Artificial intelligence in plant breeding

被引：48

作者：

Farooq, Muhammad Amjad ^{[1
,2
]}

Gao, Shang ^{[1
,2
]}

Hassan, Muhammad Adeel ^{[3
,4
]}

Huang, Zhangping ^{[1
,2
]}

Rasheed, Awais ^{[5
]}

Hearne, Sarah ^{[6
]}

Prasanna, Boddupalli ^{[7
]}

Li, Xinhai ^{[1
]}

Li, Huihui ^{[1
,2
]}

机构：

[1] Chinese Acad Agr Sci CAAS, Inst Crop Sci, Int Maize & Wheat Improvement Ctr CIMMYT China Off, State Key Lab Crop Gene Resources & Breeding, Beijing 100081, Peoples R China

[2] CAAS, Nanfan Res Inst, Sanya 572024, Hainan, Peoples R China

[3] USDA, Beltsville Agr Res Ctr, Adapt Cropping Syst Lab, Beltsville, MD 20705 USA

[4] Oak Ridge Inst Sci & Educ, Oak Ridge, TN 37830 USA

[5] Quaid I Azam Univ, Dept Plant Sci, Islamabad 45320, Pakistan

[6] CIMMYT, KM 45 Carretera Mexico Veracruz El Batan, Texcoco 56237, Mexico

[7] Int Ctr Res Agroforestry ICRAF House, CIMMYT, Nairobi 00100, Kenya

来源：

TRENDS IN GENETICS | 2024年 / 40卷 / 10期

基金：

中国国家自然科学基金;

关键词：

POPULATION-GENETICS; ASSISTED PREDICTION; NETWORK ANALYSIS; OPEN CHROMATIN; PHENOMICS; PLATFORM; SYSTEM; REGRESSION; GENES;

D O I：

10.1016/j.tig.2024.07.001

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

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.

引用

页码：891 / 908

页数：18

共 149 条

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