人工智能增强的作物防护对抗昆虫传播的疾病
Pingzhi Zhao1, Qiudong Xia1, Jian Ye1
1Department of Agri-microbiomics and Biotechnology, State Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China; CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, China.
Current opinion in biotechnology
|January 28, 2026
概括
人工智能 (AI) 正在彻底改变像类黄龙 (HLB) 这样的昆虫传播植物疾病的管理. 人工智能平台增强了对植物-昆虫相互作用的理解,使精确干预和疾病控制成为可能.
科学领域:
- 植物病理学 植物病理学
- 昆虫学 昆虫学是一门学科.
- 计算生物学 计算生物学
背景情况:
- 昆虫传播的病原体,包括导致类黄龙 (HLB) 和白传播的病毒性疾病的病原体,严重威胁全球农业.
- 这些病原体与宿主植物和昆虫载体进行复杂的多方相互作用,操纵宿主生理和载体行为以传播.
研究的目的:
- 审查植物防御机制对昆虫传播的病原体的最新进展.
- 探索病原体规避宿主防御的策略.
- 突出人工智能 (AI) 在加速研究和开发这些疾病的管理策略中的作用.
主要方法:
- 关于植物-病原体-昆虫相互作用和人工智能应用的当前科学文献的审查.
- 分析人工智能驱动的方法来识别耐药基因和开发新型农药.
- 检查人工智能平台用于自动化研究工作流程和假设测试.
主要成果:
- 人工智能加速了对复杂的植物-病原体-昆虫相互作用的理解.
- 人工智能有助于精确的干预,包括发现耐药基因和开发in silico农药.
- 人工智能平台可以创建合成免疫蛋白和自动化研究过程.
结论:
- 人工智能通过提供系统性见解和实现先进的控制策略,为管理昆虫传播的植物疾病提供了变革性的潜力.
- 集成的人工智能平台可以导致更有效的疾病爆发和农业流行病管理.
- 未来的研究应该专注于利用人工智能开发强大,可持续的解决方案来对抗破坏性植物疾病.
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