Revolutionizing Crop Breeding: Next-Generation Artificial Intelligence and Big Data-Driven Intelligent Design
文献类型: 外文期刊
第一作者: Zhang, Ying
作者: Zhang, Ying;Guo, Xinyu;Zhao, Chunjiang;Huang, Guanmin;Lu, Xianju;Wang, Yanru;Wang, Chuanyu;Zhang, Ying;Guo, Xinyu;Zhao, Chunjiang;Huang, Guanmin;Lu, Xianju;Wang, Yanru;Wang, Chuanyu;Zhang, Ying;Guo, Xinyu;Zhao, Chunjiang;Huang, Guanmin;Lu, Xianju;Wang, Yanru;Wang, Chuanyu;Zhao, Yanxin
作者机构:
关键词: Crop breeding; Next-generation artificial intelligence; Multiomics big data; Intelligent design breeding
期刊名称:ENGINEERING ( 影响因子:11.6; 五年影响因子:13.1 )
ISSN: 2095-8099
年卷期: 2025 年 44 卷
页码:
收录情况: SCI
摘要:
The security of the seed industry is crucial for ensuring national food security. Currently, developed countries in Europe and America, along with international seed industry giants, have entered the Breeding 4.0 era. This era integrates biotechnology, artificial intelligence (AI), and big data information technology. In contrast, China is still in a transition period between stages 2.0 and 3.0, which primarily relies on conventional selection and molecular breeding. In the context of increasingly complex international situations, accurately identifying core issues in China's seed industry innovation and seizing the frontier of international seed technology are strategically important. These efforts are essential for ensuring food security and revitalizing the seed industry. This paper systematically analyzes the characteristics of crop breeding data from artificial selection to intelligent design breeding. It explores the applications and development trends of AI and big data in modern crop breeding from several key perspectives. These include high- throughput phenotype acquisition and analysis, multiomics big data database and management system construction, AI-based multiomics integrated analysis, and the development of intelligent breeding software tools based on biological big data and AI technology. Based on an in-depth analysis of the current status and challenges of China's seed industry technology development, we propose strategic goals and key tasks for China's new generation of AI and big data-driven intelligent design breeding. These suggestions aim to accelerate the development of an intelligent-driven crop breeding engineering system that features large-scale gene mining, efficient gene manipulation, engineered variety design, and systematized biobreeding. This study provides a theoretical basis and practical guidance for the development of China's seed industry technology.
(c) 2024 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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