. Timely testing of new cultivars, blends, and mixtures over a range of environmental conditions by university scientists provide s an un-biased evaluation to the breeder and end-user. The objective of this study is to evaluate the suitability of the commercially available species, cultivars, and blends included in the 2004-2006 National Turfgrass Evaluation Program (NTEP) on-site fairway overseed trials for the north central region of Florida. Materials and Methods Thirty-one entries were established at th e University of Florida Golf Course in Gainesville, FL during fall of 2004 and 2005 (Appendix A). Entries included 17 perennial ryegrasses ( Lolium perenne L.), eight perennial ryegrass blends, four roughstalk bluegrasses ( Poa trivialis L.), and two intermediate ryegrasses ( Lolium hybridum Hausska.). The fairway site was selected with the aid of the superintendent to ensure that plots would receive uniform sun light and wear. The University of Florida Golf Course staff provided daily maintenan ce for the plots. Fertilization, irrigation, mowing, and pesticide regimes were applied as determined by the superintendent to provide typical golf c ourse conditions. Prior to planting, the number of seeds g for each cultivar was determined by weighing 100 fully developed seed to th e nearest mg. The number of seeds g was then calculated. This procedure was completed in three replications for each cultivar. Germination tests were completed in germination chambers (Stults Scientific Engineering Corp., Springfield, IL). Ten seeds were germin ated at 21 C (70 F) with 5 mL of water and germination paper in the bottom of Petri dishes. Ge rmination percentages were

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19 calculated from this information and the proce dure was completed in four replications for each cultivar. The fairway was scalped to 0.95 cm ( 0.375 in) from 1.14cm (0.45 in) three days prior to overseeding in 2004 and no seedbed preparation occurred in 2005. The plots were seeded on 18 Oct. 2004 and 25 Oct. 2005 with the 31 entries. Ten days after seeding the plots were mowed at 1.14 cm (0.45 in). Plots were mowed at this height three times per week for the remainder of th e study. Plots were 1.5 m by 6.1 m (5 ft by 20 ft) and arranged in a randomized complete block design with three replications. Entries were seeded onto a ‘TifSport’ bermudagrass ( Cynodon dactylon X C. transvaalenis Burtt-Davy) fairway with a drop sp reader (The Andersons Company, Maumee, OH) at rates of 392.3 kg ha (350 lbs acre) for ryegrass species and blends, and 224.2 kg ha (200 lbs acre) for roughstalk bluegrass. Because overseeding grasses provide a temporary playing surface during th e fall, winter, and spring and are reseeded each year cultivars were seeded in the same plots for two consecutive years (fall 2004 and fall 2005) to prevent un-germinated seed from emerging in the plot of a different cultivar the following year. The 31 entries tested were NTEP so licited grasses from sponsoring companies and commercially availa ble cultivars and blends. Experimental entries that were soon to be commercially available (before the end of the testing cycle) also were permitted. The first fertilization occurred on 1 Nov. 2004 with a 6-2-3 biosolid at a N rate of 17 kg ha (15.2 lbs acre). The second fertilization occurred on 15 Dec. 2004 with a 155-10 granular fertilizer at a N rate of 42 kg ha (37.5 lbs acre). On 30 Jan. the plots were fertilized at a N rate 0.65 kg ha (0.58 lbs acre) with liquid 7-0-0 with Fe and Mg

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20 as a supplement. The final fertilization o ccurred on 23 May with a sulfur coated urea (28-0-0) at a N rate of 244 kg ha (217.7 lbs acre). The plots received no pesticides during the 2004-2005 trial. During the second year the first fertili zation occurred on 6 Dec. 2005 with a 21-0-0 liquid supplemented with Mn at a N rate of 68 kg ha (60.7 lbs acre). On 3 Jan. 2006 the trial was fertilized with at 28-0-0 slow release material at a N rate of 3.25 kg ha (2.9 lbs acre). The next fertilization occurred on 17 Jan with IBDU (31-0-0) at a N rate of 69.5 kg ha (62 lbs acre). The final fertilization occurred on 14 Mar. with a N rate using 14-0-14 plus oxadiazon [2-tertbutyl-4-(2,4-dichloro-5-isopropoxyphenyl)-1, 3, 4-oxidiazon-5-one] at 39.2 kg ha (35 lbs acre). The oxidaizon was delivered at a rate of 2.69 kg a.i. ha (2.4 lbs a.i. acre) The plots were also sl it injected with fipronil [5amino-1-(2,6-dichloro-4-(trifluoromethyl)phe nyl)-4-((1,R,S,)-(trifl uoromethyl)sulinyl) 1-H-pyrazole-3-carbonitrile] on 29 Apr. at a rate of 0.028 kg a.i. ha (0.025 lbs a.i. acre) for the preventative control of mole crickets ( Scapteriscus spp.). Data collected included visual estimates of percent establishment (weekly for first six weeks after seeding), turfgrass quality (weekly during the fall transition, winter and spring transition), genetic color (every other week during the winter and spring transition), percent cover (twice weekly duri ng the winter and spri ng transition), texture (weekly during early spring pe riod), and density (weekly dur ing early spring period). Disease incidence was evaluated counting necr otic spots (centers) in each plot. NTEP Turfgrass Evaluation Guidelines (Shearman, 1998) were followed for all visual ratings. Dark Green Color Index (DGCI) values were obtained (once during the winter period) using digital images and the DGCI calculation (Karcher and Richardson, 2003).

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21 In situ shear strength measurements (kg force) were determined using a Clegg Shear tester (Dr. Baden Clegg Pty. Ltd., St. Jolimont WA) with the insertion of a 49mm wide paddle, 40mm into the soil profile. Weather data was mined from the Florida Automated Weather Network (FAWN) weather station in Citra, FL (FAWN, 2006). The soil temperatures were measured daily 10 cm belo w the soil surface at the Citra location and then the data was computed to provid e average weekly soil temperatures. For analysis all measurements and visual ratings were statistically analyzed as a main-effects model using SAS proc GLM (SAS Institute, 1999). For those traits measured multiple times during the trial the repeated measures were analyzed as split plots in time. Therefore, when the interaction of cultivar year was significant years were analyzed separately. Least significant differences (LSD) at P <0.05 was used to compare cultivar means, whereas contrasts were used to compare species differences. Results and Discussion Seeds g , as described in Table 3-1, showed that ryegrass species did not vary among species, cultivars, and blends. R oughstalk bluegrass species did exhibit significant variation ( P <0.05). Germination rates varied between species and cultivars (Table 3-1). Temperatures were average compared to historical data for north central FL. However, above average warm temperatures were recorded in early January during the 2004-2005 study (Figures 3-1 & 3-2). Frosts occurre d in both years of the trial. April, May, and June were hot dry months for much of Florida.

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22 Table 3-1 Germination and seed count data for each of the cultivars in the evaluation. Cultivar Species Germination* Count* ----%---Seeds g MTV-124 Perennial ryegrass 100 a 554 d Top Hat Perennial ryegrass 100 a 527 d RAM-100 Roughstalk bluegrass 98 ab 4,929 a OSC 116 Perennial ryegrass 98 ab 586 d RAD-OS3 Intermediate ryegrass 98 ab 442 d Flash II Perennial ryegrass 97 ab 547 d Overseeding Eagle Blend Ryegrass blend 97 ab 547 d PRS2 Perennial ryegrass 97 ab 559 d OSC108 Perennial ryegrass 95 abc 543 d Champion GQ Ryegrass blend 95 abc 613 d Covet Perennial ryegrass 95 abc 583 d Futura 2500 Ryegrass blend 95 abc 557 d League Master Ryegrass blend 95 abc 518 d Magnum Gold Ryegrass blend 95 abc 651 d ProSelect Ryegrass blend 95 abc 591 d Winterplay Roughstalk bluegrass 95 abc 4,552 c Marvelgreen Supreme Ryegrass blend 94 abcd 640 d STP Perennial ryegrass 94 abcd 630 d Playmate Ryegrass blend 94 abcd 576 d Colt Roughstalk bluegrass 94 abcd 4,791 ab PR 17 Perennial ryegrass 94 abcd 535 d CRR Perennial ryegrass 94 abcd 625 d IS-IR3 Intermediate ryegrass 93 bcd 452 d IS-OS Perennial ryegrass 93 bcd 482 d OSC110 Perennial ryegrass 93 bcd 510 d Starlite Roughstalk bluegrass 93 bcd 4,587 bc Pick SD Perennial ryegrass 91 bcd 561 d Charger Perennial ryegrass 91 bcd 473 d OS Perennial ryegrass 89 cde 511 d BMX 020383 Perennial ryegrass 88 de 536 d ALS2 Perennial ryegrass 83 e 533 d *Means followed by the same letter are not significantly different at the 0.05 level.

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23 Month OctNovDecJanFebMarAprMayJun Avergage Soil Temp (C) 5 10 15 20 25 30 35 40 Maximum Soil Temperature Minimum Soil Temperature Figure 3-1. Average weekly soil temperat ures taken 10cm below soil surface for the 2004-2005 evaluation.

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24 Month OctNovDecJanFebMarAprMayJun Avg Soil Temp (C) 5 10 15 20 25 30 35 40 Minimum Soil Temperature Maximum Soil Temperature Figure 3-2. Average weekly soil temperat ures taken 10cm below surface for the 20052006 evaluation. 2004-2005 Turf Establishment, Qualit y, and Transition Performance A cultivar by year interaction was observed for both cover and quality ratings when the data was analyzed (Table 3-2). Therefore, the data was analyzed and discussed separately for cover and quality among indi vidual growing seasons. Establishment at four weeks after (18 Nov. 2004) seeding ranged from 23 to 48% in the field study (Table 3-3). With the exception of ‘PR 17’ th e ryegrasses were more established than roughstalk bluegrass entries. Although it s hould be noted that differences were not always significant between ryegrasse s and roughstalk bluegrass entries.

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25 Table 3-2 Mean square from combined analys es of variance for c over and quality ratings of the cool-season overseed turfgr asses from the 2004-2005 and 2005-2006 growing seasons. Mean Square Source of Variation df Cover Quality Cultivar, C 30 4801.5** 63.2** Year, Y 1 613.3** 1.2 C x Y 30 357.4** 3.6** Rep, R 2 188.9** 3.7** Date(Y) 81 57820.9** 19.1** Error 7718 36.7 0.4 CV, % 11.2 9.2 Mean 54.3 6.8 Species, S 3 40836.6** 300.5** Blend vs Perennial rye, PR 1 2033.6** 9.4** Intermediate rye vs PR 1 1902.2* 6.5** PR vs Roughstalk bluegrass 1 105478.3** 794.5** *, ** Indicates significance at 0.05 and 0.01 level, respectively.

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26 Table 3-3 Percent cover of overseeded grasse s four and six weeks after seeding for the 2004-2005 trial. Overseed Cover Cultivar Species 18 Nov 04 2 Dec 04 ---------%---------Magnum Gold Ryegrass blend 48 a 70 a OSC110 Perennial ryegrass 47 ab 65 ab OSC108 Perennial ryegrass 47 ab 66 ab Flash II Perennial ryegrass 47 ab 63 abc Charger Perennial ryegrass 47 ab 57 abcde Champion GQ Ryegrass blend 47 ab 60 abcd STP Perennial ryegrass 45 ab 62abc ProSelect Ryegrass blend 43 ab 60 abcd MTV-124 Perennial ryegrass 43 ab 63 abc Marvelgreen Supreme Ryegrass blend 43 ab 60 abcd CRR Perennial ryegrass 43 ab 63 abc Playmate Ryegrass blend 42 abc 65 ab Pick SD Perennial ryegrass 42 abc 55 bcde Overseeding Eagle Blend Ryegrass blend 42 abc 63 abc OS Perennial ryegrass 42 abc 63 abc Futura 2500 Ryegrass blend 42 abc 53 cde Covet Perennial ryegrass 42 abc 63 abc Top Hat Perennial ryegrass 40 abcd 62 abc PRS2 Perennial ryegrass 40 abcd 53 cde OSC 116 Perennial ryegrass 40 abcd 57 abcde IS-OS Perennial ryegrass 40 abcd 58 abcd IS-IR3 Intermediate ryegrass 40 abcd 57 abcde ALS2 Perennial ryegrass 40 abcd 53 cde RAD-OS3 Intermediate ryegrass 38 abcde 57 abcde BMX 020383 Perennial ryegrass 38 abcde 53 cde League Master Ryegrass blend 37 abcde 57 abcde Colt Roughstalk bluegrass 32 cdef 53 cde Starlite Roughstalk bluegrass 30 def 43 ef RAM-100 Roughstalk bluegrass 28 ef 47 def PR 17 Perennial ryegrass 28 ef 43 ef Winterplay Roughstalk bluegrass 23 f 38 f Means followed by the same letter are not statistically different at the 0.05 level. Six weeks after establishment the ryegra sses and blends exhibited good coverage, (53 to 70%) the exception again being ‘PR 17’ (43%, Table 3-3) Similar to the 4-week establishment ratings the ryegrass entries and blends had higher establishment ratings. Again, not all differences were significant (P < 0.05, Table 3-3). The quality ratings at

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27 this time showed similar results as coverage with the roughstalk bluegrasses and ‘PR 17’ having the lowest quality ratings (Table 3-4) This trend of roughs talk bluegrasses and ‘PR 17’ having lower cover and quality ratings continued until late February. In March there was less than 10% differen ce between coverage ratings for all entries. The majority of the perennial ryegrasses and ryegrass bl ends still exhibited the best coverage ( 75%), but the roughstalk bluegrasses and interm ediate ryegrasses had good coverage, between 60 and 75%. Thirty of the grasses exhibited minimally acceptable quality ratings greater than six (Table 3-4). The roughstalk bluegrass ‘Colt’ ha d the poorest qu ality rating, 4.7 (Table 3-4). During early May and throughout the tran sition period, the time when ryegrasses begin to fade due to heat stress, ‘League Master’ and ‘Playmate’, perennial ryegrass blends, exhibited the highest cool-season gra ss coverage at 35% (Data not shown). They also exhibited mean quality ratings greater than or equal to 6.0 throughout the transition period (Table 3-4). Other plots exhibiti ng high overseed coverage above 33%, good bermudagrass densities, and quality ratings in mid May included the perennial ryegrasses ‘PRS 2’, ‘OSC 108’, ‘OSC110’, ‘PickSD’, a nd the ryegrass blends ‘ProSelect’ and ‘Futura 2500’. These grasses may be the appr opriate choice when turf managers desire predominately cool-season grass to persist into spring and then transition abruptly. Roughstalk bluegrasses, the intermediate ryegrass ‘RAD-OS3’, and ‘PR 17’ exhibited less than 28%, coverage and high bermudagra ss coverage through the transition period. However, ‘RAD-OS3’ exhibited a greater aver age quality rating than others during this period (Table 3-4). As temperatures incr eased in June most of the grasses had transitioned to the point that there were no st atistical differences in coverage (Data not

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28 shown) and very little difference in quality. By the end of June all entries had completely transitioned leaving all plot s with 100% bermudagrass c overage and quality ratings greater than or equal to 7.0 (1 to 9 scale) with the ex ception of ‘Colt’ (6.7, Table 3-4). Table 3-4 Quality ratings of overs eeded grasses for the 2004-2005 season. Quality Rating Cultivar 6 Dec 04 24 Mar 05 5 May 05 16 May 05 6 Jun 05 23 Jun 05 Flash II 7.0 a 7.7 ab 7.0 a 7.2 a 7.0 a 7.3 ab Magnum Gold 7.0 a 7.7 ab 6.7 ab 6.7 abcd 7.0 a 7.7 a OSC116 7.0 a 7.3 abc 6.7 ab 6.5 abcd 7.0 a 7.3 ab ProSelect 6.7 ab 6.7 bcd 6.3 abc 6.5 abcd 6.7 ab 7.0 ab OSC108 6.7 ab 7.3 abc 6.7 ab 6.8 abc 6.7 ab 7.0 ab Top Hat 6.7 ab 6.7 bcd 6.3 abc 6.3 bcd 6.7 ab 7.3 ab OSC110 6.7 ab 7.7 ab 6.3 abc 6.8 abc 6.7 ab 7.0 ab Champion GQ 6.3 abc 7.0 abcd 6.7 ab 6.8 abc 6.3 abc 7.3 ab MTV-124 6.3 abc 8.0 a 7.0 a 7.0 ab 6.3 abc 7.3 ab Overseeding EB 6.3 abc 7.0 abcd 6.7 ab 6.7 abcd 6.3 abc 6.3 b CRR 6.3 abc 7.0 abcd 6.3 abc 6.7 abcd 6.3 abc 7.7 a MG Supreme 6.3 abc 7.3 abc 6.3 abc 6.5 abcd 6.3 abc 7.0 ab League Master 6.3 abc 7.3 abc 6.7 ab 6.8 abc 6.3 abc 6.7 ab IS-OS 6.3 abc 6.7 bcd 6.0 bc 6.5 abcd 6.3 abc 7.0 ab Covet 6.3 abc 7.0 abcd 6.7 ab 6.7 abcd 6.3 abc 7.0 ab STP 6.3 abc 7.0 abcd 6.0 bc 6.5 abcd 6.3 abc 7.3 ab Playmate 6.0 abcd 7.7 ab 6.7 ab 6.8 abc 6.0 abcd 7.3 ab PRS2 6.0 abcd 6.3 dc 5.7 cd 6.5 abcd 6.0 abcd 6.3 b Futura 2500 6.0 abcd 7.0 abcd 6.7 ab 6.8 abc 6.0 abcd 6.7 ab Pick SD 6.0 abcd 7.3 abc 6.7 ab 7.0 ab 6.0 abcd 6.7 ab BMX 020383 5.7 bcde 6.7 bcd 7.0 a 7.0 ab 5.7 bcde 7.0 ab RAD-OS3 5.7 bcde 6.7 bcd 6.0 bc 6.7 abcd 5.7 bcde 7.0 ab ALS2 5.3 cde 6.3 bcd 6.0 bc 6.5 abcd 5.3 cde 7.0 ab OS-IR3 5.3 cde 7.0 abcd 6.3 abc 7.0 ab 5.3 cde 7.7 a OS 5.0 def 6.7 bcd 6.3 abc 6.8 abc 5.0 def 7.3 ab Charger 4.7 efg 6.3 dc 6.7 ab 6.8 abc 4.7 efg 6.7 ab Starlite 4.0 fgh 6.0 d 6.3 abc 6.2 cd 4.0 fgh 7.0 ab RAM-100 4.0 fgh 7.0 abcd 6.0 bc 6.2 cd 4.0 fgh 7.7 a PR 17 3.7 gh 6.3 cd 5.7 cd 6.7 abcd 3.7 gh 7.0 ab Winterplay 3.7 gh 6.3 cd 6.0 bc 6.2 cd 3.7 gh 7.3 ab Colt 3.0 h 4.7 e 5.0 d 6.0 d 3.0 h 6.7 ab Means followed by the same letter are not statistically different at the 0.05 level.

