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Full-Text Articles in Horticulture
2020-2021 Field Seasons Of Maize Gxe Project Within The Genomes To Fields Initiative, Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Alden Perkins, Dylan L. Schoemaker, Martin Costa, Kathryn J. Michel, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Michael A. Gore, Candice N. Hirsch, Joseph E. Knoll, John Mckay, Richard Minyo, Seth C. Murray, James Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Erin E. Sparks, Peter Thomison, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Jacob D. Washburn, Teclemariam Weldekidan, Wenwei Xu, Natalia De Leon
2020-2021 Field Seasons Of Maize Gxe Project Within The Genomes To Fields Initiative, Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Alden Perkins, Dylan L. Schoemaker, Martin Costa, Kathryn J. Michel, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Michael A. Gore, Candice N. Hirsch, Joseph E. Knoll, John Mckay, Richard Minyo, Seth C. Murray, James Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Erin E. Sparks, Peter Thomison, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Jacob D. Washburn, Teclemariam Weldekidan, Wenwei Xu, Natalia De Leon
Department of Agronomy and Horticulture: Faculty Publications
Objectives: This release note describes the Maize GxE project datasets within the Genomes to Fields (G2F) Initiative. The Maize GxE project aims to understand genotype by environment (GxE) interactions and use the information collected to improve resource allocation efficiency and increase genotype predictability and stability, particularly in scenarios of variable environmental patterns. Hybrids and inbreds are evaluated across multiple environments and phenotypic, genotypic, environmental, and metadata information are made publicly available. Data description: The datasets include phenotypic data of the hybrids and inbreds evaluated in 30 locations across the US and one location in Germany in 2020 and 2021, soil …
Method Developments To Identify Loci And Selection Patterns Associated With Genotype By Environment Interactions In Soybean, Mary M. Happ
Method Developments To Identify Loci And Selection Patterns Associated With Genotype By Environment Interactions In Soybean, Mary M. Happ
Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research
For many complex traits such as grain yield, genotype by environment (GxE) interactions are a prevalent source of phenotypic variation. Exploring the capacity of different methodologies to help describe and quantify the GxE interaction landscape for grain yield is an important step in informing plant breeders what the most viable strategies for management and exploitation of GxE may be. In this endeavor, we compared the results from multiple genome wide association studies (GWAS) that used either stability estimators as a phenotype to capture GxE variance, or directly mapped GxE in a mixed model for yield. Leading into this study, a …