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Research Project: Genetic and Physiological Mechanisms Underlying Complex Agronomic Traits in Grain Crops

Location: Plant Genetics Research

Title: Genomes to fields 2022 maize genotype by environment prediction competition

item LIMA, DAYANE - University Of Wisconsin
item Washburn, Jacob
item VARELA, JOSE - University Of Wisconsin
item CHEN, QIUYUE - North Carolina State University
item GAGE, JOSEPH - North Carolina State University
item ROMAY, MARIA - Cornell University
item Holland, Jim - Jim
item ERTL, DAVID - Iowa Corn Promotion Board
item LOPEZ-CRUZ, MARCO - Michigan State University
item AGUATE, FERNANDO - Michigan State University
item DE LOS CAMPOS, GUSTAVO - Michigan State University
item KAEPPLER, SHAWN - University Of Wisconsin
item BEISSINGER, TIMOTHY - University Of Gottingen
item BOHN, MARTIN - University Of Illinois
item Buckler, Edward - Ed
item Edwards, Jode
item Flint-Garcia, Sherry
item GORE, MICHAEL - Cornell University
item HIRSCH, CANDICE - University Of Minnesota
item Knoll, Joseph - Joe
item MCKAY, JOHN - Colorado State University
item MINYO, RICHARD - The Ohio State University
item MURRAY, SETH - Texas A&M University
item ORTEZ, OSLER - The Ohio State University
item SCHNABLE, JAMES - University Of Nebraska
item SEKHON, RAJANDEEP - Clemson University
item SINGH, MANINDER - Michigan State University
item SPARKS, ERIN - University Of Delaware
item THOMPSON, ADDIE - Michigan State University
item TUINSTRA, MITCHELL - Purdue University
item WALLACE, JASON - University Of Georgia
item WELDEKIDAN, TECLEMARIAM - University Of Delaware
item XU, WENWEI - Texas A&M University
item DE LEON, NATALIA - University Of Wisconsin

Submitted to: BMC Research Notes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/28/2023
Publication Date: 7/17/2023
Citation: Lima, D.C., Washburn, J.D., Varela, J.I., Chen, Q., Gage, J.L., Romay, M.C., Holland, J.B., Ertl, D., Lopez-Cruz, M., Aguate, F.M., De Los Campos, G., Kaeppler, S., Beissinger, T., Bohn, M., Buckler IV, E.S., Edwards, J.W., Flint Garcia, S.A., Gore, M.A., Hirsch, C.N., Knoll, J.E., Mckay, J., Minyo, R., Murray, S.C., Ortez, O.A., Schnable, J., Sekhon, R.S., Singh, M.P., Sparks, E.E., Thompson, A., Tuinstra, M., Wallace, J., Weldekidan, T., Xu, W., De Leon, N. 2023. Genomes to fields 2022 maize genotype by environment prediction competition. BMC Research Notes. 16: Article 148.

Interpretive Summary: Yield prediction across different cultivars and environmental conditions is critical to agricultural efficiency and improvement, but requires large data sets and sophisticated prediction models. This publications describes and makes publicly available a large dataset which has been purposefully created, curated, and used in a recent world-wide yield prediction competition. Making the data set available to the public will allow it to be used by researcher's, computer scientists, and hobbyists for further development of agricultural prediction solutions.

Technical Abstract: Objectives: The Genomes to Fields (G2F) 2022 Maize Genotype by Environment (G x E) Prediction Competition aimed to develop models for predicting grain yield for the 2022 Maize G x E project field trials, leveraging the datasets previously generated by this project and other publicly available data. Data description: This resource used data from the Maize G x E project within the G2F Initiative. The dataset included phenotypic and genotypic data of the hybrids evaluated in 45 locations from 2014 to 2022. Also, soil, weather, environmental covariates data and metadata information for all environments (combination of year and location). Competitors also had access to ReadMe files which described all the files provided. The Maize G x E is a collaborative project and all the data generated becomes publicly available. The dataset used in the 2022 Prediction Competition was curated and lightly filtered for quality and to ensure naming uniformity across years.