[1] |
Gelernter WD, Stowell LJ, Johnson ME, Brown CD. 2017. Documenting trends in land-use characteristics and environmental stewardship programs on US golf courses. Crop, Forage & Turfgrass Management 3:1−12 doi: 10.2134/cftm2016.10.0066
|
[2] |
Hanna WW, Raymer PL, Schwartz BM. 2013. Warm-season grasses-biology and breeding, In Turfgrass: Biology, Use, and Management, eds. Stier JC, Horgan BP, Bonos SA, vol 56:xv, 1307. Madison, WI: ASA, SSSA, and CSSA. pp. 543−90 https://doi.org/10.2134/agronmonogr56.c16
|
[3] |
Carrow RN, Duncan RR. 1998. Salt-affected turfgrass sites: Assessment and management. Chelsea, MI: Ann Arbor Press. 185pp.
|
[4] |
Chen Z, Wang M, Waltz C, Raymer P. 2009. Genetic diversity of warm-season turfgrass: Seashore paspalum, bermudagrass, and zoysiagrass revealed by AFLPs. Floriculture and Ornamental Biotechnology 3(1):20−24
|
[5] |
Gouveia BT, Rios EF, Nunes JAR, Gezan SA, Munoz PR, et al. 2021. Multispecies Genotype × Environment Interaction for Turfgrass Quality in Five Turfgrass Breeding Programs in the Southeastern United States. Crop Science1−17 doi: 10.1002/csc2.20421
|
[6] |
Cardona CA, Duncan RR. 1997. Callus induction and high efficiency plant regeneration via somatic embryogenesis in Paspalum. Crop Science 37:1297−302 doi: 10.2135/cropsci1997.0011183X003700040045x
|
[7] |
Heckart DL, Parrott WA, Raymer PL. 2010. Obtaining sethoxydim resistance in seashore paspalum. Crop Science 50:2632−40 doi: 10.2135/cropsci2010.02.0080
|
[8] |
Petrella DP, Watkins E. 2020. Variation in fine fescue taxa response to simulated foliar shade. Crop Science 60:3377−94 doi: 10.1002/csc2.20279
|
[9] |
Richardson MD, Mattina G, Sarno M, McCalla JH, Karcher DE, et al. 2019. Shade effects on overseeded bermudagrass athletic fields: II. Rooting, species composition, and traction. Crop Science 59:2856−65 doi: 10.2135/cropsci2019.05.0311
|
[10] |
Wherley BG, Gardner DS, Metzger JD. 2005. Tall fescue photomorphogenesis as influenced by changes in the spectral composition and light intensity. Crop Science 45:562−68 doi: 10.2135/cropsci2005.0562
|
[11] |
Beard JB. 1997. Shade stresses and adaptation mechanisms of turfgrasses. International Turfgrass Society Research Journal 8:1186−96
|
[12] |
Casal JJ. 2013. Photoreceptor signaling networks in plant responses to shade. Annual Review of Plant Biology 64:403−27 doi: 10.1146/annurev-arplant-050312-120221
|
[13] |
Ballaré CL, Pierik R. 2017. The shade-avoidance syndrome: Multiple signals and ecological consequences. Plant, Cell & Environment 40:2530−43 doi: 10.1111/pce.12914
|
[14] |
Gardner DS, Goss RM. 2013. Management of turfgrass in shade. In Turfgrass: Biology, use, and management, eds. Stier JC, Horgan BP, Bonos SA, vol 56:xv, 1307. Madison, WI: ASA, SSSA, and CSSA. pp. 219–47. https://doi.org/10.2134/agronmonogr56.c6
|
[15] |
Dudeck AE, Peacock CH. 1992. Shade and turfgrass culture. In Turfgrass, eds. Waddington DV, Carrow RN, Shearman RC, vol 32:xvii, 805. Madison, WI: ASA, SSSA, and CSSA. pp. 269–84. https://doi.org/10.2134/agronmonogr32.c8
|
[16] |
Fu JJ, Sun YF, Chu XT, Yang LY, Xu YF, et al. 2014. Exogenous nitric oxide alleviates shade-induced oxidative stress in tall fescue (Festuca arundinacea Schreb.). The Journal of Horticultural Science and Biotechnology 89:193−200 doi: 10.1080/14620316.2014.11513068
|
[17] |
Kephart KD, Buxton DR, Taylor SE. 1992. Growth of C3 and C4 perennial grasses under reduced irradiance. Crop Science 32:1033−38 doi: 10.2135/cropsci1992.0011183X003200040040x
