Artificial intelligence in plant breeding

文献类型： 外文期刊

第一作者： Farooq, Muhammad Amjad

作者： Farooq, Muhammad Amjad;Gao, Shang;Huang, Zhangping;Li, Xinhai;Li, Huihui;Farooq, Muhammad Amjad;Gao, Shang;Huang, Zhangping;Li, Huihui;Hassan, Muhammad Adeel;Hassan, Muhammad Adeel;Rasheed, Awais;Hearne, Sarah;Prasanna, Boddupalli

作者机构：

期刊名称：TRENDS IN GENETICS （ 影响因子：16.3； 五年影响因子：13.7 ）

ISSN： 0168-9525

年卷期： 2024 年 40 卷 10 期

页码：

收录情况： SCI

摘要： 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.

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