Artificial intelligence in plant breeding.

Journal: Trends in genetics : TIG
Published Date: Aug 7, 2024

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.

Authors

  • Muhammad Amjad Farooq
    State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), International Maize and Wheat Improvement Center (CIMMYT) China office, Beijing 100081, China; Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China.
  • Shang Gao
    Department of Orthopedics, Orthopedic Center of Chinese PLA, Southwest Hospital, Third Military Medical University, Chongqing, 400038, P.R.China.
  • Muhammad Adeel Hassan
    Adaptive Cropping Systems Laboratory, Beltsville Agricultural Research Center, US Department of Agriculture, Beltsville, MD 20705, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, USA.
  • Zhangping Huang
    State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.
  • Awais Rasheed
    Department of Plant Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan.
  • Sarah Hearne
    CIMMYT, KM 45 Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico.
  • Boddupalli Prasanna
    CIMMYT, International Centre for Research in Agroforestry (ICRAF) House, Nairobi 00100, Kenya.
  • Xinhai Li
    State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), International Maize and Wheat Improvement Center (CIMMYT) China office, Beijing 100081, China.
  • Huihui Li
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: 29777562@qq.com.

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