|
[18] |
Jiang Y, Duncan RR, Carrow RN. 2004. Assessment of low light tolerance of seashore paspalum and bermudagrass. Crop Science 44:587−94 doi: 10.2135/cropsci2004.5870
|
[19] |
Zhang J, Unruh JB, Kenworthy K, Erickson J, Christensen CT, et al. 2016. Phenotypic plasticity and turf performance of zoysiagrass in response to reduced light intensities. Crop Science 56:1337−48 doi: 10.2135/cropsci2015.09.0570
|
[20] |
Jiang Y, Carrow RN, Duncan RR. 2003. Effects of morning and afternoon shade in combination with traffic stress on seashore paspalum. HortScience 38:1218−22 doi: 10.21273/HORTSCI.38.6.1218
|
[21] |
Baldwin CM, Liu H, McCarty LB, Luo H, Wells CE, et al. 2009. Impacts of altered light spectral quality on warm season turfgrass growth under greenhouse conditions. Crop Science 49:1444−53 doi: 10.2135/cropsci2008.07.0412
|
[22] |
Elias AA, Robbins KR, Doerge RW, Tuinstra MR. 2016. Half a century of studying genotype × environment interactions in plant breeding experiments. Crop Science 56:2090−105 doi: 10.2135/cropsci2015.01.0061
|
[23] |
Yan W. 2016. Analysis and handling of G × E in a practical breeding program. Crop Science 56:2106−18 doi: 10.2135/cropsci2015.06.0336
|
[24] |
Yan W, Tinker NA. 2006. Biplot analysis of multi-environment trial data: principles and applications. Canadian Journal of Plant Science 86:623−45 doi: 10.4141/P05-169
|
[25] |
Yamada Y. 1962. Genotype by environment interaction and genetic correlation of the same trait under different environments. The Japanese Journal of Genetics 37:498−509 doi: 10.1266/jjg.37.498
|
[26] |
van Eeuwijk FE, Bustos-Korts DV, Malosetti M. 2016. What Should Students in Plant Breeding Know About the Statistical Aspects of Genotype × Environment Interactions? Crop Science 56:2119−40 doi: 10.2135/cropsci2015.06.0375
|
[27] |
Ceccarelli S. 1989. Wide adaptation: How wide? Euphytica 40: 197−205
|
[28] |
Agarwal A, Dutta Gupta S. 2018. Assessment of spinach seedling health status and chlorophyll content by multivariate data analysis and multiple linear regression of leaf image features. Computers and Electronics in Agriculture 152:281−89 doi: 10.1016/j.compag.2018.06.048
|
[29] |
Hassanijalilian O, Igathinathane C, Doetkott C, Bajwa S, Nowatzki J, et al. 2020. Chlorophyll estimation in soybean leaves infield with smartphone digital imaging and machine learning. Computers and Electronics in Agriculture 174:105433 doi: 10.1016/j.compag.2020.105433
|
[30] |
Rios E, Kenworthy K, Blount A, Quesenberry K, Unruh B, et al. 2017. Breeding apomictic bahiagrass (Paspalum notatum Flügge) with improved turf traits. Plant Breeding 136:253−60 doi: 10.1111/pbr.12459
|
[31] |
Zhang J, Glenn B, Unruh JB, Kruse J, Kenworthy K, et al. 2017. Comparative Performance and Daily Light Integral Requirements of Warm-Season Turfgrasses in Different Seasons. Crop Science 57:2273−82 doi: 10.2135/cropsci2017.01.0052
|
[32] |
Allard RW, Bradshaw AD. 1964. Implications of genotype-environmental interactions in applied plant breeding. Crop Science 4:503−8 doi: 10.2135/cropsci1964.0011183X000400050021x
|
[33] |
Dodd MB, McGowan AW, Power IL, Thorrold BS. 2005. Effects of variation in shade level, shade duration and light quality on perennial pastures. New Zealand Journal of Agricultural Research 48:531−43 doi: 10.1080/00288233.2005.9513686
|
[34] |
Tegg RS, Lane PA. 2004. A comparison of the performance and growth of a range of turfgrass species under shade. Australian Journal of Experimental Agriculture 44:353−58 doi: 10.1071/EA02159
