2018–2019 field seasons of the Maize Genomes to Fields (G2F) G x E project

Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Bridget A. McFarland, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Candice N. Hirsch, Elizabeth Hood, David C. Hooker, Joseph E. Knoll, Judith M. Kolkman, Sanzhen LiuJohn McKay, Richard Minyo, Danilo E. Moreta, Seth C. Murray, Rebecca Nelson, James C. Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Peter Thomison, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Jacob D. Washburn, Teclemariam Weldekidan, Randall J. Wisser, Wenwei Xu, Natalia de Leon

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Objectives: This report provides information about the public release of the 2018–2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and inbred lines across multiple environments and makes available phenotypic, genotypic, environmental, and metadata information. The initiative understands the necessity to characterize and deploy public sources of genetic diversity to face the challenges for more sustainable agriculture in the context of variable environmental conditions. Data description: Datasets include phenotypic, climatic, and soil measurements, metadata information, and inbred genotypic information for each combination of location and year. Collaborators in the G2F initiative collected data for each location and year; members of the group responsible for coordination and data processing combined all the collected information and removed obvious erroneous data. The collaborators received the data before the DOI release to verify and declare that the data generated in their own locations was accurate. ReadMe and description files are available for each dataset. Previous years of evaluation are already publicly available, with common hybrids present to connect across all locations and years evaluated since this project’s inception.

Original languageEnglish (US)
Article number29
JournalBMC Genomic Data
Issue number1
StatePublished - Dec 2023

Bibliographical note

Funding Information:
We gratefully acknowledge support from: National Corn Growers Association, Iowa Corn Promotion Board, Georgia Corn Commission, Nebraska Corn Board, Ohio Corn Marketing Program, Corn Marketing Program of Michigan, Texas Corn Producers Board, University of Göttingen startup funds, USDA-ARS, and USDA Germplasm Enhancement of Maize program.

Funding Information:
We gratefully acknowledge contributions from many field managers and data collectors including: Dustin Eilert, Marina Borsecnik, Rachel Perry, Renata Barcelos and Ben Fischer (de Leon/Kaeppler labs, University of Wisconsin—Madison). Amanda Gilbert (Hirsch lab, University of Minnesota). Christine Smith, Brandi Sigmon, Connor Pedersen, Nathaniel Pester, Isaac Stevens (Schnable Lab, University of Nebraska-Lincoln). Trevor Perla, Amy Deariso, Paige Coffee, Steven Hughes, and C.J. Dudley (USDA Tifton). Naomi Rodman, Spencer Caro, Coleman Grindle, Allison McCabe, Samuel Morris, and Bamidele Sangoyomi (Wallace lab—University of Georgia). William Widdicombe and Linsey Newton (Singh and Thompson Labs, Michigan State University). Susan Melia-Hancock and Jim Elder (Flint-Garcia Lab, USDA-ARS, Columbia MO). Emmalea Ernest and Victor Green (University of Delaware). Colby Bass and Regan Lindsey (Texas A&M University System). Kyle Evans, Kirsten Hein, Anne Howard, Jack Mullen, Patrick Woods (McKay Lab, Colorado State University). Dietrich Kaufmann (Beissinger Lab). Christina Poudyal, Kevin Silverstein, Anna Rogers, Luis Samayoa, Tyson Swetnam. In addition, we gratefully acknowledge contributions from numerous staff indirectly involved in the project, graduate students, and student workers at many locations.

Publisher Copyright:
© 2023, The Author(s).


  • Genotype by environment
  • Grain yield
  • Maize
  • Phenotype
  • Variable environments

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.


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