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29 2005-2006 Turf Establishment, Qualit y, and Transition Performance During the second year of the study the coverage again varied between the ryegrasses and the roughstalk bluegrasses. Most of the ryegrasses exhibited good establishment coverage during the first four weeks after planting (Table 3-5). The roughstalk bluegrasses were again much slow er to establish than the most of the ryegrasses. The top performers included ‘Cha rger’, ‘Pick SD’, and ‘ProSelect’ (Table 35). The perennial ryegrass ‘PR 17’ was slow to establish as in the previous year; however, it was not different from other poorer performing ryegrasses at the P < 0.05 level. The roughstalk bluegr asses establishment coverage ranged from 7 to 18% below the poorest ryegrass coverage four weeks after seedi ng (Table 3-5). At six weeks after establishment the roughs talk bluegrasses were still different from other entries (P < 0.05). The top perfor mers at six weeks included ‘Playmate’ and ‘BMX 020383’. Roughstalk bluegrasses were s till 14 to 28% less than the other grasses (Table 3-5). This trend conti nued well into March as in year one of the trial. In early quality ratings the roughstalk bluegrasses and the perennia l ryegrass ‘PR 17’ rated the poorest in quality. In mid April and early May the perennial ryegrasses ‘Playmate’, ‘PickSD’, and the ryegrass blend ‘Champion GQ’ had the highest overall cover ratings as transition began. They also exhibited mean quality ratings of 6.0 on the 1 to 9 scale and were not different (P < 0.05 level) from the majority of the ot her ryegrasses (Table 3-6). The roughstalk bluegrasses did however perform much bett er during the transition period with mean quality ratings ranging from 6.3 to 7.0 (Table 36). The roughstalk bluegrasses ranged in coverage from 30 to 35% with good bermudagrass density (Table 3-5). The intermediate ryegrass ‘RAD-OS3’ exhibited the lowest cover in early May at 30%, but ranked the

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30 highest in quality at the P < 0.05 level. By early June all of the grasses had completed transition leaving 100% bermudagrass cover and average quality ratings of 7.0 on a 1 to 9 scale. Table 3-5 Percent cover of overseeded grasse s four and six weeks after seeding for the 2005-2006 trial. Overseed Cover Cultivar Species 22 Nov 05 1 Dec 05 ---------%---------Charger Perennial ryegrass 53 a 53 abc Pick SD Perennial ryegrass 52 a 57 ab ProSelect Ryegrass blend 52 a 57 ab BMX 020383 Perennial ryegrass 50 ab 58 a Playmate Ryegrass blend 50 ab 58 a Champion GQ Ryegrass blend 48 abc 53 abc CRR Perennial ryegrass 48 abc 53 abc MTV-124 Perennial ryegrass 48 abc 55 abc Overseeding Eagle Blend Ryegrass blend 48 abc 55 abc Futura 2500 Ryegrass blend 47 abc 53 abc League Master Ryegrass blend 47 abc 57 ab Magnum Gold Ryegrass blend 47 abc 55 abc RAD-OS3 Intermediate ryegrass 47 abc 50 abc STP Perennial ryegrass 47 abc 57 ab Top Hat Perennial ryegrass 47 abc 55 abc ALS2 Perennial ryegrass 45 abc 57 ab Flash II Perennial ryegrass 45 abc 53 abc Marvelgreen Supreme Ryegrass blend 45 abc 53 abc OSC 116 Perennial ryegrass 45 abc 55 abc OSC108 Perennial ryegrass 45 abc 53 abc OSC110 Perennial ryegrass 45 abc 53 abc Covet Perennial ryegrass 43 abcd 53 abc IS-OS Perennial ryegrass 43 abcd 48 bc OS Perennial ryegrass 43 abcd 55 abc PRS2 Perennial ryegrass 43 abcd 52 abc IS-IR3 Intermediate ryegrass 40 bcd 52 abc PR 17 Perennial ryegrass 38 cd 47 c Winterplay Roughstalk bluegrass 33 d 33 d Colt Roughstalk bluegrass 18 e 18 e RAM-100 Roughstalk bluegrass 17 e 22 e Starlite Roughstalk bluegrass 15 e 18 e Means followed by the same letter are not statistically different at the 0.05 level.

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31 Table 3-6 Quality ratings of overs eeded grasses for the 2005-2006 season. Quality Rating Cultivar 12 Dec 05 13 Mar 06 2 May 06 16 May 06 23 May 06 7 Jun 06 Flash II 6.7 a 7.0 ab 7.0 a 7.2 a 7.0 a 7.0 a Magnum Gold 6.0 a 7.0 ab 6.7 ab 6.7 abcd 7.0 a 7.0 a OSC116 6.7 a 7.0 ab 6.7 ab 6.5 abcd 6.7 ab 7.0 a ProSelect 6.3 ab 7.0 ab 7.0 a 6.5 abcd 7.0 a 7.0 a OSC108 6.0 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a Top Hat 6.0 a 7.0 ab 6.7 ab 6.3 bcd 6.8 ab 7.0 a OSC110 5.7 a 7.0 ab 7.0 a 6.8 abc 6.7 ab 7.0 a Champion GQ 6.3 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a MTV-124 6.3 ab 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a OEB 6.3 a 7.0 ab 7.0 a 6.7 abcd 6.8 ab 7.0 a CRR 6.3 a 7.3 a 6.7 ab 6.7 abcd 6.8ab 7.0 a MG Supreme 6.3 a 7.3 a 6.7 ab 6.5 abcd 6.7 ab 7.0 a League Master 6.3 a 7.0 ab 7.0 a 6.8 abc 6.8 ab 7.0 a IS-OS 5.7 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a Covet 6.0 a 7.0 ab 6.7 ab 6.7 abcd 6.7 ab 7.0 a STP 6.3 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a Playmate 6.0 a 7.3 a 7.0 a 6.8 abc 7.0 a 7.0 a PRS2 6.0 a 7.0 ab 7.0 a 6.5 abcd 6.7 ab 7.0 a Futura 2500 6.0 a 7.0 ab 7.0 a 6.8 abc 6.8 ab 7.0 a Pick SD 6.3 a 7.0 ab 7.0 a 7.0 ab 6.8 ab 7.0 a BMX 020383 6.3 a 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a RAD-OS3 6.0 a 7.0 ab 7.0 a 6.7 abcd 6.8 ab 7.0 a ALS2 6.0 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a OS-IR3 6.3 a 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a OS 6.3 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a Charger 6.0 a 7.3 a 6.7 ab 6.8 abcd 6.8 ab 7.0 a Starlite 3.7 b 6.7 bc 6.7 ab 6.2 cd 6.3 bc 7.0 a RAM-100 4.0 b 6.7 bc 7.0 a 6.2 cd 6.3 bc 7.0 a PR 17 6.0 a 7.0 ab 6.7 ab 6.7 abcd 6.5 ab 7.0 a Winterplay 4.0 b 6.7 bc 6.7 ab 6.2 cd 6.5 ab 7.0 a Colt 3.7 b 6.3 c 6.3 b 6.0 d 5.8 c 7.0 a Means followed by the same letter are not statistically different at the 0.05 level. 2004-2006 Overseed Density and Texture Density was analyzed and discussed separate ly by year because a cultivar by year interaction was again observed. Perennial ryegrass and ryegrass bl ends exhibited the highest values for density during both years, but were different from one another at the 95% probability level (Table 3-7). Contra st analyses by species indicated perennial

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32 ryegrasses and roughstalk bluegrasses we re not different in density at the P < 0.05 level (Table 3-7). This was probably due to th e high seed count per unit weight of the roughstalk bluegrasses, and the coarseness of perennial ryegrass leaves. Perennial ryegrasses and intermediate ryegrasses were different at the P < 0.05 level (Table 3-7). This could possibly be explaine d by the coarser leaf blades that intermediate ryegrasses possess. The second year of the trial had grea ter average density ratings than year one. However, this variation could likely be due to the higher N rate applied during year two of the study. Specific cultivar texture perf ormance can be referenced in Appendix B. Texture ratings were analyzed across y ears because there was no cultivar by year interaction. There were differences in av erage texture between species at the 95% probability level (Table 3-7). Perennial ry egrass and the ryegrasses blend were not different at the P < 0.05 level. Intermediate ryegrasse s were different from the perennial ryegrasses, and exhibited lower texture ratings th an all of the other species. Intermediate ryegrasses had mean texture ratings below 6.8. The roughstalk blue grasses in the trial exhibited the highest textur e ratings averaging above 7.4, and with ‘RAM-100’ having the highest average texture rating. Table 3-7 Mean square from combined anal yses of variance for density and texture ratings of the cool-season overseed turfgrasses for 2004-2005 and 2005-2006. Mean Square Source of Variation df Density Texture Cultivar, C 30 0.64** 6.41 Year, Y 1 7.75** 61.83** C x Y 30 0.68** 4.80 Rep, R 2 8.80** 6.04 Date(Y) 5 1.98** 16.89 Error 650 0.52 2.77 CV, % 7.37 38.53 Mean 7.05 7.19 Species, S 3 1.75** 33.13* Blend vs Perennial rye, PR 1 1.97** 0.21 Intermediate rye vs PR 1 1.19* 52.41** PR vs Roughstalk bluegrass 1 0.86 48.85* *, ** Indicates significance at 0. 05 and 0.01 level, respectively.

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33 Visual and Digital Color Analysis The highest visual color ratings were the perennial ryegrasses and ryegrass blends in both years. The data was again analy zed separately due to a cultivar by year interaction for both methods of measuring co lor. The perennial ryegrass ‘Pick SD’ was rated higher than all of the gra sses for its deep dark green co lor, with a color rating of 8.1 in the 2004-2005 season and 8.2 2005-2006 s eason (Appendix C). The roughstalk bluegrasses ‘RAM-100’, ‘Colt’, and ‘Winterpla y’ exhibited the poorest color in the first year. Perennial ryegrasses ‘Charger’, ‘PR 17’, and the intermediate ryegrass ‘RAD-OS3’ also exhibited color ratings of less th an 6.0. In 2005-2006 the rough bluegrasses exhibited color ratings below 6.0. Digital colo r evaluations for the first and second year provided different results between trial years at P < 0.05 (Table 3-8). This was probably due to the grasses responding to the hi gher N rates of the 2005-2006 growing season. ‘PickSD’,‘MTV-124’, ‘BMX 020383’, ‘Playmate’ and ‘Futura 2500’ performed the best in both years of DGCI evaluation. Table 3-8 Mean square from combined anal yses of variance for color analysis using visual ratings and digi tal analysis of DGCI. Mean square Source of Variation df Visual Color DGCI Cultivar, C 30 28.88** 0.0001** Year, Y 1 3.74** 0.0029** C x Y 30 1.96** 0.1896* Rep 2 0.52 0.0005 Date(Y) 13†, 4.99** Error 1394†,185‡ 0.50 0.02 CV, % 7.21 4.11 Mean 6.87 0.43 Species, S 3 22.66** 45.58** Blend vs Perennial rye, PR 1 10.55** 4.17* Intermediate rye vs PR, 1 43.07** 2.03 PR vs Roughstalk bluegrass 1 557.56** 113.10** Error 1372 0.64 0.02 CV, % 9.20 4.80 *, ** Indicates significance at 0. 05 and 0.01 level, respectively. †, ‡ values for visual color and DGCI respectively

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34 The digital image analysis verified that th e roughstalk bluegrasses had the poorest color, followed by the intermediate ryegrasses duri ng both seasons. Specific color performance for each cultivar can be referenced in Appendix C. Disease Incidence During the 2004-2005 trial there was an outbr eak of apparent do llar spot symptoms on some of the plots. Small circular, sunke n, straw colored patches were observed. The roughstalk bluegrasses ‘RAM-100’, ‘WinterPla y’, ‘Colt’, and the pe rennial ryegrass ‘PR 17’ had the highest incidence of spots averagi ng at least 24 dollar spot centers for each of these entries. These cultivars had much greate r dollar spot incidence than the rest of the cultivars in the study at the 95% probability level. There were no disease symptoms during the 2005-2006 trial as indi cated by the years being different in Table 3-9. This was probably due to the dry year and higher N fertility. Table 3-9 Mean square from analysis of variance for dollar spot centers during 20042005 growing season. Mean Square Source of Variation df Dollar Spot Centers Cultivar, C 30 1724.41** Date (Year), D (Y) 1 939.38 Rep 2 64.65 C x D (Y) 30 1044.10* Error 185 523.58 CV, % 277.71 Mean 8.24 *, ** Indicates significance at 0.05 and 0.01 level, respectively. Shear Strength In situ shear strength data indicated that there was no difference among entries or years (Table 3-10). This was most likely due to the late season April testing of the shear strength in the 2004-2005 season, as the be rmudagrass had already started rooting.

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35 Table 3-10 Mean square from analysis of variance for in situ shear strength (kg force) for both years. Mean square Source of Variation df Shear Value Cultivar, C 30 230.80 Rep 2 509.63 Year, Y 1 294.39 C x Y 30 201.58 Error 185 0.64 CV, % 18.28 Mean 76.74 Indicates significance at P 0.05 Conclusions This study further indicated that perenni al ryegrass and ryegrass blends provide quick establishment, better coverage, and highe r quality turf than roughstalk bluegrass. Perennial ryegrass entries and blends provided the highest co verage and quality ratings during the transition period further illustra ting the persistent nature of perennial ryegrasses to heat stress during transiti on. Intermediate ryegrasses provided less coverage than perennial ryegrasses during the transition period, yet maintained high overall plot quality. The intermediate ry egrasses transitioned fa ster allowing greater bermudagrass densities during the spring transi tion period, indicating that it may be the most appropriate choice for turfgrass manage rs who wish to maintain good quality and provide less competition for the underlying be rmudagrass. Roughstalk bluegrasses are much slower to germinate and often took most of the season to establish. The roughstalk bluegrasses had low percent coverage and th e poorest quality rati ngs during the spring reaffirming that the species may not be an appropriate choice for use as a stand-alone species for overseeding fairways. Both me thods for evaluating color indicated that perennial ryegrass had the darkest green co lor followed by intermediate ryegrass and roughstalk bluegrass, respectively. With th e many different qualities that overseeding

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36 0species possess, turfgrass managers shoul d take great care to seek out un-biased evaluations of seed cultivars to make the mo st appropriate selecti on for their particular needs. Turfgrass managers must also be aware of variability within sp ecies. The perennial ryegrasses and ryegrass blends varied among cultivars within speci es with respect to establishment, color, quality, density, and cove r. There is less variability among cultivars within the roughstalk bluegrass species. The variation within species is less than that observed between species, but it can influence the success of transition.

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37 CHAPTER 4 AN EVALUATION OF THREE MODELS TO PREDICT TURFGRASS OVERSEED TRANSITION Introduction Turfgrass managers who overseed are well aw are of the influence weather can have on the success or failure of overseeding and transition programs (Gelernter and Stowell, 2005). Weather, especially temperature, is always the driving force when it comes to the success of overseeding and spring transition. If cool-season grasses transition too quickly the warm-season grasses may be weak and uns ightly. However, if the cool-season grasses persist, they compete with the warm -season grasses for light, water, and nutrition that are needed for spring green-up (Geler nter and Stowell, 200 5). When cool-season grasses are left to transition naturally, the bermudagrass growing season can be limited to less than nine weeks (Howard, 2006). Periods of less than 16 weeks for bermudagrass to recuperate and repair from overseeding ar e not adequate (Howard, 2006). Thus, over multiple shortened growing seasons bermuda grass will not endure (Howard, 2006). Turfgrass managers are continuously seeki ng ways to better understand climate and its effect on overseeding, spring tran sition, and bermudagrass health. A mathematical model can be used to better understand the spring transition. Mathematical models have been used to comprehend many aspects of turfgrass culture. Models have been developed to help tu rfgrass managers develop pesticide spray schedules for insects (Tolley and Robi nson, 1986), diseases (Danneberger, 1983; Danneberger and Vargas, 1984), weeds (Throsse ll et al., 1987), and timing of plant

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38 growth regulator appl ications (Danneberger et al ., 1987; Branham and Danneberger, 1989). However, few models have been develo ped to better explai n spring transition. The cumulative percent growth potential mode l mathematically explains the overseeding process and spring transition (G elernter and Stowell, 2005). The growth potential model compares observed temperatures with optimum temperatures for growth of warm and cool season grasses to predic t the potential growth over a s eason (Gelernter and Stowell, 2005). Another model is a percent ryegrass disappearance model (Horgan and Yelverton, 2001). Horgan and Yelverton (2001) found that a linear regression can be used to better understand the relationship between temper ature and relative humidity in the disappearance of ryegrass duri ng spring transition. The objec t of this study was to evaluate spring transition data using th ese known models and modeling techniques. Materials and Methods Turf and Weather Data Sets Percent coverage and ryegrass disappearance data were obtained from four growing seasons for overseed evaluation trials a nd National Turfgrass Evaluation Program (NTEP) on-site fairway overseed evaluations completed in Ga inesville, FL from 2002 to 2004 and from 2004 to 2006, respectively. The tria ls evaluated up to fi ve species of cool season grasses to be commercially marketed as overseed for bermudagrass sports turf. The only data used from these trials were th e percent coverage data. Cool-season grass disappearance was calculated from this data. Weather data was mined from the Florida Automated Weather Network (FAWN) weather station in Citra, FL. The data mined included average daily soil temperatures and average daily air temperatures. The soil temperatures were measured 10 cm below th e soil surface and air temperatures were measured 60 cm above the soil surface (FAWN, 2006). The daily averages were used to

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39 generate average weekly and average monthly temperatures. These data were used to evaluate the three models for predicting spring transition. Florida Turfgrass Transition Model A transition model was developed using N TEP on-site evaluation coverage data from consecutive overseeding trials (20042005 and 2005-2006). The variables, average weekly air temperature, average weekly soil temperature, and days after seeding (DAS), were evaluated using multivariate analysis proc STEPWISE (SAS Institute, 1999) to determine which variables were most appropriate for use in the model. Cumulative Growth Potential and Ryegrass Disappearance Models The two models used for comparison were previously published models that describe overseed performance and spring tr ansition. The cumulative growth potential (CGP) model has been extensively used by th e Pace Turfgrass Research Institute of San Diego, CA (Gelernter and Stowell, 2005). Th e CGP growth potential model was used to calculate the growth potential of warm and cool-season grasses using the following equation and average monthly soil temperat ure data for each of the four years: 2 esd ) optT obsT ( 2 11 100 GP [eq. 1] Where GP = growth potential; obsT = obser ved temperature (C); optT = optimal temperature (31.1C for warm-season turf and 20C for cool-season turf); sd = standard deviation of the distribution (sd warm-season turf = 12; and sd cool-season turf = 10), and e = natural logarithm base (Gelernter and Stowell, 2005) In this study, average monthly coverage data, for the two consecutive years of the NTEP trials, were compared

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40 with the growth potential curves calculated for each year to determine the appropriateness of the CGP model for overseed performance and transition using SigmaPlot (SPSS Inc., 2002). The ryegrass disappearance (RD) model was postulated to describe the transition of ryegrass in Raleigh, NC (Horgan and Yelverton, 2001): RD = -37.01+3.41(airT) [eq. 2] Where RD = ryegrass disappearance and ai rT = air temperature (C) (Horgan and Yelverton, 2001). The r value for the goodne ss of fit about the Horgan and Yelverton (2001) data was 0.51. In this study, the actu al ryegrass disappearance data that was previously calculated from the four years of cover data were subj ected to the RD model equation and the relative fit of the RD model was determined using SigmaPlot (SPSS Inc., Chicago, IL). Linear regression was used to determine a Florida Ryegrass Disappearance (FRD) model based on weekly air temperature and the Florida coverage data from 2002-2006. The FRD model was then subjected to each of the individual growing seasons to determine the fit of the model using SigmaPlot (SPSS Inc., Chicago, IL). Results and Discussion Soil Temperature and Days After Seeding Variables The hypothesis was that overseed coverage and transition performance could best be modeled using soil temperature and th e amount of time after seeding. The multivariate analysis determined that soil temp erature and days afte r seeding provided the highest correlation for a two-va riable model. The analysis of variance provided an R value of 0.54, the highest for the two variable models. The equation of the model for

