Muhammad Amjad Farooq, Shang Gao, Muhammad Adeel Hassan, Zhangping Huang, Awais Rasheed, Sarah Hearne, Boddupalli Prasanna, Xinhai Li, Huihui Li
{"title":"Artificial intelligence in plant breeding.","authors":"Muhammad Amjad Farooq, Shang Gao, Muhammad Adeel Hassan, Zhangping Huang, Awais Rasheed, Sarah Hearne, Boddupalli Prasanna, Xinhai Li, Huihui Li","doi":"10.1016/j.tig.2024.07.001","DOIUrl":null,"url":null,"abstract":"<p><p>Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.</p>","PeriodicalId":54413,"journal":{"name":"Trends in Genetics","volume":" ","pages":"891-908"},"PeriodicalIF":13.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tig.2024.07.001","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/7 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.
期刊介绍：
Launched in 1985, Trends in Genetics swiftly established itself as a "must-read" for geneticists, offering concise, accessible articles covering a spectrum of topics from developmental biology to evolution. This reputation endures, making TiG a cherished resource in the genetic research community. While evolving with the field, the journal now embraces new areas like genomics, epigenetics, and computational genetics, alongside its continued coverage of traditional subjects such as transcriptional regulation, population genetics, and chromosome biology.
Despite expanding its scope, the core objective of TiG remains steadfast: to furnish researchers and students with high-quality, innovative reviews, commentaries, and discussions, fostering an appreciation for advances in genetic research. Each issue of TiG presents lively and up-to-date Reviews and Opinions, alongside shorter articles like Science & Society and Spotlight pieces. Invited from leading researchers, Reviews objectively chronicle recent developments, Opinions provide a forum for debate and hypothesis, and shorter articles explore the intersection of genetics with science and policy, as well as emerging ideas in the field. All articles undergo rigorous peer-review.
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