Full TGIF Record # 324968
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Web URL(s):https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/144945
    Last checked: 01/26/2023
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Publication Type:
i
Report
Content Type:Abstract or Summary only
Author(s):Yang, Haoguang
Author Affiliation:Rutgers University
Title:UAS based high-throughput phenotyping in assissting drought resistant turfgrass cultivar breeding
Section:Turfgrass and water conservation and management poster (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. 144945.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Abstract/Contents:"In the recent decade, advancement in unmanned aircraft system (UAS) based remote sensing technology has enabled researchers to apply high throughut phenotyping method to assisst plant breeding programs. Developing drought resistance turfgrass cultivars has been one of the focuses of turfgrass breeders, and traditional phenotyping such as visual assessment has been the bottleneck of turfgrass breeding programs due to its labor intensive, subjective and time consuming nature. In this study, we compared NDVI data collected from UAS based high throughput phenotyping system to data collectd from lightbox, hand-held NDVI meter and visual assessment in a rain out shelter drought resistance study of perennial ryegrass (Lolium perenne) and tall fescue (Festuca arundinacea) in the year 2021 and 2022. The prelimary result showed a good correlation between the high throughput phenotyping method and the conventional phenotyping method. Data from 2022 will be collected and analyzed this summer."
Language:English
References:0
Note:"370"
This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Yang, H. 2022. UAS based high-throughput phenotyping in assissting drought resistant turfgrass cultivar breeding. Agron. Abr. p. 144945.
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https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/144945
    Last checked: 01/26/2023
    Requires: JavaScript; HTML5
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