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41 dependent variable cover with soil temperatur e and days after seedi ng as the independent variables was: OC = 134.46 + 0.16(DAS) – 04.74(soilT) [eq. 3] Where OC = overseed cover; DAS = days afte r seeding; and soilT = average weekly soil temperature. The R value of the analysis i ndicates that 54% of the variability of OC can be accounted for by the variability in DAS a nd soilT. Therefore, the model does predict OC, but not very well. This indicates that more research is needed to determine what variables are most attribut able to OC. Further rese arch should possibly focus on temperature stress, relative humidity, disease stress, shading, solar radiation, moisture, and environmental stresses (e.g. traffic and di voting) to determine a model with a higher probability for predicting OC and spring transition. Growth Potential Model Graphical comparison of the growth poten tial, calculated using the CGP model (Gelernter and Stowell, 2005), and actual percent coverage showed that the actual cover for warm and cool-season grasses were less that the percent growth potential (Figure 41). The growth potential portrays a visu ally accurate slope of establishment and dormancy of cool-season and warm-season gras ses, respectively (Fi gure 4-1), indicating that the time for establishment could be achieved as reported by Gelernter and Stowell (2005). During periods of establishment and dormancy, the CGP model showed fluctuation in the percent grow th potential based on temperature that is not reflected in the actual cover (Figure 4-1). While these fluctuations due to temperature cannot be accounted for in the average monthly cover data they may enable turfgrass managers to determine when established stands of cool -season turf may be experiencing stress. However, additional research would be needed to determine if these fluctuations could

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42 indicate plant stress. The act ual percent cover data lags behind the disappearance of ryegrass and the re-emergence of warm-season grass from dormancy (Figure 4-1). This may make it difficult for turfgrass managers to precisely identify when to spray a herbicide to hasten the spring transition proces s. However, as reported by Gelernter and Stowell (2005) the CGP model is a valuable ai d in determining when there may be a need to spray a transition hasteni ng herbicide so warm-season gras ses have adequate time, 16 weeks (Howard, 2006), to recuperate afte r the spring transition based on visual comparison of CGP and actual cover data (Figure 4-1). 2004-2005 Overseed EvaluationMonth OctNovDecJanFebMarAprMayJun Growth Potential & Cover (0-100) 0 20 40 60 80 100 Warm-Season Growth Potential Cool-Seaspn Growth Potential Measured Warm-Season Cover Measured Cool-Season Cover 2005-2006 Overseed EvaluationMonth OctNovDecJanFebMarAprMayJun Growth Potential & Cover (0-100) 0 20 40 60 80 100 Figure 4-1. Graphical comparison of Percent Growth Potentia l (Gelernter and Stowell, 2005) and actual percent cover data fr om two years of overseed evaluation trials.

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43 Ryegrass Disappearance The regression line that Horgan and Yelverton (2001) proposed for ryegrass disappearance did fit the data for each of the f our years of overseed trials (Table 4-1). Table 4-1 Comparison of r values for Ry egrass Disappearance (RD) Model (Horgan and Yelverton, 2001) and the Florida Ryegrass Disappearance Model (FRD) for 2002-2006 overseeding coverage for Gainesville, FL. r Value Overseed Coverage RD Model FRD 2002-2003 Cover Data 0.53* 0.54 2003-2004 Cover Data 0.41* 0.78 2004-2005 Cover Data 0.31* 0.59 2005-2006 Cover Data 0.18* 0.66 2002-2006 Cover Data 0.34* 0.59 Indicates significance of RD Model (Horgan and Yelverton, 2001) at P <0.05 However, when compared to the Florida Ryegrass Disappearance Model (FRD) determined through linear regression of each of the four years of data, the Horgan and Yelverton RD model had less slope and lower r values for the coverage data (Figure 42). The same results were found when the Ho rgan and Yelverton (2001) model was fit to all transition data from the growing s easons of 2002-2006 (Figure 4-3). This could possibly be explained by higher relative humid ity in Florida and most importantly more rapid rate of temperature increase in the sp ring in Gainesville, FL than in Raleigh, NC. The equation for the Florida Ryegrass Disappearance may more appropriately be: FRD = -96.66 + 6.61(airT) [eq. 4] Where FRD = ryegrass disappearance (0-100%); airT = air temperature (C). This model allows for a more appropriate fit, r = 0.59, in Gainesville, FL with its rapidly increasing temperatures during the spring and early summer.

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44 Air Temperature (C) 10121416182022242628 Ryegrass Disappearance (0-100) 0 20 40 60 80 100 RD = -37.01 + 3.41(airT) r = 0.31 FRD = -96.66 + 6.61(airT) r = 0.59 2004-2005 Cultivar Means 12141618202224262830 RD = -37.01 + 3.41(airT) r = 0.18 FRD = -96.66 + 6.61(airT) r = 0.66 2005-2006 Cultivar Means 0 20 40 60 80 100 RD = -37.01 + 3.41(airT) r = 0.53 FRD = -96.66 + 6.61(airT) r = 0.54 2002-2003 Cultivar Means RD = -37.01 + 3.41(airT) r = 0.41 FRD = -96.66 + 6.61(airT) r = 0.78 2003-2004 Cultivar Means Figure 4-2 Graphical comparison of Ryegra ss Disappearance (RD) Model (Horgan and Yelverton, 2001) and Florida Ryegrass Disappearance (FRD) Model for average cover data from four consec utive years of overseed trials.

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45 Air Temperature (C) 1012141618202224262830 Ryegrass Disappearance (0-100) 0 20 40 60 80 100 Ryegrass Disappearance FRD = -96.66 + 6.61(airT) r = .64 RD = -37.01 + 3.41(airT) r = .39 Figure 4-3 Comparison of RD model (Horgan and Yelverton, 2001) and Florida Ryegrass Disappearance Model (FRD) for averag e cover data from four growing seasons (2002-2006). Conclusions Modeling of overseed and transition can be provided via many methods and can serve as valuable aids to turfgrass mana gers. A model for overseed coverage was determined through multi-variate analysis with average weekly soil temperature and days after seeded. The model was: OC = 134.46 + 0.16(DAS) – 04.74(soilT) [eq. 3] Where OC = percent overseed coverage; DAS = days after seeding; and soilT = average weekly soil temperature. Based on the predic tive capacity (R), this model is similar to the one reported by Horgan and Yelverton (2001), but accounts for overseed coverage

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46 based on soil temperature and days after seed ing. Further research should be conducted to ascertain a model with hi gher predictive probabilities. Based upon visual estimation, the CGP model can be a valuable aid to turfgrass managers for predicting when to seed, when establishment will occur, and if there is a need to chemically transition (Gelernter and Stowell, 2005). However, it may prove difficult to determine an exact date to spray a transition aid based on the growth potential of the warm-season and cool-season grasses. The FRD model that was created using the 2002-2006 coverage da ta fit each of the individual years better than the Horgan and Yelverton (2001) RD model. The FRD model provides a better account of Florida ryegrass disappearance. Th e FRD model is as follows: FRD = -96.66 + 6.61(airT) [eq. 4] Where FRD = ryegrass disappearance (0100%); airT = air temperature (C). These models can be used as an aid for turfgrass managers. However, because it is difficult to accurately model all of the aspects of overseed performance and transition over a wide area such as the southern United States, more research needs to be conducted on the most appropriate models and model inputs, so an even better understanding of overseeding culture can be obtained.

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47 CHAPTER 5 SUMMARY AND CONCLUSIONS University overseeding trial evaluations can result in valuable, unbiased overseed cultivar performance evaluation, thus, provi ding turfgrass managers with a wealth of knowledge when choosing a species or cultivar for overseeding. Turfgrass managers must be familiar with their particular needs when selecting a species or cultivar for overseeding. Knowing how a species or cultivar will perform under regional conditions can enable a turf manager to select the appropriate cultivar allowing for a successful overseeded winter period. An evaluation of 31 National Turfgrass Evaluation Program (NTEP) solicit ed grasses for overseeding fairways was discussed in Chapter Three. The following results were obtained: Perennial ryegrass and ryegrass blends ar e quicker to estab lish, provide better coverage, and higher quality turf stands than roughstalk bluegrass. Perennial ryegrasses have a darker green color than intermediate ryegrasses and roughstalk bluegrasses. Intermediate ryegrass transitions quicker than perennial ryegrass, perennial ryegrass blends, and roughstalk blue grass allowing for greater bermudagrass densities in early spring. Intermediate ryegrass maintains higher quality than roughstalk bluegrasses and similar qualit y to perennial ryegrass during the spring transition. Roughstalk bluegrass is slow to estab lish, has less coverage than perennial ryegrass, and provides a lower quality turf grass than perennia l ryegrass under golf course fairway conditions Top performing cultivars for establishm ent were the perennial ryegrasses: ‘OSC108’, ‘OSC110’, ‘PickSD’, ‘Flash II’, and ‘Charger’; and the perennial ryegrass blends: ‘ProSelect’, ‘Magnum Gold’, and ‘Champion GQ’. Top performing cultivars for density were the perennial ryegrasses: ‘Flash II’ and ‘Magnum Gold’; and the roughs talk bluegrass ‘RAM-100’.

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48 The cultivar ‘PickSD’ had the darkest green color. There are few models available to help predict overseed performance and transition. Existing models for overseed pe rformance and spring transition can provide valuable knowledge to turfgrass managers a bout some aspects of overseeding culture. These include establishment prediction, need for chemical aid for transition to bermudagrass, and regional ryegrass disappe arance. Evaluation of two existing models and known modeling techniques were used to better understand ove rseed performance and spring transition in Chapter Four. The following results were obtained: A model for overseed coverage based on th e independent variables average weekly soil temperature and days after seedi ng was determined through multivariate analysis. The model is OC = 134.46 + 0.16(DAS) – 04.74(soilT). The Cumulative Growth Potential model (G elernter and Stowell, 2005) can be a valuable tool for turfgrass managers for understanding the role of temperature in overseeding practices. The Ryegrass Disappearance model (H organ and Yelverton, 2001) is not appropriate for Gainesville, FL due to its rapidly increasing temp eratures during the transition period. A ryegrass disappear ance model equivalent to Horgan and Yelverton’s (2001) Ryegrass Disappearance model was successfully developed for Gainesville, FL. The model is FRD = -96.66 + 6.61(airT).

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49 APPENDIX A 2004-2006 ON-SITE TESTING GRASSES, SPECIES, AND COMPOSITION Table A-1 On-Site testing gra sses, species, and composition Entry Name Species or Composition 1 Charger Perennial ryegrass 2 Winterplay Roughstalk bluegrass 3 ProSelect 40% Jet, 40% Sonata 20% Integra P. ryegrass blend 4 Marvel Green Supreme 40% Palmer IV, 40% Prelude IV, 20% Sunkissed P. ryegrass blend 5 ALS2 Perennial ryegrass 6 PRS2 Perennial ryegrass 7 Overseeding Eagle Blend 33% Greenville, 33% ProSport, 34% Pacesetter P. ryegrass blend 8 Futura 2500 30% Blazer 4 P. ryegrass, 30% Sunshine P. ryegrass, 40% Pick Lh A-00 Intermediate ryegrass 9 Pick SD Perennial ryegrass 10 Playmate 50% Headstart 2, 50% Pick HS-01-09 P. ryegrass blend 11 BMX 020383 Perennial ryegrass 12 RAD-OS3 Intermediate ryegrass 13 RAM-100 Roughstalk bluegrass 14 IS-OS Perennial ryegrass 15 Top Hat Perennial ryegrass 16 IS-IR3 Intermediate ryegrass 17 Champion GQ 34% SR 4550, 33% SR 4420, 33% SR 4220 P. ryegrass blend 18 Magnum Gold 34% Peregrine, 33% Hawkeye, 33% Penguin P. ryegrass blend 19 Flash II Perennial ryegrass 20 MTV-124 Perennial ryegrass 21 OS Perennial ryegrass 22 STP Perennial ryegrass 23 PR 17 Perennial ryegrass 24 Starlite Roughstalk bluegrass 25 CRR Perennial ryegrass 26 League Master 40% Ringer, 20% Omega 2, 20% 04-BRE, 20% 04-BEN P. ryegrass blend 27 OSC110 Perennial ryegrass 28 OSC108 Perennial ryegrass 29 Covet Perennial ryegrass 30 OSC116 Perennial ryegrass 31 Colt Roughstalk bluegrass

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50 APPENDIX B DENSITY RATINGS FOR 2004-2005 AND 2005-2006 GROWING SEASONS Table B-1 Density ratings for 2004-2005 and 2005-2006 growing seasons. Density Rating* Cultivar 2004-2005 2005-2006 Magnum Gold 7.4 a 7.3 abc Flash II 7.3 ab 7.4 a Playmate 7.3 ab 7.3 abc Champion GQ 7.3 ab 6.9 dc MTV-124 7.2 abc 7.0 bcd Overseeding Eagle Blend 7.2 abc 7.1 abcd PickSD 7.2 abc 7.2 abc OSC110 7.1 abcd 7.3 abc BMX 020383 7.1 abcd 7.1 abcd League Master 7.0 abcd 7.2 abc ProSelect 7.0 abcd 7.3 ab Marvelgreen Supreme 7.0 abcd 7.1 abcd Charger 7.0 abcd 7.3 abc IS-OS 7.0 abcd 7.1 abcd RAM-100 6.9 abcd 7.4 a Futura 2500 6.9 abcd 7.3 abc ALS2 6.9 abcd 7.0 bcd Top Hat 6.9 abcd 7.2 abc Covet 6.9 abcd 7.3 abc OS-IR3 6.9 abcd 7.1 abcd Starlite 6.9 abcd 7.1 abcd OSC108 6.8 abcd 7.1 abcd PRS2 6.8 bcd 7.1 abcd CRR 6.8 bcd 7.2 abc Winterplay 6.8 bcd 7.2 abc OSC116 6.7 dc 7.1 abcd RAD-OS3 6.7 dc 6.8 d STP 6.7 dc 7.2 abc OS 6.7 dc 7.1 abcd PR 17 6.6 d 6.9 dc Colt 5.7 e 7.4 a *Means followed by the same letter are not si gnificantly different at the 0.05 level.

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51 APPENDIX C CULTIVAR VISUAL AND DGCI COLOR MEANS Table C-1 Visual and DGCI color ratings for both growing seasons. Visual Color* DGCI Color* Cultivar 2004-2005 2005-2006 2004-2005 2005-2006 PickSD 8.1 a 8.2 a 0.42 ab 0.51 a MTV-124 7.8 ab 7.8 b 0.43 a 0.49 abc Playmate 7.7 ab 7.7 b 0.41 bcde 0.49 abc Champion GQ 7.7 ab 7.3 cdef 0.41 bcd 0.49 abc Marvelgreen Supreme 7.6 bc 7.3 cde 0.42 abc 0.48 abcd Flash II 7.4 bcd 7.4 cd 0.40 efghij 0.47 bcdef Magnum Gold 7.4 bcde 7.1 efgh 0.41 bcdefg 0.47 bcde OSC116 7.4 bcde 7.3 cdefg 0.39 ghij 0.48 bcd BMX 020383 7.3 cdef 7.5 c 0.41 bcd 0.49 ab Futura 2500 7.3 cdef 7.3 cdef 0.41 bcdef 0.49 abc ProSelect 7.2 cdefg 7.2 defgh0.40 defghi 0.47 bcde Overseeding Eagle Blend 7.2 cdefg 7.2 defg 0.40 defghi 0.45 defg ALS2 7.1 defgh7.3 cdef 0.40 defghi 0.46 cdef OSC108 7.1 defgh7.1 fgh 0.40 defghi 0.46 bcdef PRS2 7.1 defgh7.2 defgh0.40 bcdefgh 0.47 bcde CRR 7.0 efgh 7.2 defg 0.40 defghi 0.48 bcd League Master 7.0 efgh 7.0 gh 0.40 defghi 0.46 bcdef Covet 7.0 efgh 7.1 fgh 0.39 hij 0.47 bcd STP 7.0 efgh 7.1 efgh 0.39 fghij 0.47 bcde OSC110 7.0 fgh 7.1 fgh 0.40 defghi 0.47 bcde OS 6.9 fghi 7.2 defg 0.40 defghi 0.46 bcdef IS-OS 6.8 ghij 7.0 hi 0.40 bcdefghi 0.44 efg Top Hat 6.7 hij 6.6 jk 0.40 fghij 0.43 gh Starlite 6.5 ij 5.3 m 0.39 defghij 0.43 gh OS-IR3 6.4 j 6.7 ij 0.40 bcdefghi 0.45 defg RAD-OS3 6.0 k 6.3 l 0.39 ij 0.45defg Charger 5.9 k 6.4 kl 0.40 cdefghi 0.44 fg PR 17 5.9 k 7.3 cde 0.39 jk 0.47 bcdef RAM-100 5.1 l 5.2 mn 0.35 l 0.39 i Winterplay 4.7 l 5.2 mn 0.35 l 0.40 hi Colt 4.1 m 5.0 n 0.37 kl 0.38 i *Means followed by the same letter are not significantly different at the 0.05 level.

PAGE 61

52 REFERENCES Baskerville, G.L. and P. Emin. 1969. Ra pid estimation of heat accumulation from maximum and minimum temperat ures. Ecology 50:514-517. Beard, J.B. 2002. Turf management for golf courses. Ann Ar bor Press, Chelsea, Michigan. Branham, B.E. and T.K. Danneberger. 1989. Growth suppression of ‘Kenblue’ Kentucky bluegrass using plant growth regulators a nd degree-day application timing. Agron. J. 81:749-752. Burt, E. O. and N.R. Gerhold. 1970. Poa annua control in bermudagrass turf with Kerb. Southern Weed Sci. Proc. 23:122-126 Carson, T. 2006. Seed update 2006. Golf Course Manage. 74(5):60-72. Danneberger, T.K. 1983. Epidemiology and control of anthracnose incited in Colletotrichum graminicola (CES.) WILS. on annual bluegrass. Ph.D. diss. Michigan State Univ., East Lansing. Danneberger, T.K., B.E. Branham, and J.M. Va rgas Jr. 1987. Mefluidide applications for annual bluegrass seed head suppression based on degree-day accumulation. Agron. J. 79:69-71. Danneberger, T.K. and J.M. Vargas. 1984. Annual bluegrass seed head emergence as predicted by degree-day accumulation. Agron. J. 76:756-758. Duble, R.L. 1996a. Turfgrasses: Their manage ment and use in the southern zone. Texas A&M Univ. Press, College Station, Texas. Duble, R.L. 1996b. Ryegrass: temporary sports turf for the south [Online]. PLANTanswers Web Site. Texas A&M Univ., Colle ge Station. p. 1-3. Available at http://plantanswers.tamu.edu/turf/publications/ryegrass.html (verified 30 May 2006). Florida Automated Weather Network (F AWN). 2006. [Online]. Available at http://fawn.ifas.ufl.edu (verified 6 June 2006). Gelernter, W. and Stowell, L. 2005. Im proved overseeding programs. Golf Course Manage. 72(3):108-118.

