Full TGIF Record # 324865
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Web URL(s):https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/142566
    Last checked: 01/24/2023
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Publication Type:
Content Type:Abstract or Summary only
Author(s):Rockstad, Greta; Austin, Robert; Gouveia, Beatriz T.; Carbajal Melgar, Esdras Manuel; Milla-Lewis, Susana R.
Author Affiliation:Rockstad: Presenting Author and North Carolina State Univeristy; Austin, Gouveia, Carbajal Melgar, and Milla-Lewis: North Carolina State University
Title:Assessing unmanned aerial vehicle-based imagery for breeding applications in St. Augustinegrass
Section:Molecular Techniques, Genetics, Microbiome, and Turfgrass Breeding Oral (includes student competition)
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C05 turfgrass science
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Meeting Info.:Baltimore, Maryland: November 6-9, 2022
Source:ASA, CSSA, SSSA International Annual Meeting. 2022, p. 142566.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Abstract/Contents:"The use of imagery collected from small unmanned aerial vehicles (UAVs) in turfgrass breeding has recently increased, as has the need to develop drought-resistant cultivars. However, prior to implementing UAVs for data collection under drought stress conditions, ground-truthing is necessary to ensure the accuracy of UAV-based traits. St. Augustinegrass is a warm-season turfgrass commonly grown in the southeastern United States known for its shade tolerance and aggressive stoloniferous growth but is lacking in drought resistance. Thus, this study sought to evaluate the potential of UAV-based traits by collecting ground measurements for percent green cover (PGC) and normalized difference vegetation index (NDVI) and comparing them to UAV-derived measurements under drought conditions. A population of 115 genotypes derived from the cross between 'Raleigh' x 'Seville' at two field sites in North Carolina served as the plant material. Correlation analysis showed strong agreement between ground and UAV-derived PGC and NDVI before and throughout the drought period, (r = 0.82 - 0.95), suggesting that UAVs could be used to help more efficiently phenotype drought traits in St. Augustinegrass. Additionally, no efforts have focused on identifying the most useful vegetation indices (VIs) to phenotype drought stress traits for St. Augustinegrass breeding. Using broad-sense heritability (H2) to evaluate a panel of fourteen vegetation indices (VIs) designed to measure PGC identified NDVI as the most suitable trait to phenotype under both drought and non-drought conditions as the high H2 provides a preliminary indication of potentially greater response to selection."
Note:This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Rockstad, G., R. Austin, B. T. Gouveia, E. M. Carbajal Melgar, and S. R. Milla-Lewis. 2022. Assessing unmanned aerial vehicle-based imagery for breeding applications in St. Augustinegrass. Agron. Abr. p. 142566.
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    Last checked: 01/24/2023
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