A network modeling approach provides insights into the environment-specific yield architecture of wheat
North Carolina State University | USDA Agricultural Research Service | University of Georgia
Partner institutions
North Carolina State University
Raleigh, NC, USA
A public land-grant research university in Raleigh, North Carolina, with major programs in crop and soil sciences.
USDA Agricultural Research Service
Multiple sites, USA
The chief in-house scientific research agency of the U.S. Department of Agriculture, conducting research across crop science, food safety, and agricultural technology nationwide.
University of Georgia
Athens, GA, USA
A public land-grant research university in Athens, Georgia, with programs in crop and soil sciences.
How Vibe analyzers were used
Kernel morphometric parameters (length, width, area, weight) measured with the Vibe QM3 grain analyzer fed a structural equation model mapping how QTL effects on yield components translate into overall wheat yield across five environments.
Study overview
Using a 358-line recombinant inbred wheat population evaluated across five environments, this study mapped quantitative trait loci (QTL) affecting spike and seed yield and applied structural equation/network modeling to trace how QTL effects on yield components (kernel number, kernel size) propagate to overall yield. Kernel morphometric parameters and total seed yield were obtained using the Vibe QM3 grain analyzer on threshed seed samples. Major QTL effects varied dramatically by environment and were proportionally smaller on total yield than on the component traits they influenced, showing that the genetic architecture of wheat yield is environment-specific.
Topics and keywords
Related crop analysis
Bibliographic details
Year: 2022
Publication: Genetics
Institutions: North Carolina State University, USDA Agricultural Research Service, University of Georgia
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