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53 Gbur, E.E., G.L. Thomas, and F.R. Miller. 1979. Use of segmented regression in the determination of the base temperature in heat accumulation models. Agron. J. 71:949-953. Han, D.Y. 2004. Overseeding home lawns. Ext. Circ. T-03-04. Ala. Coop. Ext., Auburn Univ., Auburn. Horgan, B.P. and F.H. Yelverton. 2001. Removal of perennial ryegrass from overseeded bermudagrass using cultural me thods. Crop Sci. 41:118-126. Howard, H.F. 2006. Proactive vs. passive transi tion part 1: Pay now or pay later. Golf Course Manage. 74(2):93-96. Johnson, B.J. 1986. Response to vertical mowing and ethofumesate for annual bluegrass control in bermudagrass turf. Agron. J. 78:495-498. Karcher, D.E. and M.D. Richardson. 2003. Quantifying turfgrass color using digital image analysis. Crop Sci. 43:943-951. Karcher, D.E., M.D. Richardson, and L.C. Purcell. 2001. Quantifying turfgrass cover using digital image analysis. Crop Sci. 41:1884-1888. Mazur, A.R. and D.F. Wagner. 1987. Influe nce of aeration, topdr essing, and vertical mowing on overseeded bermudagrass putting green turf. HortScience. 22:12761278. McCarty, L.B., J.L. Cisar, A.E. Dudeck, and M.L. Elliot. 1993. Overseeding for yearround performance. p. 117-131 In Best Management Practices for Florida Golf Courses. Univ. of Florida, Gainesville. SP 141. McCarty, L.B., A.R. Mazur, and L.C. Miller. 2001. Overseeding. p. 356-373. In L.B. McCarty (ed.) Best golf course management practices. Prentice-Hall, Inc., Upper Saddle River, NJ. McCarty, L.B. and G.L. Miller. 2002. Ma naging bermudagrass turf. Ann Arbor Press, Chelsea, MI. Morris, K.N. 2004. Grasses for overseedi ng bermudagrass fairways. Golf Course Manage. 72(7):89-94. Morris, K.N. and R.C. Shearman. 2000. Th e National Turfgrass Evaluation Program: Assessing new improved turfgra sses. Diversity. 16:19-22. Mullen, R.E. 1996. Crop science: Principle and practice. Burgess Publishing, Edina, MN. Ostmeyer, T. 2004. Golf’s extreme makeover. Golf Course Manage. 72(7): 50-52, 56, 58, 60.

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54 SAS Institute. 1999. SAS user’s guide: Statistics. 8th ed. SAS Institute, Inc. Cary, NC. Shearman, R.C. 1998. NTEP turfgrass ev aluation workbook. Beltsville, MD: National Turfgrass Evaluation Program. Throssell, C.S., Z.J. Reicher, and L.J. Left on. 1990. Spring timing of broadleaf herbicide applications using growing degree days. p. 183. In Agronomy Abstr. ASA, Madison, WI. Tolley, M.P. and W.H. Robinson. 1986. Seasonal abundance and degree-day prediction of sod webworm emergence in Virginia. J. Econ. Entomol. 79(2):400-404. Turgeon, A.J. 2002. Turfgrass management Pearson Education, Inc., Upper Saddle River, NJ. Umeda, K. and G. Towers. 2004. Comparison of sulfonylurea herbicides for spring transition. Turfgrass Land scape Urban IPM Res. Summ. p. 1-9. Unruh J.B., R.E. Gaussoin, and S.C. Wiest. 1996. Basal growth temperatures and growth rate constants of warm-season turfgr ass species. Crop Sci. 36:997-999. Young, W.C. III. 1996. Extension estimates fo r Oregon forage and turf grass seed crop acreage, 1995. News/Notes 10(1):8-11. Crop & Soil Science Dept., Oregon State Univ. Corvallis, OR. Young, W.C. III. 2005. Extension estimates for Oregan forage and turf grass seed crop acreage, 2005 [Online]. Available at http://cropandsoil.oregonstate.edu/seedex t/Agronomy/o5ftacr.pdf (verified 23 May 2006).

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55 BIOGRAPHICAL SKETCH Asa Joel High grew up in Bradenton, Flor ida. He graduated from Manatee High School in 2000, and enrolled at the University of Florida. After graduating from U.F. with a B.S. in agricultural operations management in 2004, he began working at Haile Plantation Golf and Country Club in Gainesvi lle. After his summer on the golf course he returned to U.F. to pursue a Master of Scien ce in turfgrass science. Upon graduating in July of 2006, Asa will be in terning at the Augusta Nati onal Golf Club in Augusta, Georgia, so that he may pursue a car eer as a golf course superintendent.


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Material Information

Title: In Season and Transition Performance of Ryegrasses and Roughstalk Bluegrass under Golf Course Fairway Conditions
Physical Description: Mixed Material
Copyright Date: 2008

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IN SEASON AND TRANSITION PERFORMANCE OF RYEGRASSES AND
ROUGHSTALK BLUEGRASS UNDER GOLF COURSE FAIRWAY CONDITIONS















By

ASA JOEL HIGH


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


2006
































This work is dedicated to my family: my mother for her never-ending encouragement and
support of my education, my father for teaching me to respect and enjoy life, and to my
brother for always being there when I really needed him.















ACKNOWLEDGMENTS

I would like to thank Dr. Grady L. Miller, chair of my committee, for his support

and guidance while I completed this work. I must also thank him for taking a chance on

me and allowing me the opportunity to be the resident at the Envirotron Turfgrass

Research Facility while pursuing my master's degree. I am also grateful for the help and

support of my other committee members Dr. Phil Harmon, Dr. Kevin Kenworthy, and Dr.

Carol Stiles.

Also, I would like to thank Jason Haugh and Jan Weinbrecht for their friendship,

support, and willingness to help in all aspects of this project. Special thanks go to Todd

Wilkinson, Golf Course Superintendent, and his assistant, John Drouse, for their

assistance and for use of their facility to conduct this research.

I would also like to thank the National Turfgrass Evaluation program in

conjunction with the United States Golf Association and the Golf Course Superintendents

Association of America for funding portions of this research.
















TABLE OF CONTENTS



A C K N O W L E D G M E N T S ................................................................................................. iii

LIST OF TABLES .............. ................. ........... ................... ........ vi

L IST O F F IG U R E S .... ...... ................................................ .. .. ..... .............. vii

A B S T R A C T .......................................... .................................................. v iii

CHAPTER

1 INTRODUCTION ............... ................. ........... ................. ... ..... 1

2 LITER A TU R E REV IEW ............................................................. ....................... 3

Overseeding Culture ........... ....... .... .. .................. .......... ...... .. ........ ..
A annual R yegrass.................................................... 5
Interm ediate Ryegrass ......................... ...... ........ .......... .... .. 6
Perennial R yegrass .................................................................... .6
R oughstalk B luegrass ...................... ........................ .. .......... .......... .. .. ....
Spring Transition ..................................................... .... .. ........ .. 8
H eat Stress and Turfgrass Physiology ............................................. ............... 10
Turf Growth and Transition M odeling ................................................. ................11
Heat Unit (Degree Day) Modeling ......................................... ................11
Cumulative Growth Potential ................................................... ....... ........ 12
Percent Ryegrass Disappearance...................................................................... 13
National Turfgrass Evaluation Program .......................................... ............... 13
Turfgrass Evaluation M ethods........................................................ ............... 14
Visual Evaluation of Turfgrasses ......................................................... 14
G general M methods .......................................... ................... .. ...... 14
Turfgrass Q quality ................................................ ..... ... .. ............ 15
G e n e tic C o lo r ................................................................................................. 1 5
T urfgrass D ensity ........................................ ................... .... .. ... 15
Percent Living G round Cover ........................................ ......... ............... 15
T urfgrass T exture ........................................ ................... .... .. ... 16
D digital Im age A analysis ...................................... ..................... .............. 16









3 AN EVALUATION OF TURFGRASSES FOR OVERSEEDING
BERM U D A GRA SS FA IRW A Y S ......................................................... .................. 17

In tro d u ctio n ...................................... ................................................ 17
M materials and M methods ....................................................................... .................. 18
R results and D discussion ................ ................ .... .......................... ............ 21
2004-2005 Turf Establishment, Quality, and Transition Performance ..............24
2005-2006 Turf Establishment, Quality, and Transition Performance ..............29
2004-2006 Overseed Density and Texture .....................................................31
V isual and D digital Color A nalysis.................................... ....................... 33
D disease Incidence .................................... .............. ................ 34
S h e a r S tre n g th ............................................................................................... 3 4
C o n c lu sio n s........................................................................................................... 3 5

4 AN EVALUATION OF THREE MODELS TO PREDICT TURFGRASS
O V E R SEE D TR A N SITIO N ........................................................... .....................37

In tro d u ctio n ................................................... .................. ................ 3 7
M materials and M methods ....................................................................... ..................38
Turf and W weather D ata Sets ........................................ .......................... 38
Florida Turfgrass Transition M odel ............................................................. 39
Cumulative Growth Potential and Ryegrass Disappearance Models..................39
R results and D discussion .................... .. ...... ...... .... .... ........ ............ ............ 40
Soil Temperature and Days After Seeding Variables..............................40
G row th P potential M odel ........................................................... .....................4 1
Ryegrass D disappearance ......................................................... .............. 43
C o n clu sio n s..................................................... ................ 4 5

5 SUMMARY AND CONCLUSIONS......................................................................47

APPENDIX

A 2004-2006 ON-SITE TESTING GRASSES, SPECIES, AND COMPOSITION...... 49

B DENSITY RATINGS FOR 2004-2005 AND 2005-2006 GROWING SEASONS...50

C CULTIVAR VISUAL AND DGCI COLOR MEANS .............................................51

R E F E R E N C E S ........................................ ........................................................... .. 5 2

B IO G R A PH IC A L SK E TCH ..................................................................... ..................55
















LIST OF TABLES


Table page

3-1 Germination and seed count data for each of the cultivars in the evaluation...........22

3-2 Mean square from combined analyses of variance for cover and quality ratings
of the cool-season overseed turfgrasses ............................................. ...........25

3-3 Percent cover of overseeded grasses four and six weeks after seeding for the
2 0 0 4 -2 0 0 5 trial ..................................................................... 2 6

3-4 Quality ratings of overseeded grasses for the 2004-2005 season.............................28

3-5 Percent cover of overseeded grasses four and six weeks after seeding for the
2 0 0 5 -2 0 0 6 trial ..................................................................... 3 0

3-6 Quality ratings of overseeded grasses for the 2005-2006 season.............................31

3-7 Mean square from combined analyses of variance for density and texture ratings
of the cool-season overseed turfgrasses ............................................. ...........32

3-8 Mean square from combined analyses of variance for color analysis using visual
ratings and digital analysis of DGCI ............................ .................................... 33

3-9 Mean square from analysis of variance for dollar spot centers during 2004-2005
grow ing season .................................................................................... 34

3-10 Mean square from analysis of variance for in situ shear strength (kg force) for
b o th y e a rs ......................................................................... 3 5

4-1 Comparison of r2 values for Ryegrass Disappearance (RD) Model (Horgan and
Yelverton, 2001) and the Florida Ryegrass Disappearance Model (FRD) ..............43

A-1 On-Site testing grasses, species, and composition ....................................... 49

B-l Density ratings for 2004-2005 and 2005-2006 growing seasons.............................50

C-l Visual and DGCI color ratings for both growing seasons ....................................51















LIST OF FIGURES


Figure page

3-1 Average weekly soil temperatures taken 10cm below soil surface for the 2004-
2005 evaluation ........................................................................23

3-2 Average weekly soil temperatures taken 10cm below surface for the 2005-2006
ev a lu a tio n ......................................................................... 2 4

4-1 Graphical comparison of Percent Growth Potential (Gelernter and Stowell,
2005) and actual percent cover data from two years of overseed evaluation trials .42

4-2 Graphical comparison of Ryegrass Disappearance (RD) Model (Horgan and
Yelverton, 2001) and Florida Ryegrass Disappearance (FRD) Model ....................44

4-3 Comparison of RD model (Horgan and Yelverton, 2001) and Florida Ryegrass
Disappearance M odel (FRD) ............................................................................45















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

IN SEASON AND TRANSITION PERFORMANCE OF RYEGRASSES AND
ROUGHSTALK BLUEGRASS UNDER GOLF COURSE FAIRWAY CONDITIONS

By

Asa Joel High

August 2006

Chair: Grady L. Miller
Major Department: Environmental Horticulture

Overseeding sports turf areas provides aesthetically pleasing, year-round green turf

in southern United States. Turfgrass managers are well aware of the influence that

turfgrass selection and climate have on overseeding and the spring transition.

Advancements in turfgrass breeding and selection have led to the release of new cultivars

for overseeding bermudagrass fairways each year. Turfgrass managers constantly seek

un-biased evaluations of these new turfgrasses for overseed applications. The objectives

of this study were to evaluate cultivars for overseeding bermudagrass fairways and

evaluate spring transition using known modeling techniques. Thirty-one cultivars and

blends consisting of perennial ryegrass (Lolium perenne L.), intermediate ryegrass

(Lolium hybridum L.), and roughstalk bluegrass (Poa trivialis L.) were overseeded as a

randomized complete block design on a bermudagrass (Cynodon dactylon x C.

transvalensis cv. 'TifSport') fairway at the University of Florida Golf Course in

Gainesville, FL. The trial was established in early fall of 2004 and terminated in June of









2005, and repeated the following year with cultivars planted in the same location.

Percent coverage, overall quality, genetic color, density, texture, and ability to withstand

environmental stresses under fairway conditions were evaluated. Multi-variate analysis

was used to develop a model based on the 2004-2006 overseed evaluation trial data to

determine the appropriate variables for predicting overseed coverage. Historical

overseed evaluation data from 2002-2006 were used to evaluate a cumulative growth

potential (CGP) model and a ryegrass disappearance (RD) model using graphical and

linear regression analysis, respectively. The evaluation of the grasses indicated that

perennial ryegrass and ryegrass blends were quicker to establish, provided better cover,

color, and turfgrass quality than intermediate ryegrasses and rough stalk bluegrass.

Intermediate ryegrass transitioned quickly while maintaining high turf quality.

Roughstalk bluegrass was slow to establish and provided poor coverage. Variation in

establishment and cover among species also was observed. The Florida Transition Model

was derived to describe overseed coverage from average soil temperature and days after

seeding. Results indicated that the CGP model could be a valuable tool to turfgrass

managers for further understanding the overseeding process. Linear regression of 2002-

2006 overseed coverage provided an accurate RD model for the rapidly increasing spring

and summer temperatures of FL.














CHAPTER 1
INTRODUCTION

In most of the southern United States, overseeding is a common practice used by

turfgrass managers to maintain an aesthetically pleasing green turfgrass year-round.

Overseeding does more for sports-turf managers than provide year-round beauty. An

overseeded turfgrass provides actively growing turf that can withstand traffic, improve

playability, and prevent weed invasion better than brown, dormant bermudagrass turf.

Actively growing turfgrass in winter months also can increase golf courses profits by

increasing the number of rounds played. For these reasons most turfgrass managers sow

millions of pounds of seed in the southern region of the United States each fall (Morris,

2004).

Turfgrass managers are aware that the success of overseeding sports turf areas,

especially during spring transition, is dependent on the weather and the proper species of

overseed. Many other factors including soil and water quality, previous management,

and expectations also play a role in the success of the overseeding practice. Turfgrass

managers place an emphasis on understanding the climate of their region and making

informed decisions when selecting a turfgrass for overseeding.

Overseed selection can be difficult for turfgrass managers. Each year many new

cultivars of overseed turfgrasses are released. According to Golf Course Management

magazine's 2006 seed update, over fifty turfgrasses are to be released in 2006 (Carson,

2006). Each new cultivar released varies in color, density, texture, vigor, and adaptation

to various climates. Thus, it is difficult for turfgrass managers to select the most effective









species and cultivar. This quest to improve overseed germplasm has created a need for

un-biased evaluation of newly released turfgrasses over a wide range of environmental

conditions.

Agronomists and other researchers have developed models that can help turfgrass

managers deal with climate influenced events such as the timing of insect infestations,

disease epidemics, and weed invasion (Gelemter and Stowell, 2005). However, there

have been few models that have helped turfgrass managers to understand the climate

influenced phenomena of spring transition.

Because of the need for performance evaluations of new overseed cultivars and the

need for additional research on modeling spring transition, two objectives were addresses

with this research. The first objective was to evaluate 31 overseed cultivars for fairway

use. The second objective was to evaluate models for spring transition.














CHAPTER 2
LITERATURE REVIEW

Overseeding Culture

Overseeding is the process of seeding onto an existing turfgrass stand. In fall and

winter, cool-season turfgrasses are used to provide regenerative growth and green color

during the dormant period of warm-season grasses. When temperatures drop below 15.50

C (600 F), bermudagrass shoots quit growing; when temperatures drop below 9.90 C (500

F), bermudagrass loses its green color and enters winter dormancy (McCarty et al., 2001).

In much of the southern United States overseeding golf courses provides year round color

on fairways, roughs, tees and putting greens.

Common bermudagrass [Cynodon dactylon (L.) Pers.] has been used extensively as

a soil stabilizer, sports turf, and forage for many years in the southeastern United States

(Duble, 1996a). Common bermudagrass is a warm-season perennial species widely

adapted to both tropical and subtropical climates. It spreads by stolons and rhizomes and

grows best in climates with high temperatures, mild winters, and moderate to high

rainfall. The bermudagrass adaptation range extends northward into the transitional zone

of the United States where temperatures rarely reach -12.2 C (100 F) (Duble, 1996a).

Hybrid bermudagrasses (Cynodon dactylon X C. transvaalenis Burtt-Davy) are

used widely in warm climates for both fairways and putting green surfaces. When

compared with alternative warm-season turfgrasses, hybrid bermudagrass possesses the

best overall turfgrass characteristics for fairway use and culture, providing an extremely

dense, uniform, playing surface (Beard, 2002). Hybrid bermudagrass can withstand









frequent low mowings and recuperates quickly from injury. The most common problems

faced by those managing hybrid bermudagrass are thatch accumulation, poor shade

tolerance, and a susceptibility to certain pests (Beard, 2002).

Overseeding bermudagrass golf greens and fairways has many advantages.

Overseeding provides a more aesthetically pleasing golf course, and the growing turf is

more tolerant to golf cart traffic, divots, and weed invasions (Morris, 2004). Many resort

courses in the south receive their heaviest play during the fall, winter, and spring;

therefore, overseeding can lead to an increase in revenue (McCarty et al., 2001).

Although there are many advantages, overseeding has some disadvantages. Weed

pressure can increase because annual bluegrass (Poa annua L.) is hard to control when

courses are overseeded consecutively for more than a few years (McCarty et al., 2001).

Other problems relate to delayed seed germination or distribution during planting and

result in clumps of unsightly ryegrass that are difficult to control. The cool-season

grasses also can compete aggressively with bermudagrass well into the summer months

thus delaying transition, green-up, and fill-in of the bermudagrass (McCarty et al., 2001).

Overseeding can lead to an increase in revenue, but estimated costs of overseeding

including seed, water, labor and pesticides make up to 20% of an annual budget on

southern golf courses (Ostmeyer, 2004). In St. Augustine, Florida, costs may be as high

as $45,000 to $50,000 annually to overseed an entire 18-hole golf course (Ostmeyer,

2004).

