[1]

Christians NE, Patton AJ, Law QD. 2016. Warm-season grasses. In Fundamentals of Turfgrass Management. 5th Edition. USA: John Wiley & Sons. pp. 75−95 doi: 10.1002/9781119308867.ch4

[2]

Busey P. 2003. St. Augustinegrass, Stenotaphrum secundatum (Walt.) Kuntze. In Biology, Breeding, and Genetics of Turfgrasses, eds. Casler MD, Duncan RR. Hoboken, NJ: John Wiley & Sons, Inc. pp. 309−330

[3]

DiPaola JM, Beard JB. 1992. Physiological effects of temperature stress. In Turfgrass, eds. Waddington DV, Carrow RN, Shearman RC. USA: The American Society of Agronomy, Inc.; Crop Science Society of America, Inc.; Soil Science Society of America, Inc. pp. 231−267 doi: 10.2134/agronmonogr32.c7

[4]

Miller GL. 2026. Sod Producers' Report for North Carolina. USA: North Carolina Turfgrass Producers. https://content.ces.ncsu.edu/sod-producers-report-for-north-carolina#:~:text=Producers%20reported%20nominal%20price%20increases,%2C%20with%20an%208%25%20decrease

[5]

Ebdon, JS, Gagne RA, Manley RC. 2002. Comparative cold tolerance in diverse turf quality genotypes of perennial ryegrass. HortScience 37:826−830

doi: 10.21273/hortsci.37.5.826
[6]

Fan, J, Zhang W, Amombo E, Hu L, Kjorven JO, et al. 2020. Mechanisms of environmental stress tolerance in turfgrass. Agronomy 10:522

doi: 10.3390/agronomy10040522
[7]

Li S, Yang Y, Zhang Q, Liu N, Xu Q, et al. 2018. Differential physiological and metabolic response to low temperature in two zoysiagrass genotypes native to high and low latitude. PLoS One 13:e0198885

doi: 10.1371/journal.pone.0198885
[8]

Steponkus PL. 1984. Role of the plasma membrane in freezing injury and cold acclimation. Annual Review of Plant Physiology 35:543−584

doi: 10.1146/annurev.pp.35.060184.002551
[9]

Fry J, Huang B. 2004. Applied Turfgrass Science and Physiology. Hoboken, N.J.: John Wiley & Sons. 320 pp. www.wiley.com/en-us/Applied+Turfgrass+Science+and+Physiology-p-9780471472704

[10]

Huang B, DaCosta M, Jiang Y. 2014. Research advances in mechanisms of turfgrass tolerance to abiotic stresses: from physiology to molecular biology. Critical Reviews in Plant Sciences 33:141−189

doi: 10.1080/07352689.2014.870411
[11]

Patton AJ, Reicher ZJ. 2007. Zoysiagrass species and genotypes differ in their winter injury and freeze tolerance. Crop Science 47:1619−1627

doi: 10.2135/cropsci2006.11.0737
[12]

Kimball JA, Isleib TG, Reynolds WC, Zuleta MC, Milla-Lewis SR. 2016. Combining ability for winter survival and turf quality traits in St. Augustinegrass. HortScience 51:810−815

doi: 10.21273/hortsci.51.7.810
[13]

Kimball JA, Tuong TD, Arellano C, Livingston DP, Milla-Lewis SR. 2018. Linkage analysis and identification of quantitative trait loci associated with freeze tolerance and turf quality traits in St. Augustinegrass. Molecular Breeding 38:67

doi: 10.1007/s11032-018-0817-y
[14]

Rockstad GBG, Austin RE, Gouveia BT, Carbajal EM, Milla-Lewis SR. 2024. Assessing unmanned aerial vehicle-based imagery for breeding applications in St. Augustinegrass under drought and non-drought conditions. Crop Science 64:496−510

doi: 10.1002/csc2.21128
[15]

Wang T, Chandra A, Jung J, Chang A. 2022. UAV remote sensing based estimation of green cover during turfgrass establishment. Computers and Electronics in Agriculture 194:106721

doi: 10.1016/j.compag.2022.106721
[16]

Du H, Wu N, Chang Y, Li X, Xiao J, et al. 2013. Carotenoid deficiency impairs ABA and IAA biosynthesis and differentially affects drought and cold tolerance in rice. Plant Molecular Biology 83:475−488

doi: 10.1007/s11103-013-0103-7
[17]

Jin HX, Jiang M, Yang JF, Wu ZH, Ma LL, et al. 2022. A survey of enhanced cold tolerance and low-temperature-induced anthocyanin accumulation in a novel Zoysia japonica biotype. Plants 11:429

doi: 10.3390/plants11030429
[18]

Xiong J, Wen G, Song J, Liu X, Chen Q, et al. 2024. Knockout of the chlorophyll a oxygenase gene OsCAO1 reduces chilling tolerance in rice seedlings. Genes 15:721

doi: 10.3390/genes15060721
[19]

