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Genomes to Fields 2022 Maize genotype by Environment Prediction Competition.

Dayane Cristina LimaJacob D WashburnJosé Ignacio VarelaQiuyue ChenJoseph L GageMaria Cinta RomayJames B HollandMaria Cinta RomayMarco Lopez-CruzFernando M AguateGustavo de Los CamposShawn M KaepplerTimothy M BeissingerMartin O BohnEdward S BucklerJode W EdwardsSherry A Flint-GarciaMichael A GoreCandice N HirschJoseph E KnollJohn K McKayRichard MinyoSeth C MurrayOsler A OrtezRajandeep S SekhonRajandeep S SekhonManinder P SinghAddie M ThompsonMitchell R TuinstraMitchell TuinstraTeclemariam WeldekidanTeclemariam WeldekidanNatalia de LeonNatalia de Leon
Published in: BMC research notes (2023)
This resource used data from the Maize GxE project within the G2F Initiative [1]. 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 GxE is a collaborative project and all the data generated becomes publicly available [2]. The dataset used in the 2022 Prediction Competition was curated and lightly filtered for quality and to ensure naming uniformity across years.
Keyphrases
  • quality improvement
  • electronic health record
  • big data
  • magnetic resonance imaging
  • risk assessment
  • human health
  • climate change
  • artificial intelligence