Full TGIF Record # 333434
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Web URL(s):https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150435
    Last checked: 12/01/2023
Publication Type:
i
Report
Content Type:Abstract or Summary only
Author(s):Serba, Desalegn D.; Conley, Matthew M.; Wu, Yanqi; Hejl, Reagan; Thorp, Kelly R.; Williams, Clinton F.
Author Affiliation:Serba: Presenting Author and USDA-ARS, Maricopa, AZ; Conley: ARS, USDA, Maricopa, AZ; Wu: Oklahoma State University, Stillwater, OK; Hejl: Soil & Crop Sciences, USDA-ARS, Maricopa, AZ; Thorp and Williams: USDA-ARS, Maricopa, AZ
Title:RGB-based phenotyping of hybrid bermudagrass for turf performance
Section:Turfgrass physiology, molecular biology, breeding, genetic and microbiome poster (includes student competition)
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C05 turfgrass science
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210
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Meeting Info.:St. Louis, Missouri: October 29-November 1, 2023
Source:ASA, CSSA, SSSA International Annual Meeting. 2023, p. 150435.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Abstract/Contents:"Hybrid turf bermudagrass is a warm season turfgrass extensively used in the U.S. south and southwest. High-throughput phenotyping (HTP) using proximal imagery is a non-destructive and rapid approach for assessing multiple phenotypic traits for genetic variation related to turfgrass growth, quality, and stress tolerance. A total of 48 bermudagrass genotypes have been established in the field at Maricopa, AZ since August 31, 2021. The experiment was laid out in a split-block design with two replications, where three irrigation rates are main plots and genotypes are assigned to sub-plots. The sub-plots were imaged every other week starting in March 2023 using a Nikon N1 aw1 RGB (red-green-blue) camera in nadir view at 2 meters height, and the data were processed using the opensource TurfAnalyzer software. Results revealed variations among the hybrids for spring green up, color, density, uniformity, and overall turf quality traits. Image based data were highly correlated with concurrent visual assessments. This study illustrates an application of image based HTP in assessing important turfgrass characteristics."
Language:English
References:0
Note:This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Serba, D. D., M. M. Conley, Y. Wu, R. Hejl, K. R. Thorp, and C. F. Williams. 2023. RGB-based phenotyping of hybrid bermudagrass for turf performance. Agron. Abr. p. 150435.
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Web URL(s):
https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150435
    Last checked: 12/01/2023
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