{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["16"],"submitter":["Ni Z"],"pubmed_abstract":["With the global population explosion, the increasing demand in food supply pushes the development of advanced breeding methods. This study presents a bi-stage data-driven and process-based crop model to provide breeding recommendations based on Genotype x Environment (GxE) effects for sorghum, a vital cereal crop with various plant types, such as Grain (G), Forage (F), Dual Purpose (DP), and Photoperiod-Sensitive (PS). The model combines traditional process-based crop modeling with explainable data-driven methods, which increases the general interpretability and flexibility of the model. The model considers extensive environmental data, including seven years of hourly weather records and soil factors from three research farms in Iowa, together with management practices and parental informa"],"journal":["Frontiers in plant science"],"pagination":["1617753"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12823968"],"repository":["biostudies-literature"],"pubmed_title":["A bi-stage data-driven process-based model for sorghum breeding and yield prediction: coupling explainable artificial intelligence and crop modeling."],"pmcid":["PMC12823968"],"pubmed_authors":["Ni Z","Salas-Fernandez MG","Kemp J","Chang Y","Wang L"],"additional_accession":[]},"is_claimable":false,"name":"A bi-stage data-driven process-based model for sorghum breeding and yield prediction: coupling explainable artificial intelligence and crop modeling.","description":"With the global population explosion, the increasing demand in food supply pushes the development of advanced breeding methods. This study presents a bi-stage data-driven and process-based crop model to provide breeding recommendations based on Genotype x Environment (GxE) effects for sorghum, a vital cereal crop with various plant types, such as Grain (G), Forage (F), Dual Purpose (DP), and Photoperiod-Sensitive (PS). The model combines traditional process-based crop modeling with explainable data-driven methods, which increases the general interpretability and flexibility of the model. The model considers extensive environmental data, including seven years of hourly weather records and soil factors from three research farms in Iowa, together with management practices and parental informa","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-06T03:19:48.178Z","creation":"2026-06-06T03:10:30.47Z"},"accession":"S-EPMC12823968","cross_references":{"pubmed":["41584661"],"doi":["10.3389/fpls.2025.1617753"]}}