Long S, Yan F, Yang L, Sun Z, Wei S. 2020. Responses of Manila Grass (Zoysia matrella) to chilling stress: from transcriptomics to physiology. PLoS One 15:e0235972

doi: 10.1371/journal.pone.0235972
[20]

Fang S, Lang T, Han T, Cai M, Cao S, et al. 2020. A novel efficient single-phase dual-emission phosphor with high resemblance to the photosynthetic spectrum of chlorophyll A and B. Journal of Materials Chemistry C 8:6245−6253

doi: 10.1039/D0TC00811G
[21]

Kimball JA, Tuong TD, Arellano C, Livingston DP, Milla-Lewis SR. 2017. Assessing freeze tolerance in St. Augustinegrass: II. acclimation treatment effects. Euphytica 213:282

doi: 10.1007/s10681-017-2074-2
[22]

Moseley DO, Trappe JM, Milla-Lewis SR, Chandra A, Kenworthy KE, et al. 2021. Characterizing the growth and winter survival of commercially available and experimental genotypes of St. Augustinegrass. Crop Science 61:3097−3109

doi: 10.1002/csc2.20445
[23]

Bateman DR. 1980. Notice to Sod Producers and Growers Relative to the Naming and Release of the New St. Augustine Cultivar 'Raleigh'. Raleigh, NC: North Carolina Agricutural Research Service.

[24]

Brown JM, Yu X, Holloway HMP, Tuong TD, Schwartz BM, et al. 2021. Identification of QTL associated with cold acclimation and freezing tolerance in Zoysia japonica. Crop Science 61:3044−3055

doi: 10.1002/csc2.20368
[25]

Mackay TFC, Stone EA, Ayroles JF. 2009. The genetics of quantitative traits: challenges and prospects. Nature Reviews Genetics 10:565−577

doi: 10.1038/nrg2612
[26]

Asrat Z. 2021. The application of quantitative trait loci (QTL) mapping in crop improvement. International Journal of Plant Breeding and Genetics 8:1−5

[27]

Parihar A, Shiwani. 2022. Molecular breeding and marker-assisted selection for crop improvement. In Plant Genomics for Sustainable Agriculture, eds. Singh RL, Mondal S, Parihar A, Singh PK. Singapore: Springer Nature Singapore. pp. 129−164 doi: 10.1007/978-981-16-6974-3_6

[28]

Morris K. 2001. National Turfgrass Evaluation Program. Beltsville, MD, USA: NTEP. 200 pp. www.ntep.org/data/bg07/bg07_13-10f/bg07_13-10f.pdf

[29]

Wellburn AR. 1994. The spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. Journal of Plant Physiology 144:307−313

doi: 10.1016/S0176-1617(11)81192-2
[30]

Neff MM, Chory J. 1998. Genetic interactions between phytochrome A, phytochrome B, and cryptochrome 1 during Arabidopsis development. Plant Physiology 118:27−35

doi: 10.1104/pp.118.1.27
[31]

Rabino I, Mancinelli AL. 1986. Light, temperature, and anthocyanin production. Plant Physiology 81:922−924

doi: 10.1104/pp.81.3.922
[32]

Tashtoush SH, Ereifej KI, Feng H, Rababah TM, Al-U'datt MH, et al. 2016. Temperature and acidified solvent effect on total anthocyanins and RP-HPLC phenolic acids determination in selected spices. Food and Nutrition Sciences 7:20−29

doi: 10.4236/fns.2016.71003
[33]

Butler DG, Cullis BR, Gilmour AR, Gogel BJ, Thompson R. 2017. ASReml-R Reference Manual Version 4. Hemel Hempstead, UK: VSN International Ltd. 187 pp. https://asreml.kb.vsni.co.uk/wp-content/uploads/sites/3/ASReml-R-Reference-Manual-4.2.pdf

[34]

Posit team. 2025. RStudio: integrated development environment for R. Boston, MA, USA: Posit Software, PBC. www.posit.co

[35]

R Core Team. 2024. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. www.R-project.org

[36]

Dixon PM. 2016. Should blocks be fixed or random? Conference on Applied Statistics in Agriculture 4:1−17

doi: 10.4148/2475-7772.1474
[37]

Poland JA, Brown PJ, Sorrells ME, Jannink JL. 2012. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS One 7:e32253

doi: 10.1371/journal.pone.0032253
[38]

Melo ATO, Bartaula R, Hale I. 2016. GBS-SNP-CROP: a reference-optional pipeline for SNP discovery and plant germplasm characterization using variable length, paired-end genotyping-by-sequencing data. BMC Bioinformatics 17:29

doi: 10.1186/s12859-016-0879-y
[39]

Schoonmaker AN, Yow AG, Yu X, van der Laat R, Glaubitz JC, et al. 2025. A whole-genome assembly of St. Augustinegrass and visualizing diversity within the species. The Plant Genome 19:e70144

doi: 10.1002/tpg2.70144
[40]

Mollinari M, Garcia AAF. 2019. Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models. G3 Genes|Genomes|Genetics 9:3297−3314

doi: 10.1534/g3.119.400378
[41]

da Silva Pereira G, Gemenet DC, Mollinari M, Olukolu BA, Wood JC, et al. 2020. Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population. Genetics 215:579−595

doi: 10.1534/genetics.120.303080
[42]