Turfgrass selection is perhaps the most important step when beginning the

overseeding process. Prior to 1960 the most common species used for overseeding was

annual ryegrass (Lolium multiflorum Lam.). Seeding rates were as high as 480.6 kg ha-1









(60 lb 1000 ft-2) (Turgeon, 2002). These rates are high by today's standard, but were

necessary because of poor quality seed and poor germination among early annual

ryegrass cultivars. In addition, annual ryegrass exhibited poor heat tolerance when

mowed low and transitioned quickly leaving a poor stand of bermudagrass (Turgeon,

2002). During the 1960's mixtures and blends of seed were used frequently for

overseeding (Turgeon, 2002). It was not uncommon to find mixtures and blends of fine

fescue (Festuca spp.), bentgrass (Agrostis spp.), roughstalk bluegrass (Poa trivialis L.),

Kentucky bluegrass (Poapratensis L.) and perennial ryegrass (Lolium perenne L.)

(Turgeon, 2002). Mixtures and blends provided enhanced germination, better frost

tolerance, greater disease resistance, reduced seeding rates, and smoother transitions than

a single cultivar (Turgeon, 2002). Blends and mixtures continue to be popular choices

for many turfgrass managers. Advances in breeding programs have provided turfgrass

managers with cultivars of turf-type perennial ryegrasses with qualities early annual

ryegrasses lacked (Turgeon, 2002). Turf-type overseeding grasses can be defined as

cultivars that have greater cold tolerance, wear tolerance, disease resistance, and

persistence than non-turf type cultivars (Duble, 1996b). These turf-type cultivars exhibit

finer texture, greater density, darker color, and better mowing qualities according to

Duble (1996b). The overseeding and transition processes can be facilitated greatly by

proper turfgrass selection.

Annual Ryegrass

Annual ryegrass has lost importance as an overseed the last two decades due to a

coarser, more open, growth habit compared to perennial ryegrasses (McCarty et al.,

2001). According to McCarty et al. (2001), annual ryegrass exhibits poor heat and cold

tolerance and early death in the spring that leads to poor transition. Unlike some of the









heat resistant perennial ryegrasses, annual ryegrass will die quickly with warm spring

temperatures leaving thin areas of dormant bermudagrass (Turgeon, 2002). However,

annual ryegrass does have some positive characteristics for overseeding. Annual ryegrass

is quicker to germinate than other ryegrasses and is acceptable for fairways and less

important areas where color is needed (McCarty et al., 2001). This is especially true

when budget constraints exist (McCarty at al., 2001). Annual ryegrass is cheaper than

perennial ryegrass, and because it is less heat tolerant than perennial ryegrass, it will

often transition at a faster rate (Han, 2004).

Intermediate Ryegrass

Intermediate ryegrass (Lolium hybridum Hausska.) is a hybrid of annual and

perennial ryegrasses. Similar to annual ryegrasses, intermediate ryegrasses are quick to

germinate but lack heat tolerance (McCarty et al., 2001). They have a medium texture,

are lighter green in color, and have reduced shoot growth when compared to other

ryegrass species (McCarty et al., 2001). Unlike many of the perennial ryegrasses,

intermediate ryegrasses will usually disappear quickly, with increasing temperatures,

once bermudagrass begins to grow in the spring (McCarty et al., 2001). Morris (2004)

found that intermediate ryegrasses had slightly lower quality ratings than perennial

ryegrasses, but they did transition faster in the 1999-2001 National Turfgrass Evaluation

Program's on-site fairway trials.

Perennial Ryegrass

Traditionally, perennial ryegrass is the preferred grass for overseeding fairways and

roughs. Current cultivars germinate quickly, usually 5 to 7 days, and have excellent dark

green color, superior texture, and better disease and traffic resistance compared to annual

ryegrass (McCarty et al., 2001). Many cultivars of perennial ryegrasses are available for









overseeding. Oregon is the world's major producer of cool-season forage and turfgrass

seed. Oregon produces almost two-thirds of the total U.S. cool-season grass seed (Young,

1996). Nearly 78,086 ha (192,950 acre) of perennial ryegrass was harvested for seed in

Oregon in 2005 (Young, 2005). Average seed yield is 1,555 kg ha-1 (1,387 lbs acre-')

(Young, 2005).

Most seed produced in the USA is of turf-type cultivars (Young, 1996). A blend of

perennial ryegrass cultivars is recommended to provide greater performance over a wide

range of conditions (McCarty et al., 2001). Many new turf-type cultivars of perennial

ryegrass have improved heat tolerances and are more competitive during spring transition

than previously used cultivars (McCarty et al., 2001). Many persist well into May, June,

and July (McCarty et al., 2001). In Florida, the recommended seeding rate for perennial

ryegrass in fairways is 244 to 732 kg ha-1 (5 to 15 lb 1000 ft-2) (McCarty et al., 1993).

Roughstalk Bluegrass

Roughstalk bluegrass is known for having a finer texture and higher density due to

a seed count of approximately 8 to 1 by weight when compared to perennial ryegrass

(McCarty et al., 2001). Primarily used to overseed greens because of its seed size, in the

last five years the National Turfgrass Evaluation Program (NTEP) also has been testing

cultivars in fairway situations. Rough stalk bluegrass is generally lighter in color, and

slower to establish and develop into a dense stand of turf than ryegrass (Morris, 2004).

This slower establishment may limit its use as a stand alone species on fairways (Morris,

2004). Rough stalk bluegrass tolerates poorly drained soils and has good shade tolerance

making it a good choice for tree-lined fairways lacking drainage from heavy native soils

(McCarty et al., 2001). It is generally quicker to transition in the spring because it has

lower heat tolerance than perennial ryegrass (McCarty et al., 2001). However, Morris









(2004) found that in Florida and California trials, roughstalk bluegrass was actually

slower to transition than perennial ryegrasses. The quickness of roughstalk bluegrass to

transition can leave thin dormant bermudagrass. However, if the roughstalk bluegrass

persists, as described by Morris (2004), it may out-compete the underlying bermudagrass.

Spring Transition

Turfgrass managers who overseed are well aware of the influence weather can have

on the success or failure of overseeding and transition programs (Gelernter and Stowell,

2005). Weather is always the driving force when it comes to the success of overseeding

and the spring transition. If cool-season grasses transition too quickly the warm-season

grasses may be weak and unsightly. However, if the cool-season grasses persist they

compete with the warm-season grasses for vital light, water, and nutrition that are needed

for a successful spring transition (Gelernter and Stowell, 2005). This problem can be

compounded by long term poly-stands of cool-season and warm-season grasses

(Gelernter and Stowell, 2005). Superintendents are constantly looking for better ways to

transition from cool-season to warm-season grasses.

Over the past years several cultural methods have been employed to enhance the

transition process. It is believed among many superintendents that vertical mowing,

aeration, and topdressing lead to a successful transition. However, Mazur and Wagner

(1987) reported high-intensity vertical mowing and topdressing for overseeded

bermudagrass are not effective in promoting bermudagrass emergence in the spring. In

fact, vertical mowing was actually found to delay the emergence of bermudagrass (Mazur

and Wagner, 1987; Johnson, 1986). Horgan and Yelverton (2001) found that cultural

practices did affect perennial ryegrass coverage, but did not hasten its ultimate

disappearance. Also, it was found that plots receiving core cultivation had lower









bermudagrass shoot density at the end of the transition period (Horgan and Yelverton,

2001). This was due to the physical removal of bermudagrass shoots and the stress of

coring each treatment during the hot summer months (Horgan and Yelverton, 2001).

Selective herbicides have successfully removed cool-season grasses. Chemical

transition allows the superintendent to remove cool-season grasses quickly without as

much concern for weather related issues, and the bermudagrass does not have to compete

for sunlight, water, and nutrients (Gelemter and Stowell, 2005). This allows the

bermudagrass a chance to become better established early in the normal growing season.

Burt and Gerhold (1970) observed that pronamide [3,5-dichloro-N-(1,1-dimethyl-2-

propynyl)-benzamide] completely eliminated or injured most cool-season grasses without

affecting the warm-season grasses. Sulfonylurea herbicides have made transition more

predictable, more manageable, and more beneficial for the growth of bermudagrasses

(Gelernter and Stowell, 2005). Umeda and Towers (2004) tested seven different

sulfonylurea herbicides for removing cool-season grasses from overseeded bermudagrass.

They found applications made at the higher labeled rates effectively removed cool-season

grasses from bermudagrass in April and May. The products tested included

flazasulfuron1, foramsulfuron2, rimsulfuron [N-((4,6-dimethoxypyrimidin-2-yl)

aminocoarbonyl)-3-(ethylsulfonyl)-2 pyridinesulfonamide], trifloxysulfuron [2-

pyridinesulfonamide,[ N-[[(4,6-dimethoxy-2-pyrimidinyl)amino]carbonyl]-3-(2,2,2-

trifluoroethoxy)-,monosodium salt, monohydrate salt, monohydrate]], and chlorsulfuron

[2-chloro-N-[(4-methoxy-6-methyl-1,3,5-triazin-2-yl) aminiocarbonyl]


1 Chemical name protected by U.S. Patent No 5,922,646.

2 Not currently labeled.









benzenesulfonamide] (Umeda and Towers, 2004).

Heat Stress and Turfgrass Physiology

In order to fully understand the transition of cool-season to warm-season grasses it

is important to understand the physiology of the grasses involved in transition and how

they react to light and temperature stress. It was not fully understood why cool-season

grasses and warm-season grasses differed in their ability to handle environmental stresses

until the Calvin-Benson or C3 and the Hatch and Slack or C4 carbon fixation cycles were

discovered in the 1950's and 1960's, respectively (McCarty and Miller, 2002). The

discovery of the two carbon fixation methods helped explain why warm-season and cool-

season grasses perform differently. The C4 or warm-season grasses are able to withstand

higher light intensities and warmer temperatures than C3 grasses (McCarty and Miller,

2002). Warm-season grasses grow best when exposed to full sunlight, because C4 plants

exhibit a non-saturated growth curve at light intensities found in nature (McCarty and

Miller, 2002). Cool-season grasses become stressed because growth curves plateau at

one-half full sunlight (McCarty and Miller, 2002). Once this occurs, photosynthesis

decreases and photorespiration increases. In the spring and summer growth of cool-

season plant slows because of light saturation and high temperatures. During these

periods when temperatures increase bermudagrass metabolism changes and dormancy is

broken. Cool-season grasses compete for the sunlight needed by bermudagrass to begin

growth in spring. When the cool-season overseeded grasses persist well into spring or

summer bermudagrass growth is hindered. A slow transition can lead to bermudagrass

death. This is why transition modeling to better understand the role that light and

temperature play in spring transition could greatly help turfgrass managers make

management decisions.









Turf Growth and Transition Modeling

Heat Unit (Degree Day) Modeling

Growing degree days, or heat accumulation units, can be used to measure or predict

the effect of temperature on biological processes (Baskerville and Emin, 1969). The heat

accumulation concept has been an excellent resource for many agricultural researchers

and is commonly used for modeling plant growth (Gbur et al., 1979). Research has

shown that understanding the relationship between plant growth and temperature can be

helpful for many aspects of agricultural production (Unruh et al., 1996). Degree day

models have helped turfgrass managers schedule pesticide applications for insects (Tolley

and Robinson, 1986), disease (Danneberger, 1983; Danneberger and Vargas, 1984), and

weed control (Throssell et al., 1990). Degree day modeling has been used to time plant

growth regulator applications (Danneberger et al., 1987; Branham and Danneberger,

1989).

The correlation between growth and temperature in degree day modeling can

predict when plants will germinate, mature, or even die (Mullen, 1996). These events in

plant development can be measured in "Heat Units" (Mullen, 1996). A heat unit can be

defined as the daily minimum temperature plus the daily maximum temperature minus a

previously determined base temperature for the plant species in question (Mullen, 1996).

Unruh et al. (1996) defines the base temperature as the temperature above which growth

takes place and below which the plant is dormant. Limits are often placed on the daily

maximum and minimum temperatures, and these are called "Growing Degree Days" or

degree days (Mullen, 1996). Degree day units accumulate over a growing season, and

thus provide an index of growth (Mullen, 1996). Degree day modeling has not been

applied to the transition of overseeded cool-season grasses.









Cumulative Growth Potential

Gelernter and Stowell (2005) considered the growth requirements for both warm-

season and cool-season turfgrasses and developed a model to help understand and explain

the variable nature of overseeding programs. The model is based on cumulative growth

potential which is a concept to help illustrate the interaction between weather and turf

performance (Gelernter and Stowell, 2005). Like degree day modeling the cumulative

growth potential model takes into account temperature data. The growth potential is

calculated by the following equation:



GP = 100 1
I (obsT optT) 2
Le2 J [eq. 1]

Where GP = growth potential; obsT = observed temperature (C); optT = optimal

temperature (C); sd = standard deviation of the distribution (sd warm-season turf = 12;

and sd cool-season turf = 10), and e = natural logarithm base (Gelernter and Stowell,

2005).

According to Gelernter and Stowell (2005), when the growth potential is at 100%

the turfgrass has reached its optimal growth because temperatures are ideal for the

particular turf species. Turf growth is still generally good until 50% because stress is

minimal (Gelernter and Stowell, 2005). Once the growth potential falls below 50% the

growth is limited, and as it nears 0% growth is halted (Gelernter and Stowell, 2005). The

percent growth potential can be graphed over time and by overlapping the graphs of

warm-season and cool-season turfgrasses a model can be constructed for a growing

season including the transition periods of overseeded bermudagrass.









Percent Ryegrass Disappearance

Horgan and Yelverton (2001) found that increased relative humidity and air

temperature in Raleigh, NC, accelerate natural ryegrass disappearance. Using two

cultivars of perennial ryegrasses, 'Derby Supreme' and 'Gator', it was found that percent

ryegrass disappearance could be modeled with linear regression over two growing

seasons (Horgan and Yelverton, 2001). In finding that both relative humidity and air

temperature were significant in the disappearance of ryegrass, it was noted also that there

was no difference between the heat tolerance of the two varieties (Horgan and Yelverton,

2001). The equations used to model the disappearance of the ryegrasses were as follows:

RD = -37.01+3.41(airT) [eq. 2]

and

RD = -274.7+4.31(RH) [eq. 3]

Where RD = ryegrass disappearance; airT = air temperature (C); and RH = relative

humidity (Horgan and Yelverton, 2001).

National Turfgrass Evaluation Program

The National Turfgrass Evaluation Program, commonly referred to as NTEP, is

designed to coordinate uniform evaluation trials of turfgrass varieties and promising

selections in the United States and Canada (Morris and Shearman, 2000). The world-

wide turfgrass community has relied heavily on the evaluation of information collected

and summarized by NTEP since the early 1980's. NTEP is a partnership between the

USDA's Agricultural Research Service, land-grant universities, and turfgrass seed

companies (Morris and Shearman, 2000). NTEP is sponsored by the National Turfgrass

Federation and the United States Department of Agriculture (Morris and Shearman,

2000). In most cases, NTEP evaluation trials are one of the first steps a new cultivar,









blend, or mixture will go through before being released on the market. New turfgrasses

should be well adapted for their intended applications. To accomplish this goal NTEP has

designed trials to collect unbiased cultivar data using very consistent methods over a

large range of environmental conditions.

Turfgrass Evaluation Methods

Visual Evaluation of Turfgrasses

The evaluation of turfgrasses is a difficult and complex issue (Shearman, 1998).

Unlike agricultural crops, it is unreasonable to evaluate turfgrasses using methods such as

a measure of yield or nutritive value (Shearman, 1998). Turfgrass quality is a subjective

measure based on visual estimates of aesthetic qualities such as genetic color, stand

density, leaf texture, uniformity, smoothness, and growth habit (Shearman, 1998).

Trained observers can indeed effectively discern slight differences in turfgrasses using a

visual rating system (Karcher et al., 2001; Karcher and Richardson, 2003; Shearman,

1998). Shearman (1998) and NTEP have created the following guidelines and

suggestions for the evaluation of turfgrasses.

General Methods

Visual ratings require consistency to ensure merit. One person should take the

data for a study over the entire duration of a study. Before taking data, a study should be

observed. The investigator should walk around the treatments and identify the range of

differences that occur. This process allows the investigator to establish a rating range

each time treatments are evaluated and keeps the ratings consistent. NTEP protocol

suggests turfgrasses are rated on a one to nine scale and should only be rated in whole

numbers. Ideally, evaluations should be made between mid-morning to early afternoon,

when shadows and reflections are minimal. (Shearman, 1998)









Turfgrass Quality

Quality ratings take into account the functional and aesthetic aspects of turfgrass.

They are based on a combination of color, density, uniformity, texture, and disease or

environmental stress. Quality is based on nine being the best and one being the poorest.

Quality values of nine are generally reserved for a perfect or ideal grass, while a rating of

six is generally considered an acceptable turf. Investigators must keep this in mind when

rating turfgrasses. (Shearman, 1998)

Genetic Color

Genetic color reflects the inherent color of a genotype. The visual rating is a one

to nine scale, one being light green and nine being dark green. Chlorosis and browning

from necrosis are not part of genetic color. Color charts, including Munsell Color Charts

for Plant Tissue (GreTagMacbeth LLC, New Windsor, NY), are useful in describing

turfgrass color and help in maintaining consistent visual color ratings. (Shearman, 1998)

Turfgrass Density

Turfgrass density is a visual estimate of living plants or tillers per unit area. Dead

patches in turf are excluded. A visual rating scale of one to nine is used and nine equals

maximum density. Turfgrass density can be measured quantitatively by counting shoots

in a specified area. However, this process is extremely time consuming and labor

intensive. Visual density ratings are highly correlated to counts and require less time and

labor. (Shearman, 1998)

Percent Living Ground Cover

Percent living ground cover is based on the surface area covered by the originally

planted species. Expressed from zero tol00%, it is generally used to measure damage

caused by insects, disease, environmental stresses and weed infestation. Ratings taken









over a season enable tracking of turfgrass response to various stresses during the growing

season. (Shearman, 1998)

Turfgrass Texture

Turfgrass texture is a measure or estimate of leaf width. The visual rating of

texture is based on a one to nine scale with one equaling coarse and nine equaling fine.

Visual estimate of texture is difficult and less than precise. However, actual physical

measurement is tedious, time consuming and labor intensive. Care must be taken to

measure leaves of similar age and stage of development. Visual ratings of texture can

successfully separate cultivars within species. Actual visual estimations of texture should

be completed when the turfgrass is actively growing and not under stress. (Shearman,

1998)

Digital Image Analysis

Color is a key component of the aesthetic properties of turfgrass and a good

indicator of water and nutrient stress (Beard, 2002). Digital analysis has been shown to

quantify color differences among standard Munsell Plant Tissue color chips, zoysiagrass

and creeping bentgrass receiving various N fertility treatments, and bermudagrass

varying in genetic color (Karcher and Richardson, 2003). A Dark Green Color Index

DGCI was created from the hue, saturation, and brightness values obtained from digital

image color analysis for comparison with values from subjective visual ratings. DGCI

variance is significantly lower than the variance when compared to visual ratings of

genetic color (Karcher and Richardson, 2003). The accuracy of digital image analysis

allows turfgrass researchers to record reflected turfgrass color on a standardized scale

rather that using arbitrary color values (Karcher and Richardson, 2003). This enables

valid comparisons of color data to be made across researchers, locations, and years.