|
[35] |
de Figueiredo UJ, Berchembrock YV, do Valle CB, Barrios SCL, Quesenberry KH, et al. 2019. Evaluating early selection in perennial tropical forages. Crop Breeding and Applied Biotechnology 19(3):291−99 doi: 10.1590/1984-70332019v19n3a41
|
[36] |
Leinauer B, VanLeeuwen DM, Serena M, Schiavon M, Sevostianova E. 2014. Digital image analysis and spectral reflectance to determine turfgrass quality. Agronomy Journal 106:1787−94 doi: 10.2134/agronj14.0088
|
[37] |
Depew M, Bennett S, Tillman PH. 2002. Seashore paspalum 'SDX-1'. U.S. Plant Patent No. 13294 https://www.freepatentsonline.com/PP13294.html
|
[38] |
Raymer PL, Burpee LL, Carrow RN, Schwartz BM. 2015. Seashore paspalum plant named 'UGA 31'. U.S. Plant Patent No. 25761 https://www.freepatentsonline.com/PP25761.html
|
[39] |
Trenholm LE, Unruh JB. 2019. Seashore Paspalum Management for Home Lawn Use in Florida. http://ufdcimages.uflib.ufl.edu/IR/00/00/17/53/00001/EP15300.pdf
|
[40] |
Waltz C, Martinez-Espinoza AD, McCullough P, Braman K. 2019. Paspalum Management. https://gapaspalum.com/grass-management
|
[41] |
Richardson MD, Karcher DE, Purcell LC. 2001. Quantifying turfgrass cover using digital image analysis. Crop Science 41:1884−8 doi: 10.2135/cropsci2001.1884
|
[42] |
Karcher DE, Richardson MD. 2005. Batch analysis of digital images to evaluate turfgrass characteristics. Crop Science 45:1536−39 doi: 10.2135/cropsci2004.0562
|
[43] |
Morris KN, Shearman RC. 1998. NTEP turfgrass evaluation guidelines. Beltsville, Maryland: Turfgrass Evaluation Workshop. pp. 1–5
|
[44] |
Morris KN. 2004. A guide to NTEP turfgrass ratings. https://www.ntep.org/reports/ratings.htm
|
[45] |
Butler DG, Cullis BR, Gilmour AR, Gogel BG, Thompson R. 2017. ASReml-R Reference Manual Version 4. Hemel Hempstead, HP1 1ES, UK: VSN International Ltd. https://asreml.kb.vsni.co.uk/wp-content/uploads/sites/3/2018/02/ASReml-R-Reference-Manual-4.pdf
|
[46] |
R Core Team. 2020. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing https://www.R-project.org/
|
[47] |
Gilmour AR, Thompson R, Cullis BR. 1995. Average Information REML: An efficient algorithm for Variance Parameter estimation in linear mixed models. Biometrics 51:1440 doi: 10.2307/2533274
|
[48] |
Smith AB, Stringer JK, Wei X, Cullis BR. 2007. Varietal selection for perennial crops where data relate to multiple harvests from a series of field trials. Euphytica 157:253−66 doi: 10.1007/s10681-007-9418-2
|
[49] |
Schwarz G. 1978. Estimating the dimension of a model. Annals of Statistics 6:461−64 doi: 10.1214/AOS/1176344136
|
[50] |
Mendiburu F. 2019. Agricolae: Statistical procedures for agricultural research. R package version 1.3-1.
|
[51] |
Cullis BR, Smith AB, Coombes NE. 2006. On the design of early generation variety trials with correlated data. Journal of Agricultural, Biological, and Environmental Statistics 11:381 doi: 10.1198/108571106X154443
|
[52] |
Tang Y, Horikoshi M, Li W. 2016. ggfortify: Unified interface to visualize statistical result of popular R packages. The R Journal 8:474−85 doi: 10.32614/RJ-2016-060
|
[53] |
Wickham H. 2016. ggplot2: Elegant graphics for data analysis. NY: Springer, New York. VIII, 213 pp. https://doi.org/10.1007/978-3-319-24277-4
|
[54] |
Yan W, Hunt LA, Johnson P, Stewart G, Lu X. 2002. On-farm strip trials vs. replicated performance trials for cultivar evaluation. Crop Science 42:385−92 doi: 10.2135/cropsci2002.3850
|