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Smart Breeding: Integration and Application from High-Throughput Phenotyping to Genome Selection

  • YU Chuang-Xin ,
  • LI Jian-Qi ,
  • ZHANG Ying ,
  • HAN Dong ,
  • FANG Jing ,
  • DIAO En-Guang ,
  • HUANG Hua ,
  • DA Ling-Ling ,
  • ZHANG Ji
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  • 1College of Life Sciences, Northwest Normal University, Lanzhou 730070, China; 2Institute of New Rural Development, Northwest Normal University, Lanzhou 730070, China

Received date: 2025-08-30

  Revised date: 2025-11-14

  Online published: 2025-12-16

Abstract

With global warming and population growth accelerating, crop breeding must advance towards greater precision, efficiency and sustainability. Riding the wave of rapid AI development, AI-driven Smart Breeding has emerged as the cutting edge of plant breeding. Leveraging technologies such as high-throughput phenotyping through machine learning and deep learning, genome-wide association studies for genomic selection, and multi-omics big data analysis, it integrates and edits genetic information while linking phenotypes with genomes. This approach promises revolutionary changes in agricultural breeding, enhancing crop productivity, improving quality, and refining traits. Looking ahead, precision agriculture and personalised breeding represent key developmental trajectories. Strategies focusing on environmental adaptability and climate change mitigation will aid in addressing ecological challenges. The cutting-edge technologies of smart Breeding, significantly enhancing breeding efficiency and precision, will shape the future direction and progress of plant breeding.


Cite this article

YU Chuang-Xin , LI Jian-Qi , ZHANG Ying , HAN Dong , FANG Jing , DIAO En-Guang , HUANG Hua , DA Ling-Ling , ZHANG Ji . Smart Breeding: Integration and Application from High-Throughput Phenotyping to Genome Selection[J]. Chinese Bulletin of Botany, 0 : 1 -0 . DOI: 10.11983/CBB25155

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