CHAPTER 3
AN EVALUATION OF TURFGRASSES FOR OVERSEEDING BERMUDAGRASS
FAIRWAYS

Introduction

In the southern United States overseeding bermudagrass fairways is a common

practice. Overseeding provides an aesthetically-pleasing and functional playing surface

during winter months when temperatures drop below 9.9C (50F), and bermudagrass has

lost its green color due to winter dormancy (McCarty and Miller, 2002). The actively

growing turfgrass provided by overseed is more tolerant of traffic, divoting, and weed

invasions than dormant bermudagrass (Morris, 2004). Having overseeded turf can add to

a golf course's revenue by increasing the number of rounds played during cooler months

(Morris, 2004). However, overseeding can add significant costs to a golf course's budget

(McCarty et al., 2001). Costs include seed, water, labor, and pesticides and make up to

20% of an annual budget on southern golf courses (Ostmeyer, 2004). Another

disadvantage of overseeding is that the persistence of overseeded turfgrasses into late

spring and summer months can have detrimental effects on the underlying bermudagrass

as they compete for light, moisture, and nutrients (Gelernter and Stowell, 2005). Thus,

transition, bermudagrass green-up, and fill-in are delayed (McCarty et al., 2001). This

problem can be combated with the proper selection of overseed species and cultivars.

Turfgrass managers desire grasses that establish quickly, provide excellent

playability, transition appropriately, require fewer inputs, and are aesthetically pleasing.

Breeding programs have led to the release of many new overseed cultivars each year.









The quest to improve turfgrass performance under stressful environmental conditions

requires breeding and selecting new germplasm. In addition to breeding and selection of

new cultivars, each year seed companies formulate new mixtures and blends. Timely

testing of new cultivars, blends, and mixtures over a range of environmental conditions

by university scientists provides an un-biased evaluation to the breeder and end-user.

The objective of this study is to evaluate the suitability of the commercially available

species, cultivars, and blends included in the 2004-2006 National Turfgrass Evaluation

Program (NTEP) on-site fairway overseed trials for the north central region of Florida.

Materials and Methods

Thirty-one entries were established at the University of Florida Golf Course in

Gainesville, FL during fall of 2004 and 2005 (Appendix A). Entries included 17

perennial ryegrasses (Lolium perenne L.), eight perennial ryegrass blends, four

roughstalk bluegrasses (Poa trivialis L.), and two intermediate ryegrasses (Lolium

hybridum Hausska.). The fairway site was selected with the aid of the superintendent to

ensure that plots would receive uniform sunlight and wear. The University of Florida

Golf Course staff provided daily maintenance for the plots. Fertilization, irrigation,

mowing, and pesticide regimes were applied as determined by the superintendent to

provide typical golf course conditions.

Prior to planting, the number of seeds g-1 for each cultivar was determined by

weighing 100 fully developed seed to the nearest mg. The number of seeds g-1 was then

calculated. This procedure was completed in three replications for each cultivar.

Germination tests were completed in germination chambers (Stults Scientific Engineering

Corp., Springfield, IL). Ten seeds were germinated at 21 oC (70 oF) with 5 mL of water

and germination paper in the bottom of Petri dishes. Germination percentages were









calculated from this information and the procedure was completed in four replications for

each cultivar.

The fairway was scalped to 0.95 cm (0.375 in) from 1.14cm (0.45 in) three days

prior to overseeding in 2004 and no seedbed preparation occurred in 2005. The plots

were seeded on 18 Oct. 2004 and 25 Oct. 2005 with the 31 entries. Ten days after

seeding the plots were mowed at 1.14 cm (0.45 in). Plots were mowed at this height

three times per week for the remainder of the study. Plots were 1.5 m by 6.1 m (5 ft by

20 ft) and arranged in a randomized complete block design with three replications.

Entries were seeded onto a 'TifSport' bermudagrass (Cynodon dactylon X C.

transvaalenis Burtt-Davy) fairway with a drop spreader (The Andersons Company,

Maumee, OH) at rates of 392.3 kg ha-' (350 lbs acre-') for ryegrass species and blends,

and 224.2 kg ha-' (200 lbs acre-') for roughstalk bluegrass. Because overseeding grasses

provide a temporary playing surface during the fall, winter, and spring and are reseeded

each year cultivars were seeded in the same plots for two consecutive years (fall 2004

and fall 2005) to prevent un-germinated seed from emerging in the plot of a different

cultivar the following year. The 31 entries tested were NTEP solicited grasses from

sponsoring companies and commercially available cultivars and blends. Experimental

entries that were soon to be commercially available (before the end of the testing cycle)

also were permitted.

The first fertilization occurred on 1 Nov. 2004 with a 6-2-3 biosolid at a N rate of

17 kg ha-' (15.2 lbs acre-'). The second fertilization occurred on 15 Dec. 2004 with a 15-

5-10 granular fertilizer at aN rate of 42 kg ha-' (37.5 lbs acre-'). On 30 Jan. the plots

were fertilized at a N rate 0.65 kg ha-' (0.58 lbs acre-') with liquid 7-0-0 with Fe and Mg









as a supplement. The final fertilization occurred on 23 May with a sulfur coated urea

(28-0-0) at a N rate of 244 kg ha-1 (217.7 lbs acre-'). The plots received no pesticides

during the 2004-2005 trial.

During the second year the first fertilization occurred on 6 Dec. 2005 with a 21-0-0

liquid supplemented with Mn at a N rate of 68 kg ha-1 (60.7 lbs acre-'). On 3 Jan. 2006

the trial was fertilized with at 28-0-0 slow release material at a N rate of 3.25 kg ha-1 (2.9

lbs acre-'). The next fertilization occurred on 17 Jan with IBDU (31-0-0) at a N rate of

69.5 kg ha-1 (62 lbs acre-'). The final fertilization occurred on 14 Mar. with a N rate

using 14-0-14 plus oxadiazon [2-tert-butyl-4-(2,4-dichloro-5-isopropoxyphenyl)-A-1, 3,

4-oxidiazon-5-one] at 39.2 kg ha-1 (35 lbs acre-'). The oxidaizon was delivered at a rate

of2.69 kg a.i. ha-' (2.4 lbs a.i. acre-') The plots were also slit injected with fipronil [5-

amino- -(2,6-dichloro-4-(trifluoromethyl)phenyl)-4-((1,R, S,)-(trifluoromethyl)sulinyl) -

1-H-pyrazole-3-carbonitrile] on 29 Apr. at a rate of 0.028 kg a.i. ha-1 (0.025 lbs a.i.

acre-') for the preventative control of mole crickets (Scapteriscus spp.).

Data collected included visual estimates of percent establishment (weekly for first

six weeks after seeding), turfgrass quality (weekly during the fall transition, winter and

spring transition), genetic color (every other week during the winter and spring

transition), percent cover (twice weekly during the winter and spring transition), texture

(weekly during early spring period), and density (weekly during early spring period).

Disease incidence was evaluated counting necrotic spots (centers) in each plot. NTEP

Turfgrass Evaluation Guidelines (Shearman, 1998) were followed for all visual ratings.

Dark Green Color Index (DGCI) values were obtained (once during the winter

period) using digital images and the DGCI calculation (Karcher and Richardson, 2003).









In situ shear strength measurements (kg force) were determined using a Clegg Shear

tester (Dr. Baden Clegg Pty. Ltd., St. Jolimont, WA) with the insertion of a 49mm wide

paddle, 40mm into the soil profile. Weather data was mined from the Florida Automated

Weather Network (FAWN) weather station in Citra, FL (FAWN, 2006). The soil

temperatures were measured daily 10 cm below the soil surface at the Citra location and

then the data was computed to provide average weekly soil temperatures.

For analysis all measurements and visual ratings were statistically analyzed as a

main-effects model using SAS proc GLM (SAS Institute, 1999). For those traits

measured multiple times during the trial the repeated measures were analyzed as split

plots in time. Therefore, when the interaction of cultivar x year was significant years

were analyzed separately. Least significant differences (LSD) at P <0.05 was used to

compare cultivar means, whereas contrasts were used to compare species differences.

Results and Discussion

Seeds g- 1, as described in Table 3-1, showed that ryegrass species did not vary

among species, cultivars, and blends. Roughstalk bluegrass species did exhibit

significant variation (P <0.05). Germination rates varied between species and cultivars

(Table 3-1).

Temperatures were average compared to historical data for north central FL.

However, above average warm temperatures were recorded in early January during the

2004-2005 study (Figures 3-1 & 3-2). Frosts occurred in both years of the trial. April,

May, and June were hot dry months for much of Florida.









Table 3-1 Germination and seed count data for each of the cultivars in the evaluation.
Cultivar Species Germination* Count*
----%---- Seeds g-
MTV-124 Perennial ryegrass 100 a 554 d
Top Hat Perennial ryegrass 100 a 527 d
RAM-100 Roughstalk bluegrass 98 ab 4,929 a
OSC 116 Perennial ryegrass 98 ab 586 d
RAD-OS3 Intermediate ryegrass 98 ab 442 d
Flash II Perennial ryegrass 97 ab 547 d
Overseeding Eagle Blend Ryegrass blend 97 ab 547 d
PRS2 Perennial ryegrass 97 ab 559 d
OSC108 Perennial ryegrass 95 abc 543 d
Champion GQ Ryegrass blend 95 abc 613 d
Covet Perennial ryegrass 95 abc 583 d
Futura 2500 Ryegrass blend 95 abc 557 d
League Master Ryegrass blend 95 abc 518 d
Magnum Gold Ryegrass blend 95 abc 651 d
ProSelect Ryegrass blend 95 abc 591 d
Winterplay Roughstalk bluegrass 95 abc 4,552 c
Marvelgreen Supreme Ryegrass blend 94 abcd 640 d
STP Perennial ryegrass 94 abcd 630 d
Playmate Ryegrass blend 94 abcd 576 d
Colt Roughstalk bluegrass 94 abcd 4,791 ab
PR 17 Perennial ryegrass 94 abcd 535 d
CRR Perennial ryegrass 94 abcd 625 d
IS-IR3 Intermediate ryegrass 93 bcd 452 d
IS-OS Perennial ryegrass 93 bcd 482 d
OSC110 Perennial ryegrass 93 bcd 510 d
Starlite Roughstalk bluegrass 93 bcd 4,587 bc
Pick SD Perennial ryegrass 91 bcd 561 d
Charger Perennial ryegrass 91 bcd 473 d
OS Perennial ryegrass 89 cde 511 d
BMX 020383 Perennial ryegrass 88 de 536 d
ALS2 Perennial ryegrass 83 e 533 d
*Means followed by the same letter are not significantly different at the 0.05 level.













40


35


S 30 -
SMaximum Soil Temperature

U 25


20


15 Minimum Soil Temperature


10



Oct Nov Dec Jan Feb Mar Apr May Jun


Month


Figure 3-1. Average weekly soil temperatures taken 10cm below soil surface for the
2004-2005 evaluation.












40


35


30
Maximum Soil Temperature

S25


v) 20


15


10 Minimum Soil Temperature
10



Oct Nov Dec Jan Feb Mar Apr May Jun

Month
Figure 3-2. Average weekly soil temperatures taken 10cm below surface for the 2005-
2006 evaluation.

2004-2005 Turf Establishment, Quality, and Transition Performance

A cultivar by year interaction was observed for both cover and quality ratings when

the data was analyzed (Table 3-2). Therefore, the data was analyzed and discussed

separately for cover and quality among individual growing seasons. Establishment at

four weeks after (18 Nov. 2004) seeding ranged from 23 to 48% in the field study (Table

3-3). With the exception of 'PR 17' the ryegrasses were more established than

roughstalk bluegrass entries. Although it should be noted that differences were not

always significant between ryegrasses and roughstalk bluegrass entries.









Table 3-2 Mean square from combined analyses of variance for cover and quality ratings
of the cool-season overseed turfgrasses from the 2004-2005 and 2005-2006
growing seasons.
Mean Square
Source of Variation df Cover Quality
Cultivar, C 30 4801.5** 63.2**
Year, Y 1 613.3** 1.2
CxY 30 357.4** 3.6**
Rep, R 2 188.9** 3.7**
Date(Y) 81 57820.9** 19.1**
Error 7718 36.7 0.4
CV, % 11.2 9.2
Mean 54.3 6.8
Species, S 3 40836.6** 300.5**
Blend vs Perennial rye, PR 1 2033.6** 9.4**
Intermediate rye vs PR 1 1902.2* 6.5**
PR vs Roughstalk bluegrass 1 105478.3** 794.5**
*, ** Indicates significance at 0.05 and 0.01 level, respectively.









Table 3-3 Percent cover of overseeded grasses four and six weeks after seeding for the
2004-2005 trial.


Cultivar


Species


Magnum Gold
OSC110
OSC108
Flash II
Charger
Champion GQ
STP
ProSelect
MTV-124
Marvelgreen Supreme
CRR
Playmate
Pick SD
Overseeding Eagle Blend
OS
Futura 2500
Covet
Top Hat
PRS2
OSC 116
IS-OS
IS-IR3
ALS2
RAD-OS3
BMX 020383
League Master
Colt
Starlite
RAM-100
PR 17
Winterplav


Ryegrass blend
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Intermediate ryegrass
Perennial ryegrass
Intermediate ryegrass
Perennial ryegrass
Ryegrass blend
Roughstalk bluegrass
Roughstalk bluegrass
Roughstalk bluegrass
Perennial ryegrass
Roughstalk bluegrass


* Means followed by the same letter are not statistically different at the 0.05 level.


Six weeks after establishment the ryegrasses and blends exhibited good coverage,

(53 to 70%) the exception again being 'PR 17' (43%, Table 3-3). Similar to the 4-week

establishment ratings the ryegrass entries and blends had higher establishment ratings.

Again, not all differences were significant (P < 0.05, Table 3-3). The quality ratings at


Overseed Cover
18 Nov 04 2 Dec 04
----------%----------
48 a 70 a
47 ab 65 ab
47 ab 66 ab
47 ab 63 abc
47 ab 57 abcde
47 ab 60 abcd
45 ab 62abc
43 ab 60 abcd
43 ab 63 abc
43 ab 60 abcd
43 ab 63 abc
42 abc 65 ab
42 abc 55 bcde
42 abc 63 abc
42 abc 63 abc
42 abc 53 cde
42 abc 63 abc
40 abcd 62 abc
40 abcd 53 cde
40 abcd 57 abcde
40 abcd 58 abcd
40 abcd 57 abcde
40 abcd 53 cde
38 abcde 57 abcde
38 abcde 53 cde
37 abcde 57 abcde
32 cdef 53 cde
30 def 43 ef
28 ef 47 def
28 ef 43 ef
23 f 38f









this time showed similar results as coverage with the roughstalk bluegrasses and 'PR 17'

having the lowest quality ratings (Table 3-4). This trend of roughstalk bluegrasses and

'PR 17' having lower cover and quality ratings continued until late February. In March

there was less than 10% difference between coverage ratings for all entries. The majority

of the perennial ryegrasses and ryegrass blends still exhibited the best coverage (>75%),

but the roughstalk bluegrasses and intermediate ryegrasses had good coverage, between

60 and 75%. Thirty of the grasses exhibited minimally acceptable quality ratings greater

than six (Table 3-4). The roughstalk bluegrass 'Colt' had the poorest quality rating, 4.7

(Table 3-4).

During early May and throughout the transition period, the time when ryegrasses

begin to fade due to heat stress, 'LeagueMaster' and 'Playmate', perennial ryegrass

blends, exhibited the highest cool-season grass coverage at 35% (Data not shown). They

also exhibited mean quality ratings greater than or equal to 6.0 throughout the transition

period (Table 3-4). Other plots exhibiting high overseed coverage above 33%, good

bermudagrass densities, and quality ratings in mid May included the perennial ryegrasses

'PRS 2', 'OSC 108', 'OSC110', 'PickSD', and the ryegrass blends 'ProSelect' and

'Futura 2500'. These grasses may be the appropriate choice when turf managers desire

predominately cool-season grass to persist into spring and then transition abruptly.

Roughstalk bluegrasses, the intermediate ryegrass 'RAD-OS3', and 'PR 17' exhibited

less than 28%, coverage and high bermudagrass coverage through the transition period.

However, 'RAD-OS3' exhibited a greater average quality rating than others during this

period (Table 3-4). As temperatures increased in June most of the grasses had

transitioned to the point that there were no statistical differences in coverage (Data not









shown) and very little difference in quality. By the end of June all entries had completely

transitioned leaving all plots with 100% bermudagrass coverage and quality ratings

greater than or equal to 7.0 (1 to 9 scale) with the exception of 'Colt' (6.7, Table 3-4).

Table 3-4 Quality ratings of overseeded grasses for the 2004-2005 season.
Quality Rating
Cultivar 6 Dec 04 24 Mar 05 5 May 05 16 May 05 6 Jun 05 23 Jun 05
Flash II 7.0 a 7.7 ab 7.0 a 7.2 a 7.0 a 7.3 ab
Magnum Gold 7.0 a 7.7 ab 6.7 ab 6.7 abcd 7.0 a 7.7 a
OSC116 7.0 a 7.3 abc 6.7 ab 6.5 abcd 7.0 a 7.3 ab
ProSelect 6.7 ab 6.7 bcd 6.3 abc 6.5 abcd 6.7 ab 7.0 ab
OSC108 6.7 ab 7.3 abc 6.7 ab 6.8 abc 6.7 ab 7.0 ab
Top Hat 6.7 ab 6.7 bcd 6.3 abc 6.3 bcd 6.7 ab 7.3 ab
OSC110 6.7 ab 7.7 ab 6.3 abc 6.8 abc 6.7 ab 7.0 ab
Champion GQ 6.3 abc 7.0 abcd 6.7 ab 6.8 abc 6.3 abc 7.3 ab
MTV-124 6.3 abc 8.0 a 7.0 a 7.0 ab 6.3 abc 7.3 ab
Overseeding EB 6.3 abc 7.0 abcd 6.7 ab 6.7 abcd 6.3 abc 6.3 b
CRR 6.3 abc 7.0 abcd 6.3 abc 6.7 abcd 6.3 abc 7.7 a
MG Supreme 6.3 abc 7.3 abc 6.3 abc 6.5 abcd 6.3 abc 7.0 ab
League Master 6.3 abc 7.3 abc 6.7 ab 6.8 abc 6.3 abc 6.7 ab
IS-OS 6.3 abc 6.7 bcd 6.0 bc 6.5 abcd 6.3 abc 7.0 ab
Covet 6.3 abc 7.0 abcd 6.7 ab 6.7 abcd 6.3 abc 7.0 ab
STP 6.3 abc 7.0 abcd 6.0 bc 6.5 abcd 6.3 abc 7.3 ab
Playmate 6.0 abcd 7.7 ab 6.7 ab 6.8 abc 6.0 abcd 7.3 ab
PRS2 6.0 abcd 6.3 dc 5.7 cd 6.5 abcd 6.0 abcd 6.3 b
Futura 2500 6.0 abcd 7.0 abcd 6.7 ab 6.8 abc 6.0 abcd 6.7 ab
Pick SD 6.0 abcd 7.3 abc 6.7 ab 7.0 ab 6.0 abcd 6.7 ab
BMX 020383 5.7 bcde 6.7 bcd 7.0 a 7.0 ab 5.7 bcde 7.0 ab
RAD-OS3 5.7 bcde 6.7 bcd 6.0 bc 6.7 abcd 5.7 bcde 7.0 ab
ALS2 5.3 cde 6.3 bcd 6.0 bc 6.5 abcd 5.3 cde 7.0 ab
OS-IR3 5.3 cde 7.0 abcd 6.3 abc 7.0 ab 5.3 cde 7.7 a
OS 5.0 def 6.7 bcd 6.3 abc 6.8 abc 5.0 def 7.3 ab
Charger 4.7 efg 6.3 dc 6.7 ab 6.8 abc 4.7 efg 6.7 ab
Starlite 4.0 fgh 6.0 d 6.3 abc 6.2 cd 4.0 fgh 7.0 ab
RAM-100 4.0 fgh 7.0 abcd 6.0 bc 6.2 cd 4.0 fgh 7.7 a
PR 17 3.7 gh 6.3 cd 5.7 cd 6.7 abcd 3.7 gh 7.0 ab
Winterplay 3.7 gh 6.3 cd 6.0 bc 6.2 cd 3.7 gh 7.3 ab
Colt 3.0 h 4.7 e 5.0 d 6.0 d 3.0 h 6.7 ab
* Means followed by the same letter are not statistically different at the 0.05 level.









