{"doi":"10.5772/intechopen.93126","title":"Current Applicable DNA Markers for Marker Assisted Breeding in Rice (<i>Oryza sativa</i> L.)","abstract":"<jats:p>Rice, (Oryza sativa L.) account as the second cereal most cultivated in the world. Unfortunately, global rice production is rendered by significant number abiotic and biotic stresses. Breeding for resistant variety through conventional breeding is an economical method; generally, it takes at least 10 years to release a new rice variety. Advance technology in molecular marker had revolutionized and irreversibly changes the disciplines of plant genetic and breeding. Integration of DNA-based markers in selection process enhances the effectiveness and accuracy of conventional plant breeding. It offers a novel tool for discovering and tagging alleles and genes specifically in plant. Ubiquitous of DNA marker-trait associations for diverse crops species are available with the findings of many quantitative trait loci (QTLs) mapping studies. The linkage drags, and time-consuming in conventional breeding can minimize with the application of DNA markers in plant breeding. The utilization of DNA marker in QTL mapping, MAS and gene pyramiding has been investigated. In this chapter, we discussed the recent utilizing markers in rice breeding program against abiotic and biotic stresses. In a few decades, molecular marker assisted breeding (MAB) provide a boundless task for breeders in attaining an important impact on crop development.</jats:p>","journal":"Recent Advances in Rice Research","year":2021,"id":43332,"datarank":0.2985269881961715,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.09058283402818793,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.09058283402818793,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":3,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":206072,"name":"Mohd Rafii Yusoff","orcid":null,"position":1,"is_corresponding":false},{"id":206073,"name":"Abdul Rahim Harun","orcid":null,"position":2,"is_corresponding":false},{"id":206074,"name":"Faiz Ahmad","orcid":null,"position":3,"is_corresponding":false},{"id":206071,"name":"Nor’Aishah Hasan","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21464855","pmcid":null,"openalex_id":"https://openalex.org/W3045322599","authors":[],"funders":[],"total_grants":0,"fwci":1.3518,"citation_percentile":0.80640816,"influential_citations":0,"citation_trend":[{"year":2021,"count":1},{"year":2022,"count":2}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://www.intechopen.com/citation-pdf-url/72661","host_type":"ebook platform"},{"url":"https://doi.org/10.5772/intechopen.93126","host_type":"HYBRID"},{"url":"https://www.intechopen.com/citation-pdf-url/72661","host_type":"publisher"},{"url":"http://www.intechopen.com/download/pdf/72661","host_type":"publisher"},{"url":"http://www.intechopen.com/articles/show/title/current-applicable-dna-markers-for-marker-assisted-breeding-in-rice-oryza-sativa-l","host_type":"repository"}],"fields_of_study":["GABA and Rice Research","Genetic Mapping and Diversity in Plants and Animals","Rice Cultivation and Yield Improvement","Biology","Agricultural and Food Sciences"],"mesh_terms":[],"keywords":["Marker-assisted selection","Oryza sativa","Biology","Molecular breeding","Quantitative trait locus","Molecular marker","Abiotic component","Biotechnology","Plant breeding","Genetic marker","Abiotic stress","Selection (genetic algorithm)","Genetics","Agronomy","Gene","Computer science","Ecology"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Zero hunger"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-14T22:25:38.822296Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}