ReviewFrontiers in plant science2023
Digitalizing breeding in plants: A new trend of next-generation breeding based on genomic prediction.
Review in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 57 citations in OpenAlex.
- Novel genomic regions associated with adult-plant resistance to multiple fungal pathogens in wheat (Triticum aestivum L.) revealed by DArT marker sequencing.Journal of applied genetics · 2026Article
- Integrating Genetic and Biotechnological Approaches to Enhance High-CBD Cannabis sativa L. Cultivation for Medicinal Purposes.Molecular biotechnology · 2026Review
- Ensemble-based genomic prediction for maize flowering time improves prediction accuracy and reveals novel insights into trait genetic variation.G3 (Bethesda, Md.) · 2026Article
- Review
- Genomic selection for multi-trait crop improvement in wheat (Triticum aestivum L.): a practical modeling approach.BMC plant biology · 2026Article
- Enhancing genomic prediction ability of blast resistance using genome-wide association study-derived marker weights in two rice (Oryza sativa L.) populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- AI-integrated digital breeding for crop improvement.Frontiers in plant science · 2026Review
- MAGIC populations: a next-generation framework for dissecting complex quantitative traits and accelerating molecular breeding in crops.Frontiers in plant science · 2026Review
- Article
- Improving plant breeding through AI-supported data integration.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Enhancing Genomic Prediction Accuracy of Reproduction Traits in Rongchang Pigs Through Machine Learning.Animals : an open access journal from MDPI · 2025Article
- A new approach for evaluating maize transgressive segregants and their three-way cross potential in the S4 convergent breeding population.BMC plant biology · 2025Article
- Genetic improvement of robusta coffee (Frontiers in plant science · 2025Review
- Quantifying Genetic Parameters for Blackleg Resistance in Rapeseed: A Comparative Study.Plants (Basel, Switzerland) · 2024Article
- Review
- Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress.International journal of molecular sciences · 2024Review
- The Dark Side of the pollen: BSA-seq identified genomic regions linked to male sterility in globe artichoke.BMC plant biology · 2024Article
- Application of bulk segregant RNA-Seq (BSR-Seq) and allele-specific primers to study soybean powdery mildew resistance.BMC plant biology · 2024Article
- Hybrid Rice Production: A Worldwide Review of Floral Traits and Breeding Technology, with Special Emphasis on China.Plants (Basel, Switzerland) · 2024Review
- Genome ofFrontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the world's population grows and food needs diversification, the demand for cereals and horticultural crops with beneficial traits increases. In order to meet a variety of demands, suitable cultivars and innovative breeding methods need to be developed. Breeding methods have changed over time following the advance of genetics. With the advent of new sequencing technology in the early 21st century, predictive breeding, such as genomic selection (GS), emerged when large-scale genomic information became available. GS shows good predictive ability for the selection of individuals with traits of interest even for quantitative traits by using various types of the whole genome-scanning markers, breaking away from the limitations of marker-assisted selection (MAS). In the current review, we briefly describe the history of breeding techniques, each breeding method, various statistical models applied to GS and methods to increase the GS efficiency. Consequently, we intend to propose and define the term digital breeding through this review article. Digital breeding is to develop a predictive breeding methods such as GS at a higher level, aiming to minimize human intervention by automatically proceeding breeding design, propagating breeding populations, and to make selections in consideration of various environments, climates, and topography during the breeding process. We also classified the phases of digital breeding based on the technologies and methods applied to each phase. This review paper will provide an understanding and a direction for the final evolution of plant breeding in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.