A trade-off-aware framework is proposed that links causal-allele identification, mechanism-matched editing, quantitative allele design, multidimensional phenotyping, and validation across generations, genetic backgrounds, and production-relevant environments that can guide the development of balanced, breeding-ready to...
Chae Jia, S. Han, H. Kim et al.· Plants· 0 citations
An integrated AI-to-field framework that connects target discovery, editability prediction, DNA-free editing, regeneration reprogramming, phenotypic validation, and breeding deployment into a unified soybean improvement pipeline is proposed.
H. Kim, Chae Jia, S. Han et al.· Plants· 0 citations
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