Zou F, Fine JP, Hu J, Lin DY. 2004. An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci. Genetics 168:2307−2316

doi: 10.1534/genetics.104.031427
[43]

Rockstad GBG, Yu X, de Siqueira Gesteira G, Gaire S, Dickey AN, et al. 2025. The integration of QTL and transcriptome studies reveals candidate genes for water stress response in St. Augustinegrass. BMC Plant Biology 25:662

doi: 10.1186/s12870-025-06692-7
[44]

Gaire S, Yu X, Milla-Lewis SR. 2024. Molecular advances in St. Augustinegrass: from DNA markers to genome sequencing. Grass Research 4:e021

doi: 10.48130/grares-0024-0017
[45]

Ding Y, Shi Y, Yang S. 2024. Regulatory networks underlying plant responses and adaptation to cold stress. Annual Review of Genetics 58:43−65

doi: 10.1146/annurev-genet-111523-102226
[46]

Kim JS, Kidokoro S, Yamaguchi-Shinozaki K, Shinozaki K. 2024. Regulatory networks in plant responses to drought and cold stress. Plant Physiology 195:170−189

doi: 10.1093/plphys/kiae105
[47]

Khahani B, Tavakol E, Shariati V, Rossini L. 2021. Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions. Scientific Reports 11:6942

doi: 10.1038/s41598-021-86259-2
[48]

Lv W, Zheng X, Kuang Y, Cao D, Yan Y, et al. 2016. QTL variations for growth-related traits in eight distinct families of common carp (Cyprinus carpio). BMC Genetics 17:65

doi: 10.1186/s12863-016-0370-9
[49]

Chen Y, Lübberstedt T. 2010. Molecular basis of trait correlations. Trends in Plant Science 15:454−461

doi: 10.1016/j.tplants.2010.05.004
[50]

Capilla-Pérez L, Solier V, Gilbault E, Lian Q, Goel M, et al. 2024. Enhanced recombination empowers the detection and mapping of quantitative trait loci. Communications Biology 7:829

doi: 10.1038/s42003-024-06530-w
[51]

Zhu C, Gore M, Buckler ES, Yu J. 2008. Status and prospects of association mapping in plants. The Plant Genome 1:plantgenome2008.02.0089

doi: 10.3835/plantgenome2008.02.0089
[52]

Zhu M, Zhao S. 2007. Candidate gene identification approach: progress and challenges. International Journal of Biological Sciences 3:420−427

doi: 10.7150/ijbs.3.420
[53]

Fanucchi F, Alpi E, Olivieri S, Cannistraci CV, Bachi A, et al. 2012. Acclimation increases freezing stress response of Arabidopsis thaliana at proteome level. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 1824:813−825

doi: 10.1016/j.bbapap.2012.03.015
[54]

Jiang HW, Xin DW, Liu CY, Qiu HM, Zhu RS, et al. 2014. A comparative proteomics analysis of soybean cotyledon and unifoliolate leaves under heat (chilling) treatments. Current Proteomics 11:61−70

doi: 10.2174/1570164611666140206230157
[55]

Xie Z, Lin W, Yu G, Cheng Q, Xu B, et al. 2019. Improved cold tolerance in switchgrass by a novel CCCH-type zinc finger transcription factor gene, PvC3H72, associated with ICE1–CBF–COR regulon and ABA-responsive genes. Biotechnology for Biofuels 12:224

doi: 10.1186/s13068-019-1564-y
[56]

Brown JM, Weldt CE, Holloway HMP, Tuong TD, Patton AJ, et al. 2023. Transcriptomic analysis of zoysiagrass (Zoysia japonica) provides novel insights into the molecular basis of cold acclimation. Grass Research 3:25

doi: 10.48130/gr-2023-0025
[57]

Mi X, Tang M, Zhu J, Shu M, Wen H, et al. 2024. Alternative splicing of CsWRKY21 positively regulates cold response in tea plant. Plant Physiology and Biochemistry 208:108473

doi: 10.1016/j.plaphy.2024.108473
[58]

Jeena GS, Kumar S, Shukla RK. 2019. Structure, evolution and diverse physiological roles of SWEET sugar transporters in plants. Plant Molecular Biology 100:351−365

doi: 10.1007/s11103-019-00872-4
[59]

Nie P, Wang L, Li M, Lyu D, Qin S, et al. 2023. MdSWEET23, a sucrose transporter from apple (Malus × domestica Borkh. ), influences sugar metabolism and enhances cold tolerance in tomato. Frontiers in Plant Science 14:1266194

doi: 10.3389/fpls.2023.1266194
[60]

Le Hir R, Spinner L, Klemens PAW, Chakraborti D, de Marco F, et al. 2015. Disruption of the sugar transporters AtSWEET11 and AtSWEET12 affects vascular development and freezing tolerance in Arabidopsis. Molecular Plant 8:1687−1690

doi: 10.1016/j.molp.2015.08.007