Abstract

Digital breeding integrates modern technologies like genomics, bioinformatics, and data analytics into conventional plant breeding. It accelerates the breeding process, improves selection effectiveness, and enhances crop yield and quality. High-throughput genotyping and phenotyping technologies enable efficient analysis of large populations and rapid characterization of plant traits. Genomic selection and data analytics aid in predicting breeding values and analyzing extensive data for trait improvement. Digital breeding applications include accelerated breeding cycles, trait-based breeding, disease resistance, stress tolerance, nutritional quality enhancement, remote sensing, yield prediction, multi-environment testing, and precision breeding and prospects involve integrating multiple omics technologies, developing precise phenotypic prediction models, and fostering data sharing and collaboration. Digital breeding can greatly improve breeding programs and address global food security challenges.Digital breeding integrates modern technologies like genomics, bioinformatics, and data analytics into conventional plant breeding. It accelerates the breeding process, improves selection effectiveness, and enhances crop yield and quality. High-throughput genotyping and phenotyping technologies enable efficient analysis of large populations and rapid characterization of plant traits. Genomic selection and data analytics aid in predicting breeding values and analyzing extensive data for trait improvement. Digital breeding applications include accelerated breeding cycles, trait-based breeding, disease resistance, stress tolerance, nutritional quality enhancement, remote sensing, yield prediction, multi-environment testing, and precision breeding and prospects involve integrating multiple omics technologies, developing precise phenotypic prediction models, and fostering data sharing and collaboration. Digital breeding can greatly improve breeding programs and address global food security challenges.

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