ReviewPlants (Basel, Switzerland)2022
Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane.
Review in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- From n + n to 2n + n: Unconventional Chromosome Inheritance and Stable Retention of the EntirePlants (Basel, Switzerland) · 2026Article
- Accelerating genetic gain through integrated genomic selection in crop plants.Journal of applied genetics · 2026Review
- Sugarcane Breeding in the Genomic Era: Integrative Strategies and Emerging Technologies.Plants (Basel, Switzerland) · 2026Review
- Review
- Integrative Machine Learning Approaches for Identifying Loci Associated with Anthracnose Resistance in Strawberry.Plants (Basel, Switzerland) · 2025Article
- Article
- Genomic prediction powered by multi-omics data.Frontiers in genetics · 2025Article
- Transcriptomics in solanaceous crop improvement: advances and opportunities.Frontiers in plant science · 2025Review
- Genetic dissection of nutrient element enrichment inFrontiers in plant science · 2025Article
- Identification ofAnimal biotechnology · 2024Article
- Sugarcane breeding: a fantastic past and promising future driven by technology and methods.Frontiers in plant science · 2024Article
- Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals.Genes · 2023Review
- A Genome-Wide Association Study and Genomic Prediction for Fiber and Sucrose Contents in a Mapping Population of LCP 85-384 Sugarcane.Plants (Basel, Switzerland) · 2023Article
- Comparative expression analysis ofPeerJ · 2023Article
- Genome-wide association study as a powerful tool for dissecting competitive traits in legumes.Frontiers in plant science · 2023Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder's equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement.
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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 Socratic graph.