Full TGIF Record # 317147
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Web URL(s):https://scisoc.confex.com/scisoc/2021am/meetingapp.cgi/Paper/134199
    Last checked: 04/01/2022
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Publication Type:
i
Report
Content Type:Abstract or Summary only
Author(s):Rockstad, Greta; Austin, Robert; Miller, Grady L.; Milla-Lewis, Susana R.
Author Affiliation:Crop and Soil Sciences, North Carolina State University, Raleigh, NC
Title:Assessing UAV-based imagery for drought stress phenotyping in St. Augustinegrass
Section:Turfgrass physiology, molecular biology, and genetics poster (includes student competition)
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C05 turfgrass science
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Meeting Info.:Salt Lake City, Utah: November 7-10, 2021
Source:ASA, CSSA and SSSA International Annual Meetings. 2021, p. 134199.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Related Web URL:https://scisoc.confex.com/scisoc/2021am/mediafile/Handout/Paper134199/Final_Rockstad_C5_2021_poster.pdf
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http://docs.google.com/viewer?url=https://scisoc.confex.com/scisoc/2021am/mediafile/Handout/Paper134199/Final_Rockstad_C5_2021_poster.pdf
    Last checked: 04/05/2022
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Abstract/Contents:"Most turfgrass traits are rated using a subjective visual scale; however, these ratings are often supplemented with more quantitative traits like percent green cover, typically obtained by moving a box with a camera and uniform lighting from plot to plot and analyzing the images. This offers the objective standardization but at the cost of significant effort. Unmanned aerial vehicle (UAV) imagery at low altitudes may offer a quicker alternative, in addition to being able to simultaneously measure other traits that are commonly collected on the ground like normalized difference vegetation index (NDVI) and canopy temperature. There have been efforts to incorporate UAV imagery into turfgrass ratings, but none have focused on drought stress in St. Augustinegrass, a warm-season turfgrass commonly grown in the southeastern United States known for its weed suppression and shade tolerance. In this study, UAV imagery was used alongside ground data to measure percent green cover and NDVI on a plot-level basis in a population of 'Raleigh' x 'Seville' St. Augustinegrass at two field sites in North Carolina. Additionally, because it was collected simultaneously, aerial canopy temperature was also evaluated for its usefulness as a drought stress trait, although there was no ground equivalent. Traits were measured prior to the initiation of drought to obtain a baseline and every three days during the drought period. Correlation analysis showed strong agreement between measurements collected on the ground and in the air both before and throughout the drought period, suggesting that UAVs could be used to help more efficiently phenotype drought traits in St. Augustinegrass with the development of a streamlined image processing pipeline."
Language:English
References:0
Note:This item is an abstract only!
"Poster #1252"
"337"
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Rockstad, G., R. Austin, G. L. Miller, and S. R. Milla-Lewis. 2021. Assessing UAV-based imagery for drought stress phenotyping in St. Augustinegrass. Agron. Abr. p. 134199.
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https://scisoc.confex.com/scisoc/2021am/meetingapp.cgi/Paper/134199
    Last checked: 04/01/2022
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