Positive effects of public breeding on US rice yields under future climate scenarios.

ABSTRACT: In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from h

SUBMITTER: Wang DR 

PROVIDER: S-EPMC10990131 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature