ArticlePlant phenomics (Washington, D.C.)2025
Integrating crop models, single nucleotide polymorphism, and climatic indices to develop genotype-environment interaction model: A case study on rice flowering time.
Article in Plant phenomics (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.The plant genome · 2026Article
- Genomic prediction vs. gene-based crop models: a case study on rice trait prediction.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
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12 authors.
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Abstract
Genotype-environment interaction (G × E) models have potential in digital breeding and crop phenotype prediction. Using genotype-specific parameters (GSPs) as a bridge, crop growth models can capture G × E and simulate plant growth and development processes. In this study, a dataset containing multi-environmental planting and flowering data for 169 genotypes, each with 700K single nucleotide polymorphism (SNP) markers was used. Three rice growth models (ORYZA, CERES-Rice, and RiceGrow), SNPs, and climatic indices were integrated for flowering time prediction. Significant associations between GSPs and quantitative trait nucleotides (QTNs) were investigated using genome-wide association study (GWAS) methods. Several GSPs were associated with previously reported rice flowering genes, including
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