2005-2006 Turf Establishment, Quality, and Transition Performance

During the second year of the study the coverage again varied between the

ryegrasses and the roughstalk bluegrasses. Most of the ryegrasses exhibited good

establishment coverage during the first four weeks after planting (Table 3-5). The

roughstalk bluegrasses were again much slower to establish than the most of the

ryegrasses. The top performers included 'Charger', 'Pick SD', and 'ProSelect' (Table 3-

5). The perennial ryegrass 'PR 17' was slow to establish as in the previous year;

however, it was not different from other poorer performing ryegrasses at the P < 0.05

level. The roughstalk bluegrasses establishment coverage ranged from 7 to 18% below

the poorest ryegrass coverage four weeks after seeding (Table 3-5).

At six weeks after establishment the roughstalk bluegrasses were still different

from other entries (P < 0.05). The top performers at six weeks included 'Playmate' and

'BMX 020383'. Roughstalk bluegrasses were still 14 to 28% less than the other grasses

(Table 3-5). This trend continued well into March as in year one of the trial. In early

quality ratings the roughstalk bluegrasses and the perennial ryegrass 'PR 17' rated the

poorest in quality.

In mid April and early May the perennial ryegrasses 'Playmate', 'PickSD', and the

ryegrass blend 'Champion GQ' had the highest overall cover ratings as transition began.

They also exhibited mean quality ratings of 6.0 on the 1 to 9 scale and were not different

(P < 0.05 level) from the majority of the other ryegrasses (Table 3-6). The roughstalk

bluegrasses did however perform much better during the transition period with mean

quality ratings ranging from 6.3 to 7.0 (Table 3-6). The roughstalk bluegrasses ranged in

coverage from 30 to 35% with good bermudagrass density (Table 3-5). The intermediate

ryegrass 'RAD-OS3' exhibited the lowest cover in early May at 30%, but ranked the









highest in quality at the P < 0.05 level. By early June all of the grasses had completed

transition leaving 100% bermudagrass cover and average quality ratings of 7.0 on a 1 to 9

scale.

Table 3-5 Percent cover of overseeded grasses four and six weeks after seeding for the
2005-2006 trial.


Cultivar


Species


Charger
Pick SD
ProSelect
BMX 020383
Playmate
Champion GQ
CRR
MTV-124
Overseeding Eagle Blend
Futura 2500
League Master
Magnum Gold
RAD-OS3
STP
Top Hat
ALS2
Flash II
Marvelgreen Supreme
OSC 116
OSC108
OSC110
Covet
IS-OS
OS
PRS2
IS-IR3
PR 17
Winterplay
Colt
RAM-100
Starlite


Perennial ryegrass
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Ryegrass blend
Ryegrass blend
Perennial ryegrass
Perennial ryegrass
Ryegrass blend
Ryegrass blend
Ryegrass blend
Ryegrass blend
Intermediate ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Ryegrass blend
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Intermediate ryegrass
Perennial ryegrass
Roughstalk bluegrass
Roughstalk bluegrass
Roughstalk bluegrass
Roughstalk bluegrass


Overseed Cover
22 Nov 05 1 Dec 05
----------%----------
53 a 53 abc
52 a 57 ab
52 a 57 ab
50 ab 58 a
50 ab 58 a
48 abc 53 abc
48 abc 53 abc
48 abc 55 abc
48 abc 55 abc
47 abc 53 abc
47 abc 57 ab
47 abc 55 abc
47 abc 50 abc
47 abc 57 ab
47 abc 55 abc
45 abc 57 ab
45 abc 53 abc
45 abc 53 abc
45 abc 55 abc
45 abc 53 abc
45 abc 53 abc
43 abcd 53 abc
43 abcd 48 bc
43 abcd 55 abc
43 abcd 52 abc
40 bcd 52 abc
38 cd 47 c
33 d 33 d
18e 18e
17 e 22 e
15e 18e


* Means followed by the same letter are not statistically different at the 0.05 level.









Table 3-6 Quality ratings of overseeded grasses for the 2005-2006 season.
Quality Rating
Cultivar 12 Dec 05 13 Mar 06 2 May 06 16 May 06 23 May 06 7 Jun 06
Flash II 6.7 a 7.0 ab 7.0 a 7.2 a 7.0 a 7.0 a
Magnum Gold 6.0 a 7.0 ab 6.7 ab 6.7 abcd 7.0 a 7.0 a
OSC116 6.7 a 7.0 ab 6.7 ab 6.5 abcd 6.7 ab 7.0 a
ProSelect 6.3 ab 7.0 ab 7.0 a 6.5 abcd 7.0 a 7.0 a
OSC108 6.0 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a
Top Hat 6.0 a 7.0 ab 6.7 ab 6.3 bcd 6.8 ab 7.0 a
OSC110 5.7 a 7.0 ab 7.0 a 6.8 abc 6.7 ab 7.0 a
Champion GQ 6.3 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a
MTV-124 6.3 ab 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a
OEB 6.3 a 7.0 ab 7.0 a 6.7 abcd 6.8 ab 7.0 a
CRR 6.3 a 7.3 a 6.7 ab 6.7 abcd 6.8ab 7.0 a
MG Supreme 6.3 a 7.3 a 6.7 ab 6.5 abcd 6.7 ab 7.0 a
League Master 6.3 a 7.0 ab 7.0 a 6.8 abc 6.8 ab 7.0 a
IS-OS 5.7 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a
Covet 6.0 a 7.0 ab 6.7 ab 6.7 abcd 6.7 ab 7.0 a
STP 6.3 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a
Playmate 6.0 a 7.3 a 7.0 a 6.8 abc 7.0 a 7.0 a
PRS2 6.0 a 7.0 ab 7.0 a 6.5 abcd 6.7 ab 7.0 a
Futura 2500 6.0 a 7.0 ab 7.0 a 6.8 abc 6.8 ab 7.0 a
Pick SD 6.3 a 7.0 ab 7.0 a 7.0 ab 6.8 ab 7.0 a
BMX 020383 6.3 a 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a
RAD-OS3 6.0 a 7.0 ab 7.0 a 6.7 abcd 6.8 ab 7.0 a
ALS2 6.0 a 7.0 ab 7.0 a 6.5 abcd 6.8 ab 7.0 a
OS-IR3 6.3 a 7.0 ab 7.0 a 7.0 ab 7.0 a 7.0 a
OS 6.3 a 7.0 ab 6.7 ab 6.8 abc 6.8 ab 7.0 a
Charger 6.0 a 7.3 a 6.7 ab 6.8 abcd 6.8 ab 7.0 a
Starlite 3.7 b 6.7 be 6.7 ab 6.2 cd 6.3 be 7.0 a
RAM-100 4.0 b 6.7 be 7.0 a 6.2 cd 6.3 be 7.0 a
PR 17 6.0 a 7.0 ab 6.7 ab 6.7 abcd 6.5 ab 7.0 a
Winterplay 4.0 b 6.7 be 6.7 ab 6.2 cd 6.5 ab 7.0 a
Colt 3.7 b 6.3 c 6.3 b 6.0 d 5.8 c 7.0 a
* Means followed by the same letter are not statistically different at the 0.05 level.

2004-2006 Overseed Density and Texture

Density was analyzed and discussed separately by year because a cultivar by year

interaction was again observed. Perennial ryegrass and ryegrass blends exhibited the

highest values for density during both years, but were different from one another at the

95% probability level (Table 3-7). Contrast analyses by species indicated perennial










ryegrasses and roughstalk bluegrasses were not different in density at the P < 0.05 level

(Table 3-7). This was probably due to the high seed count per unit weight of the

roughstalk bluegrasses, and the coarseness of perennial ryegrass leaves. Perennial

ryegrasses and intermediate ryegrasses were different at the P < 0.05 level (Table 3-7).

This could possibly be explained by the coarser leaf blades that intermediate ryegrasses

possess. The second year of the trial had greater average density ratings than year one.

However, this variation could likely be due to the higher N rate applied during year two

of the study. Specific cultivar texture performance can be referenced in Appendix B.

Texture ratings were analyzed across years because there was no cultivar by year

interaction. There were differences in average texture between species at the 95%

probability level (Table 3-7). Perennial ryegrass and the ryegrasses blend were not

different at the P < 0.05 level. Intermediate ryegrasses were different from the perennial

ryegrasses, and exhibited lower texture ratings than all of the other species. Intermediate

ryegrasses had mean texture ratings below 6.8. The roughstalk bluegrasses in the trial

exhibited the highest texture ratings averaging above 7.4, and with 'RAM-100' having

the highest average texture rating.

Table 3-7 Mean square from combined analyses of variance for density and texture
ratings of the cool-season overseed turfgrasses for 2004-2005 and 2005-2006.
Mean Square
Source of Variation df Density Texture
Cultivar, C 30 0.64** 6.41
Year, Y 1 7.75** 61.83**
CxY 30 0.68** 4.80
Rep, R 2 8.80** 6.04
Date(Y) 5 1.98** 16.89
Error 650 0.52 2.77
CV, % 7.37 38.53
Mean 7.05 7.19
Species, S 3 1.75** 33.13*
Blend vs Perennial rye, PR 1 1.97** 0.21
Intermediate rye vs PR 1 1.19* 52.41**
PR vs Roughstalk bluegrass 1 0.86 48.85*
*, ** Indicates significance at 0.05 and 0.01 level, respectively.










Visual and Digital Color Analysis

The highest visual color ratings were the perennial ryegrasses and ryegrass blends

in both years. The data was again analyzed separately due to a cultivar by year

interaction for both methods of measuring color. The perennial ryegrass 'Pick SD' was

rated higher than all of the grasses for its deep dark green color, with a color rating of 8.1

in the 2004-2005 season and 8.2 2005-2006 season (Appendix C). The roughstalk

bluegrasses 'RAM-100', 'Colt', and 'Winterplay' exhibited the poorest color in the first

year. Perennial ryegrasses 'Charger', 'PR 17', and the intermediate ryegrass 'RAD-OS3'

also exhibited color ratings of less than 6.0. In 2005-2006 the rough bluegrasses

exhibited color ratings below 6.0. Digital color evaluations for the first and second year

provided different results between trial years at P < 0.05 (Table 3-8). This was probably

due to the grasses responding to the higher N rates of the 2005-2006 growing season.

'PickSD','MTV-124', 'BMX 020383', 'Playmate', and 'Futura 2500' performed the best

in both years of DGCI evaluation.

Table 3-8 Mean square from combined analyses of variance for color analysis using
visual ratings and digital analysis of DGCI.
Mean square
Source of Variation df Visual Color DGCI
Cultivar, C 30 28.88** 0.0001**
Year, Y 1 3.74** 0.0029**
CxY 30 1.96** 0.1896*
Rep 2 0.52 0.0005
Date(Y) 13", 4.99** -
Error 1394",1855 0.50 0.02
CV, % 7.21 4.11
Mean 6.87 0.43
Species, S 3 22.66** 45.58**
Blend vs Perennial rye, PR 1 10.55** 4.17*
Intermediate rye vs PR, 1 43.07** 2.03
PR vs Roughstalk bluegrass 1 557.56** 113.10**
Error 1372 0.64 0.02
CV, % 9.20 4.80
*, ** Indicates significance at 0.05 and 0.01 level, respectively.
T, t values for visual color and DGCI respectively









The digital image analysis verified that the roughstalk bluegrasses had the poorest color,

followed by the intermediate ryegrasses during both seasons. Specific color performance

for each cultivar can be referenced in Appendix C.

Disease Incidence

During the 2004-2005 trial there was an outbreak of apparent dollar spot symptoms

on some of the plots. Small circular, sunken, straw colored patches were observed. The

roughstalk bluegrasses 'RAM-100', 'WinterPlay', 'Colt', and the perennial ryegrass 'PR

17' had the highest incidence of spots averaging at least 24 dollar spot centers for each of

these entries. These cultivars had much greater dollar spot incidence than the rest of the

cultivars in the study at the 95% probability level. There were no disease symptoms

during the 2005-2006 trial as indicated by the years being different in Table 3-9. This

was probably due to the dry year and higher N fertility.

Table 3-9 Mean square from analysis of variance for dollar spot centers during 2004-
2005 growing season.
Mean Square
Source of Variation df Dollar Spot Centers
Cultivar, C 30 1724.41**
Date (Year), D (Y) 1 939.38
Rep 2 64.65
C x D (Y) 30 1044.10*
Error 185 523.58
CV, % 277.71
Mean 8.24
*, ** Indicates significance at 0.05 and 0.01 level, respectively.

Shear Strength

In situ shear strength data indicated that there was no difference among entries or

years (Table 3-10). This was most likely due to the late season April testing of the shear

strength in the 2004-2005 season, as the bermudagrass had already started rooting.









Table 3-10 Mean square from analysis of variance for in situ shear strength (kg force) for
both years.
Mean square
Source of Variation df Shear Value
Cultivar, C 30 230.80
Rep 2 509.63
Year, Y 1 294.39
CxY 30 201.58
Error 185 0.64
CV, % 18.28
Mean 76.74
* Indicates significance at P > 0.05

Conclusions

This study further indicated that perennial ryegrass and ryegrass blends provide

quick establishment, better coverage, and higher quality turf than roughstalk bluegrass.

Perennial ryegrass entries and blends provided the highest coverage and quality ratings

during the transition period further illustrating the persistent nature of perennial

ryegrasses to heat stress during transition. Intermediate ryegrasses provided less

coverage than perennial ryegrasses during the transition period, yet maintained high

overall plot quality. The intermediate ryegrasses transitioned faster allowing greater

bermudagrass densities during the spring transition period, indicating that it may be the

most appropriate choice for turfgrass managers who wish to maintain good quality and

provide less competition for the underlying bermudagrass. Roughstalk bluegrasses are

much slower to germinate and often took most of the season to establish. The roughstalk

bluegrasses had low percent coverage and the poorest quality ratings during the spring

reaffirming that the species may not be an appropriate choice for use as a stand-alone

species for overseeding fairways. Both methods for evaluating color indicated that

perennial ryegrass had the darkest green color followed by intermediate ryegrass and

roughstalk bluegrass, respectively. With the many different qualities that overseeding









Species possess, turfgrass managers should take great care to seek out un-biased

evaluations of seed cultivars to make the most appropriate selection for their particular

needs.

Turfgrass managers must also be aware of variability within species. The perennial

ryegrasses and ryegrass blends varied among cultivars within species with respect to

establishment, color, quality, density, and cover. There is less variability among cultivars

within the roughstalk bluegrass species. The variation within species is less than that

observed between species, but it can influence the success of transition.














CHAPTER 4
AN EVALUATION OF THREE MODELS TO PREDICT TURFGRASS OVERSEED
TRANSITION

Introduction

Turfgrass managers who overseed are well aware of the influence weather can have

on the success or failure of overseeding and transition programs (Gelernter and Stowell,

2005). Weather, especially temperature, is always the driving force when it comes to the

success of overseeding and spring transition. If cool-season grasses transition too quickly

the warm-season grasses may be weak and unsightly. However, if the cool-season

grasses persist, they compete with the warm-season grasses for light, water, and nutrition

that are needed for spring green-up (Gelernter and Stowell, 2005). When cool-season

grasses are left to transition naturally, the bermudagrass growing season can be limited to

less than nine weeks (Howard, 2006). Periods of less than 16 weeks for bermudagrass to

recuperate and repair from overseeding are not adequate (Howard, 2006). Thus, over

multiple shortened growing seasons bermudagrass will not endure (Howard, 2006).

Turfgrass managers are continuously seeking ways to better understand climate and its

effect on overseeding, spring transition, and bermudagrass health.

A mathematical model can be used to better understand the spring transition.

Mathematical models have been used to comprehend many aspects of turfgrass culture.

Models have been developed to help turfgrass managers develop pesticide spray

schedules for insects (Tolley and Robinson, 1986), diseases (Danneberger, 1983;

Danneberger and Vargas, 1984), weeds (Throssell et al., 1987), and timing of plant









growth regulator applications (Danneberger et al., 1987; Branham and Danneberger,

1989). However, few models have been developed to better explain spring transition.

The cumulative percent growth potential model mathematically explains the overseeding

process and spring transition (Gelernter and Stowell, 2005). The growth potential model

compares observed temperatures with optimum temperatures for growth of warm and

cool season grasses to predict the potential growth over a season (Gelernter and Stowell,

2005). Another model is a percent ryegrass disappearance model (Horgan and Yelverton,

2001). Horgan and Yelverton (2001) found that a linear regression can be used to better

understand the relationship between temperature and relative humidity in the

disappearance of ryegrass during spring transition. The object of this study was to

evaluate spring transition data using these known models and modeling techniques.

Materials and Methods

Turf and Weather Data Sets

Percent coverage and ryegrass disappearance data were obtained from four growing

seasons for overseed evaluation trials and National Turfgrass Evaluation Program

(NTEP) on-site fairway overseed evaluations completed in Gainesville, FL from 2002 to

2004 and from 2004 to 2006, respectively. The trials evaluated up to five species of cool

season grasses to be commercially marketed as overseed for bermudagrass sports turf.

The only data used from these trials were the percent coverage data. Cool-season grass

disappearance was calculated from this data. Weather data was mined from the Florida

Automated Weather Network (FAWN) weather station in Citra, FL. The data mined

included average daily soil temperatures and average daily air temperatures. The soil

temperatures were measured 10 cm below the soil surface and air temperatures were

measured 60 cm above the soil surface (FAWN, 2006). The daily averages were used to









generate average weekly and average monthly temperatures. These data were used to

evaluate the three models for predicting spring transition.

Florida Turfgrass Transition Model

A transition model was developed using NTEP on-site evaluation coverage data

from consecutive overseeding trials (2004-2005 and 2005-2006). The variables, average

weekly air temperature, average weekly soil temperature, and days after seeding (DAS),

were evaluated using multivariate analysis proc STEPWISE (SAS Institute, 1999) to

determine which variables were most appropriate for use in the model.

Cumulative Growth Potential and Ryegrass Disappearance Models

The two models used for comparison were previously published models that

describe overseed performance and spring transition. The cumulative growth potential

(CGP) model has been extensively used by the Pace Turfgrass Research Institute of San

Diego, CA (Gelernter and Stowell, 2005). The CGP growth potential model was used to

calculate the growth potential of warm and cool-season grasses using the following

equation and average monthly soil temperature data for each of the four years:



GP = 100 1
1 r0(obsToptT)12
LL s J [eq. 1]

Where GP = growth potential; obsT = observed temperature (C); optT = optimal

temperature (31.1 C for warm-season turf and 200C for cool-season turf); sd = standard

deviation of the distribution (sd warm-season turf = 12; and sd cool-season turf = 10),

and e = natural logarithm base (Gelernter and Stowell, 2005). In this study, average

monthly coverage data, for the two consecutive years of the NTEP trials, were compared









with the growth potential curves calculated for each year to determine the appropriateness

of the CGP model for overseed performance and transition using SigmaPlot (SPSS Inc.,

2002).

