@article{graham_gouveia_carbajal_laat_milla-lewis_2022, title={Using base index for selection of St. Augustinegrass breeding lines evaluated in multienvironment trials for turfgrass quality traits and stress tolerance in North Carolina}, volume={7}, ISSN={["1435-0653"]}, url={https://doi.org/10.1002/csc2.20755}, DOI={10.1002/csc2.20755}, abstractNote={AbstractSt. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is a warm‐season turfgrass primarily used for home lawns and commercial landscapes in the southern United States. New cultivars that possess desirable turfgrass quality (TQ) in combination with improved tolerance to diseases, drought and cold are needed to increase the sustainability of St. Augustinegrass production and maintenance in transitional zones. This study's objectives were to evaluate breeding lines in multienvironment trials across North Carolina to (a) assess relationships among economically important traits, and (b) select genotypes with stable performance across environments. Sixty‐one St. Augustinegrass genotypes and five commercial checks were established in replicated field trials at three locations across North Carolina. Entries were evaluated for rate of establishment, TQ, turfgrass stand density, genetic color, leaf texture, uniformity, winter survival, fall color, drought tolerance, and gray leaf spot resistance from 2017 to 2020. Best linear unbiased predictions were used to calculate a selection index to identify elite genotypes across traits. The 10 traits were clustered into three groups: winter survival and fall color; genetic color, leaf texture, and gray leaf spot resistance; and establishment rate, TQ, density, uniformity, and drought tolerance. Selection of the top 10 genotypes using the selection index resulted in positive estimated genetic gains for all 10 traits, indicating it is an effective method for simultaneous selection. Line XSA 14271 outperformed ‘Palmetto’, ‘Raleigh’, ‘Captiva’, and ‘Seville’, for several traits and was the top‐ranked line. It will be advanced to on‐farm trials to evaluate sod production traits to assess its potential for commercial release.}, journal={CROP SCIENCE}, author={Graham, Sydney E. and Gouveia, Beatriz Tome and Carbajal, Esdras M. and Laat, Rocio and Milla-Lewis, Susana R.}, year={2022}, month={Jul} }
 @article{yu_brown_graham_carbajal_zuleta_milla-lewis_2019, title={Detection of quantitative trait loci associated with drought tolerance in St. Augustinegrass}, volume={14}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0224620}, abstractNote={St. Augustinegrass (Stenotaphrum secundatum) is a warm-season grass species commonly utilized as turf in the southeastern US. Improvement in the drought tolerance of St. Augustinegrass has significant value within the turfgrass industry. Detecting quantitative trait loci (QTL) associated with drought tolerance will allow for advanced breeding strategies to identify St. Augustinegrass germplasm with improved performance for this trait. A multi-year and multi-environment study was performed to identify QTL in a ‘Raleigh’ x ‘Seville’ mapping population segregating for phenotypic traits associated with drought tolerance. Phenotypic data was collected from a field trial and a two-year greenhouse study, which included relative water content (RWC), chlorophyll content (CHC), leaf firing (LF), leaf wilting (LW), green cover (GC) and normalized difference vegetative index (NDVI). Significant phenotypic variance was observed and a total of 70 QTL were detected for all traits. A genomic region on linkage group R6 simultaneously harbored QTL for RWC, LF and LW in different experiments. In addition, overlapping QTL for GC, LF, LW and NDVI were found on linkage groups R1, R5, R7 and S2. Sequence alignment analysis revealed several drought response genes within these regions. The QTL identified in this study have potential to be used in the future to identify genes associated with drought tolerance and for use in marker-assisted breeding.}, number={10}, journal={PLOS ONE}, author={Yu, Xingwang and Brown, Jessica M. and Graham, Sydney E. and Carbajal, Esdras M. and Zuleta, Maria C. and Milla-Lewis, Susana R.}, year={2019}, month={Oct} }