BMC Genomic Data (May 2023)

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 Liu,
  • John 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

DOI
https://doi.org/10.1186/s12863-023-01129-2
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 4

Abstract

Read online

Abstract 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.

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