Fastlink to record 333428
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| Full TGIF Record # 333428 Item 1 of 1 |
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| Web URL(s): | https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/151004 Last checked: 12/01/2023 |
| Publication Type: | Report |
| Content Type: | Abstract or Summary only |
| Author(s): | Escalona, Maria Carolina; Rockstad, Greta; de Siqueira Gesteira, Gabriel; Gouveia, Beatriz T.; Yu, Xingwang; Austin, Robert; Milla-Lewis, Susana R. |
| Author Affiliation: | Escalona: Presenting Author and Crop and Soil Sciences, North Carolina State University, Raleigh, NC; Rockstad: USDA-ARS Soybean & Nitrogen Fixation Unit; de Siqueira Gesteira: North Carolina State University; Gouveia: Biology, North Carolina State University, Raleigh, NC; Yu: Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC; Austin: Crop and Soil Sciences, North Carolina State University, Raleigh, NC; Milla-Lewis: Crop Science, North Carolina State University, Raleigh, NC |
| Title: | Using high throughput phenotyping methods to validate previously identified QTL associated with drought tolerance in S. secundatum |
| Section: | Turfgrass physiology, molecular biology, breeding, genetic and microbiome poster (includes student competition) Other records with the "Turfgrass physiology, molecular biology, breeding, genetic and microbiome poster (includes student competition)" Section C05 turfgrass science Other records with the "C05 turfgrass science" Section 210 Other records with the "210" Section |
| Meeting Info.: | St. Louis, Missouri: October 29-November 1, 2023 |
| Source: | ASA, CSSA, SSSA International Annual Meeting. 2023, p. 151004. |
| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
| # of Pages: | 1 |
| Abstract/Contents: | "Unmanned Aircraft systems (UAS)-assisted high-throughput phenotyping holds significant potential for enhancing the efficiency of data collection, reducing variability in visual ratings, promoting standardization across trials, and ultimately improving phenotyping accuracy. By utilizing multispectral and RGB imagery, valuable drought-related data such as normalized difference vegetation index (NDVI) and percent green cover (PGC) can be obtained. Extensive research has demonstrated a strong correlation between aerial and ground-based NDVI measurements, establishing it as the preferred vegetation index for drought monitoring. St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is a warm-season turfgrass widely utilized in residential lawns and landscapes throughout the southeastern and south-central regions of the United States. Its exceptional shade tolerance and dense stoloniferous growth habit have contributed to its popularity. However, the species experiences adverse effects drought conditions, significantly impacting its performance. To address this issue, a mapping population derived from a cross between 'XSA10098' and 'XSA10127', two breeding lines selected due to their divergent responses to drought in both greenhouse and field environments was planted at the Sanhills Research Station (Jackson Springs, NC) in randomized complete block design with three replicates. Both NDVI and PGC were collected before irrigation was withheld and, subsequent measurements were taken every three days during the drought period. The study will continue with a third year of data collection and analysis in 2023, with the gathered traits serving as a basis for mapping quantitative trait loci. Ultimately, this information will guide marker-assisted selection to enhance drought resistance in St. Augustinegrass." |
| Language: | English |
| References: | 0 |
| Note: | This item is an abstract only! |
| ASA/CSSA/SSSA Citation (Crop Science-like – may be incomplete): | Escalona, M. C., G. Rockstad, G. de Siqueira Gesteira, B. T. Gouveia, X. Yu, R. Austin, et al. 2023. Using high throughput phenotyping methods to validate previously identified QTL associated with drought tolerance in S. secundatum. Agron. Abr. p. 151004. |
| Fastlink to access this record outside TGIF: | http://tic.msu.edu/tgif/flink/RECNO/333428 |
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| Web URL(s) : | https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/151004 Last checked: 12/01/2023 |
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