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Data associated with "Predicting G×E in biomass of rice: modeling method combining crop growth models and genomic prediction models" by Toda et al.

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YT100100/ReferenceData_2018_PLoSONE

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ReferenceData_2018_PLoSONE

Data associated with "Predicting G×E in biomass of rice: modeling method combining crop growth models and genomic prediction models" by Toda et al.

Contents

PhenotypeData_RILs_2014.csv / PhenotypeData_RILs_2015.csv
Phenotype data of the target RILs. Names of row and column represents each line and trait, respectively. Names of traits with numbers represents trait name and the observation date (e.g. LeafAge_0519 = Leaf age observed in 19 May). Data is separated in two files depending on the year of the field trial.

EnvironmentalData.csv
Environmental data of the field trial including date, daily average of temperature, theoretical day length and PAR (photosynthesically active radiation). Data is available from http://www.naro.affrc.go.jp/org/niaes/aws/

DVRparameter_RILs.csv
DVR parameters of the target RILs. This data was estimated with the data of 112 cultivars, containing heading-date data of multi-environment trail and marker genotypes of six heading-date-related genes 112 lines. The relationship between genotype and heading date was explained by ELM.

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Data associated with "Predicting G×E in biomass of rice: modeling method combining crop growth models and genomic prediction models" by Toda et al.

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