The ryegrass disappearance (RD) model was postulated to describe the transition

of ryegrass in Raleigh, NC (Horgan and Yelverton, 2001):

RD = -37.01+3.41(airT) [eq. 2]

Where RD = ryegrass disappearance and airT = air temperature (C) (Horgan and

Yelverton, 2001). The r2 value for the goodness of fit about the Horgan and Yelverton

(2001) data was 0.51. In this study, the actual ryegrass disappearance data that was

previously calculated from the four years of cover data were subjected to the RD model

equation and the relative fit of the RD model was determined using SigmaPlot (SPSS

Inc., Chicago, IL). Linear regression was used to determine a Florida Ryegrass

Disappearance (FRD) model based on weekly air temperature and the Florida coverage

data from 2002-2006. The FRD model was then subjected to each of the individual

growing seasons to determine the fit of the model using SigmaPlot (SPSS Inc., Chicago,

IL).

Results and Discussion

Soil Temperature and Days After Seeding Variables

The hypothesis was that overseed coverage and transition performance could best

be modeled using soil temperature and the amount of time after seeding. The multi-

variate analysis determined that soil temperature and days after seeding provided the

highest correlation for a two-variable model. The analysis of variance provided an R2

value of 0.54, the highest for the two variable models. The equation of the model for









dependent variable cover with soil temperature and days after seeding as the independent

variables was:

OC = 134.46 + 0.16(DAS) 04.74(soilT)2 [eq. 3]

Where OC = overseed cover; DAS = days after seeding; and soilT = average weekly soil

temperature. The R2 value of the analysis indicates that 54% of the variability of OC can

be accounted for by the variability in DAS and soilT. Therefore, the model does predict

OC, but not very well. This indicates that more research is needed to determine what

variables are most attributable to OC. Further research should possibly focus on

temperature stress, relative humidity, disease stress, shading, solar radiation, moisture,

and environmental stresses (e.g. traffic and divoting) to determine a model with a higher

probability for predicting OC and spring transition.

Growth Potential Model

Graphical comparison of the growth potential, calculated using the CGP model

(Gelernter and Stowell, 2005), and actual percent coverage showed that the actual cover

for warm and cool-season grasses were less that the percent growth potential (Figure 4-

1). The growth potential portrays a visually accurate slope of establishment and

dormancy of cool-season and warm-season grasses, respectively (Figure 4-1), indicating

that the time for establishment could be achieved as reported by Gelernter and Stowell

(2005). During periods of establishment and dormancy, the CGP model showed

fluctuation in the percent growth potential based on temperature that is not reflected in

the actual cover (Figure 4-1). While these fluctuations due to temperature cannot be

accounted for in the average monthly cover data, they may enable turfgrass managers to

determine when established stands of cool-season turf may be experiencing stress.

However, additional research would be needed to determine if these fluctuations could








42



indicate plant stress. The actual percent cover data lags behind the disappearance of


ryegrass and the re-emergence of warm-season grass from dormancy (Figure 4-1). This


may make it difficult for turfgrass managers to precisely identify when to spray a


herbicide to hasten the spring transition process. However, as reported by Gelernter and


Stowell (2005) the CGP model is a valuable aid in determining when there may be a need


to spray a transition hastening herbicide so warm-season grasses have adequate time, 16


weeks (Howard, 2006), to recuperate after the spring transition based on visual


comparison of CGP and actual cover data (Figure 4-1).


2004-2005 Overseed Evaluation

100I .. ... -.



60 -

S40 -.

20 -

0- / 2005-2006 Overseed Evaluation


Oct Nov Dec Jan Feb Mar
Month


Apr M


Warm-Season Growth Potential
................ Cool-Seaspn Growth Potential
-- Measured Warm-Season Cover
Measured Cool-Season Cover


ay Jun
100

80

60

S 40

S20


Oct Nov Dec Jan Feb Mar Apr May Jun
Month


Figure 4-1. Graphical comparison of Percent Growth Potential (Gelernter and Stowell,
2005) and actual percent cover data from two years of overseed evaluation
trials.









Ryegrass Disappearance

The regression line that Horgan and Yelverton (2001) proposed for ryegrass

disappearance did fit the data for each of the four years of overseed trials (Table 4-1).

Table 4-1 Comparison of r2 values for Ryegrass Disappearance (RD) Model (Horgan and
Yelverton, 2001) and the Florida Ryegrass Disappearance Model (FRD) for
2002-2006 overseeding coverage for Gainesville, FL.
r2 Value
Overseed Coverage RD Model FRD
2002-2003 Cover Data 0.53* 0.54
2003-2004 Cover Data 0.41* 0.78
2004-2005 Cover Data 0.31* 0.59
2005-2006 Cover Data 0.18* 0.66
2002-2006 Cover Data 0.34* 0.59
* Indicates significance of RD Model (Horgan and Yelverton, 2001) at P <0.05

However, when compared to the Florida Ryegrass Disappearance Model (FRD)

determined through linear regression of each of the four years of data, the Horgan and

Yelverton RD model had less slope and lower r2 values for the coverage data (Figure 4-

2). The same results were found when the Horgan and Yelverton (2001) model was fit to

all transition data from the growing seasons of 2002-2006 (Figure 4-3). This could

possibly be explained by higher relative humidity in Florida and most importantly more

rapid rate of temperature increase in the spring in Gainesville, FL than in Raleigh, NC.

The equation for the Florida Ryegrass Disappearance may more appropriately be:

FRD = -96.66 + 6.61(airT) [eq. 4]

Where FRD = ryegrass disappearance (0-100%); airT = air temperature (C). This model

allows for a more appropriate fit, r2 = 0.59, in Gainesville, FL with its rapidly increasing

temperatures during the spring and early summer.















-- RD= -37 01+ 341(arT)= 053 -- RD= -37 01 + 3 41(arT) = 0 41 *
...... FRD-9666+ 661(arT)I = 054 ****** FRD = -9666+ 661(arT) 2 078
* 2002-2003 Cultvar Means 2003-2004 Cultvar Means







0

0

I III


- RD = -37 01+ 3 41(arT) r = 031
...... FRD = -96 66 + 6 61(arT) r = 0 59
* 2004-2005 Cultvar Means


0.*

0.


- RD= -3701+341(airT)r= 018
...... FRD -9666+661(airT) = 066
* 2 205-206 Cultvar Means


10 12 14 16 18 20 22 24 26 28 12 14 16 18 20 22 24 26 28 30

Air Temperature (C)



Figure 4-2 Graphical comparison of Ryegrass Disappearance (RD) Model (Horgan and

Yelverton, 2001) and Florida Ryegrass Disappearance (FRD) Model for

average cover data from four consecutive years of overseed trials.













100 *
SRyegrass Disappearance *
--- FRD = -96.66 + 6.61(airT) r2 =.64
S-- RD = -37.01 + 3.41(airT) r2 =.39
S 80 '
e /
60 *
S *
S60




40

*-

20 -
~ 20


/
0 / **
I I I I I I I I I
10 12 14 16 18 20 22 24 26 28 30

Air Temperature (C)


Figure 4-3 Comparison of RD model (Horgan and Yelverton, 2001) and Florida Ryegrass
Disappearance Model (FRD) for average cover data from four growing
seasons (2002-2006).

Conclusions

Modeling of overseed and transition can be provided via many methods and can

serve as valuable aids to turfgrass managers. A model for overseed coverage was

determined through multi-variate analysis with average weekly soil temperature and days

after seeded. The model was:

OC = 134.46 + 0.16(DAS) 04.74(soilT)2 [eq. 3]

Where OC = percent overseed coverage; DAS = days after seeding; and soilT = average

weekly soil temperature. Based on the predictive capacity (R2), this model is similar to

the one reported by Horgan and Yelverton (2001), but accounts for overseed coverage









based on soil temperature and days after seeding. Further research should be conducted

to ascertain a model with higher predictive probabilities.

Based upon visual estimation, the CGP model can be a valuable aid to turfgrass

managers for predicting when to seed, when establishment will occur, and if there is a

need to chemically transition (Gelemter and Stowell, 2005). However, it may prove

difficult to determine an exact date to spray a transition aid based on the growth potential

of the warm-season and cool-season grasses.

The FRD model that was created using the 2002-2006 coverage data fit each of

the individual years better than the Horgan and Yelverton (2001) RD model. The FRD

model provides a better account of Florida ryegrass disappearance. The FRD model is as

follows:

FRD = -96.66 + 6.61(airT) [eq. 4]

Where FRD = ryegrass disappearance (0-100%); airT = air temperature (C).

These models can be used as an aid for turfgrass managers. However, because it

is difficult to accurately model all of the aspects of overseed performance and transition

over a wide area such as the southern United States, more research needs to be conducted

on the most appropriate models and model inputs, so an even better understanding of

overseeding culture can be obtained.














CHAPTER 5
SUMMARY AND CONCLUSIONS

University overseeding trial evaluations can result in valuable, unbiased overseed

cultivar performance evaluation, thus, providing turfgrass managers with a wealth of

knowledge when choosing a species or cultivar for overseeding.

Turfgrass managers must be familiar with their particular needs when selecting a

species or cultivar for overseeding. Knowing how a species or cultivar will perform

under regional conditions can enable a turf manager to select the appropriate cultivar

allowing for a successful overseeded winter period. An evaluation of 31 National

Turfgrass Evaluation Program (NTEP) solicited grasses for overseeding fairways was

discussed in Chapter Three. The following results were obtained:

* Perennial ryegrass and ryegrass blends are quicker to establish, provide better
coverage, and higher quality turf stands than roughstalk bluegrass. Perennial
ryegrasses have a darker green color than intermediate ryegrasses and roughstalk
bluegrasses.

* Intermediate ryegrass transitions quicker than perennial ryegrass, perennial
ryegrass blends, and roughstalk bluegrass allowing for greater bermudagrass
densities in early spring. Intermediate ryegrass maintains higher quality than
roughstalk bluegrasses and similar quality to perennial ryegrass during the spring
transition.

* Roughstalk bluegrass is slow to establish, has less coverage than perennial
ryegrass, and provides a lower quality turfgrass than perennial ryegrass under golf
course fairway conditions

* Top performing cultivars for establishment were the perennial ryegrasses:
'OSC108', 'OSC110', 'PickSD', 'Flash II', and 'Charger'; and the perennial
ryegrass blends: 'ProSelect', 'Magnum Gold', and 'Champion GQ'.

* Top performing cultivars for density were the perennial ryegrasses: 'Flash II' and
'Magnum Gold'; and the roughstalk bluegrass 'RAM-100'.









* The cultivar 'PickSD' had the darkest green color.

There are few models available to help predict overseed performance and

transition. Existing models for overseed performance and spring transition can provide

valuable knowledge to turfgrass managers about some aspects of overseeding culture.

These include establishment prediction, need for chemical aid for transition to

bermudagrass, and regional ryegrass disappearance. Evaluation of two existing models

and known modeling techniques were used to better understand overseed performance

and spring transition in Chapter Four. The following results were obtained:

* A model for overseed coverage based on the independent variables average weekly
soil temperature and days after seeding was determined through multivariate
analysis. The model is OC = 134.46 + 0.16(DAS) 04.74(soilT)2.

* The Cumulative Growth Potential model (Gelernter and Stowell, 2005) can be a
valuable tool for turfgrass managers for understanding the role of temperature in
overseeding practices.

* The Ryegrass Disappearance model (Horgan and Yelverton, 2001) is not
appropriate for Gainesville, FL due to its rapidly increasing temperatures during the
transition period. A ryegrass disappearance model equivalent to Horgan and
Yelverton's (2001) Ryegrass Disappearance model was successfully developed for
Gainesville, FL. The model is FRD = -96.66 + 6.61(airT).

















APPENDIX A
2004-2006 ON-SITE TESTING GRASSES, SPECIES, AND COMPOSITION

Table A-i On-Site testing grasses, species, and composition
Entry Name Species or Composition
1 Charger Perennial ryegrass
2 Winterplay Roughstalk bluegrass
3 ProSelect 40% Jet, 40% Sonata, 20% Integra P. ryegrass blend
4 Marvel Green 40% Palmer IV, 40% Prelude IV, 20% Sunkissed P. ryegrass blend
Supreme
5 ALS2 Perennial ryegrass
6 PRS2 Perennial ryegrass
7 Overseeding Eagle 33% Greenville, 33% ProSport, 34% Pacesetter P. ryegrass blend
Blend


8 Futura 2500

9 Pick SD
10 Playmate
11 BMX 020383
12 RAD-OS3
13 RAM-100
14 IS-OS
15 Top Hat
16 IS-IR3
17 Champion GQ
18 Magnum Gold
19 Flash II
20 MTV-124
21 OS
22 STP
23 PR 17
24 Starlite
25 CRR
26 League Master

27 OSC110
28 OSC108
29 Covet
30 OSC116
31 Colt


30% Blazer 4 P. ryegrass, 30% Sunshine P. ryegrass, 40% Pick Lh A-00
Intermediate ryegrass
Perennial ryegrass
50% Headstart 2, 50% Pick HS-01-09 P. ryegrass blend
Perennial ryegrass
Intermediate ryegrass
Roughstalk bluegrass
Perennial ryegrass
Perennial ryegrass
Intermediate ryegrass
34% SR 4550, 33% SR 4420, 33% SR 4220 P. ryegrass blend
34% Peregrine, 33% Hawkeye, 33% Penguin P. ryegrass blend
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Roughstalk bluegrass
Perennial ryegrass
40% Ringer, 20% Omega 2, 20% 04-BRE, 20% 04-BEN P. ryegrass
blend
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Perennial ryegrass
Roughstalk bluegrass
















APPENDIX B
DENSITY RATINGS FOR 2004-2005 AND 2005-2006 GROWING SEASONS

Table B-1 Density ratings for 2004-2005 and 2005-2006 growing seasons.
Density Rating*
Cultivar 2004-2005 2005-2006
Magnum Gold 7.4 a 7.3 abc
Flash II 7.3 ab 7.4 a
Playmate 7.3 ab 7.3 abc
Champion GQ 7.3 ab 6.9 dc
MTV-124 7.2 abc 7.0 bcd
Overseeding Eagle Blend 7.2 abc 7.1 abcd
PickSD 7.2 abc 7.2 abc
OSC110 7.1 abcd 7.3 abc
BMX 020383 7.1 abcd 7.1 abcd
League Master 7.0 abcd 7.2 abc
ProSelect 7.0 abcd 7.3 ab
Marvelgreen Supreme 7.0 abcd 7.1 abcd
Charger 7.0 abcd 7.3 abc
IS-OS 7.0 abcd 7.1 abcd
RAM-100 6.9 abcd 7.4 a
Futura 2500 6.9 abcd 7.3 abc
ALS2 6.9 abcd 7.0 bcd
Top Hat 6.9 abcd 7.2 abc
Covet 6.9 abcd 7.3 abc
OS-IR3 6.9 abcd 7.1 abcd
Starlite 6.9 abcd 7.1 abcd
OSC108 6.8 abcd 7.1 abcd
PRS2 6.8 bcd 7.1 abcd
CRR 6.8 bcd 7.2 abc
Winterplay 6.8 bcd 7.2 abc
OSC116 6.7 dc 7.1 abcd
RAD-OS3 6.7 dc 6.8 d
STP 6.7 dc 7.2 abc
OS 6.7 dc 7.1 abcd
PR 17 6.6 d 6.9 dc
Colt 5.7 e 7.4 a
*Means followed by the same letter are not significantly different at the 0.05 level.














APPENDIX C
CULTIVAR VISUAL AND DGCI COLOR MEANS

Table C-1 Visual and DGCI color ratings for both growing seasons.


Visual Color*
Cultivar 2004-2005 2005-2006
PickSD 8.1 a 8.2 a
MTV-124 7.8 ab 7.8 b
Playmate 7.7 ab 7.7 b
Champion GQ 7.7 ab 7.3 cdef
Marvelgreen Supreme 7.6 be 7.3 cde
Flash II 7.4 bcd 7.4 cd
Magnum Gold 7.4 bcde 7.1 efgh
OSC116 7.4 bcde 7.3 cdefg
BMX 020383 7.3 cdef 7.5 c
Futura 2500 7.3 cdef 7.3 cdef
ProSelect 7.2 cdefg 7.2 defgh
Overseeding Eagle Blend 7.2 cdefg 7.2 defg
ALS2 7.1 defgh 7.3 cdef
OSC108 7.1 defgh 7.1 fgh
PRS2 7.1 defgh 7.2 defgh
CRR 7.0 efgh 7.2 defg
League Master 7.0 efgh 7.0 gh
Covet 7.0 efgh 7.1 fgh
STP 7.0 efgh 7.1 efgh
OSC110 7.0 fgh 7.1 fgh
OS 6.9 fghi 7.2 defg
IS-OS 6.8 ghij 7.0 hi
Top Hat 6.7 hij 6.6 jk
Starlite 6.5 ij 5.3 m
OS-IR3 6.4j 6.7 ij
RAD-OS3 6.0 k 6.3 1
Charger 5.9 k 6.4 kl
PR 17 5.9 k 7.3 cde
RAM-100 5.11 5.2 mn
Winterplay 4.71 5.2 mn
Colt 4.1 m 5.0 n
*Means followed by the same letter are not significantly


DGCI Color*
2004-2005 2005-2006
0.42 ab 0.51 a
0.43 a 0.49 abc
0.41 bcde 0.49 abc
0.41 bcd 0.49 abc
0.42 abc 0.48 abcd
0.40 efghij 0.47 bcdef
0.41 bcdefg 0.47 bcde
0.39 ghij 0.48 bcd
0.41 bcd 0.49 ab
0.41 bcdef 0.49 abc
0.40 defghi 0.47 bcde
0.40 defghi 0.45 defg
0.40 defghi 0.46 cdef
0.40 defghi 0.46 bcdef
0.40 bcdefgh 0.47 bcde
0.40 defghi 0.48 bcd
0.40 defghi 0.46 bcdef
0.39 hij 0.47 bcd
0.39 fghij 0.47 bcde
0.40 defghi 0.47 bcde
0.40 defghi 0.46 bcdef
0.40 bcdefghi 0.44 efg
0.40 fghij 0.43 gh
0.39 defghij 0.43 gh
0.40 bcdefghi 0.45 defg
0.39 ij 0.45defg
0.40 cdefghi 0.44 fg
0.39jk 0.47 bcdef
0.35 1 0.39 i
0.351 0.40 hi
0.37 kl 0.38 i
different at the 0.05 level.
















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BIOGRAPHICAL SKETCH

Asa Joel High grew up in Bradenton, Florida. He graduated from Manatee High

School in 2000, and enrolled at the University of Florida. After graduating from U.F.

with a B.S. in agricultural operations management in 2004, he began working at Haile

Plantation Golf and Country Club in Gainesville. After his summer on the golf course he

returned to U.F. to pursue a Master of Science in turfgrass science. Upon graduating in

July of 2006, Asa will be interning at the Augusta National Golf Club in Augusta,

Georgia, so that he may pursue a career as a golf course superintendent.