Agronomy and Horticulture, Department of



Dayane Cristina Lima, University of Wisconsin-Madison
Alejandro Castro Aviles, University of Wisconsin-Madison
Ryan Timothy Alpers, University of Wisconsin-Madison
Alden Perkins, University of Wisconsin-Madison
Dylan L. Schoemaker, University of Wisconsin-Madison
Martin Costa, University of Wisconsin-Madison
Kathryn J. Michel, University of Wisconsin-Madison
Shawn Kaeppler, University of Wisconsin-Madison
David Ertl, Iowa Corn
Maria Cinta Romay, Cornell University
Joseph L. Gage, NC State University
James Holland, United States Department of Agriculture
Timothy Beissinger, Georg-August-Universität Göttingen
Martin Bohn, University of Illinois Urbana-Champaign
Edward Buckler, Cornell University
Jode Edwards, USDA Agricultural Research Service
Sherry Flint-Garcia, University of Missouri
Michael A. Gore, Cornell University
Candice N. Hirsch, University of Minnesota Twin Cities
Joseph E. Knoll, USDA Agricultural Research Service
John McKay, Colorado State University
Richard Minyo, The Ohio State University
Seth C. Murray, Texas A&M University
James Schnable, University of Nebraska - LincolnFollow
Rajandeep S. Sekhon, Clemson University
Maninder P. Singh, Michigan State University
Erin E. Sparks, University of Delaware
Peter Thomison, The Ohio State University
Addie Thompson, Michigan State University
Mitchell Tuinstra, Purdue University
Jason Wallace, University of Georgia
Jacob D. Washburn, University of Missouri
Teclemariam Weldekidan, University of Delaware
Wenwei Xu, Texas A&M University
Natalia de Leon, University of Wisconsin-Madison

Document Type


Date of this Version



Lima et al. BMC Research Notes (2023) 16:219



This article is licensed under a Creative Commons Attribution 4.0 International License


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 and climatic measurements and metadata information for all environments (combination of year and location), ReadMe, and description files for each data type. A set of common hybrids is present in each environment to connect with previous evaluations. Each environment had a collaborator responsible for collecting and submitting the data, the GxE coordination team combined all the collected information and removed obvious erroneous data. Collaborators received the combined data to use, verify and declare that the data generated in their own environments was accurate. Combined data is released to the public with minimal filtering to maintain fidelity to the original data.