人工智能辅助培育植物抗病能力
Juan Ma1, Zeqiang Cheng1, Yanyong Cao1
1Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China.
International journal of molecular sciences
|June 13, 2025
概括
人工智能 (AI) 彻底改变了对抗疾病的植物育种. 深度学习和大型模型增强了疾病检测和奥米克预测,加速了弹性作物的发展.
科学领域:
- 植物科学 植物科学
- 计算生物学 计算生物学
- 遗传学和繁殖 遗传学和繁殖
背景情况:
- 提高作物抗病能力对于全球粮食安全至关重要.
- 传统的育种方法在有效开发耐药品种方面面临挑战.
- 像人工智能这样的新兴技术为增强植物弹性提供了新的途径.
研究的目的:
- 审查人工智能的进展,以检测植物疾病和预测耐药性.
- 探索深度学习,大型语言模型和植物科学中的多模式模型的潜力.
- 提供关于将人工智能整合到植物育种计划中以获得抗病能力的见解.
主要方法:
- 对最近关于人工智能在植物疾病检测方面的研究进行了图书统计分析,重点关注卷积神经网络.
- 对大型语言模型和多模式模型的审查,用于从异质数据中解释复杂的疾病模式.
- 探索人工智能在基因组和现象选择中对抗性相关特征的应用.
主要成果:
- 人工智能,特别是深度学习,显著提高了植物疾病检测能力.
- 大型语言和多模式模型在分析复杂的多来源植物健康数据方面表现有前途.
- 人工智能加速了基因组和现象选择的高通量分析,有助于预测抗病表型.
结论:
- 人工智能集成对于开发抗病作物具有变革性.
- 未来的方向包括解决数据,模型和隐私挑战,可能通过联合学习.
- 本综述是应用人工智能的指南,以加快作物育种以提高抗病能力.
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