Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by environmental covariables' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agricultural research","Days to Flowering","Days to Heading","Days to Maturity","Grain yield","Plant height","Triticum aestivum","Wheat"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by environmental covariables' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by environmental covariables
Agricultural research; Days to Flowering; Days to Heading; Days to Maturity; Grain yield; Plant height; Triticum aestivum; Wheat