新型植物病检测技术 - - 一个简短的回顾
Srividya Attaluri1, Rathnaprabha Dharavath2
1National Institute of Technology, Warangal, Telangana, India. vidya.attaluri@gmail.com.
Molecular biology reports
|October 12, 2023
概括
植物疾病的早期检测对农业至关重要. 本综述涵盖了先进的方法,如光谱学和人工智能辅助的图像处理,用于快速,非侵入性的病原体识别,提高作物产量.
科学领域:
- 农业科学 农业科学
- 植物病理学 植物病理学
- 生物技术是生物技术.
背景情况:
- 植物疾病导致全球农业的重大损失.
- 传统的视觉侦察仅限于无症状的疾病检测.
- 需要快速,非侵入性和现场植物疾病检测方法.
研究的目的:
- 审查当前和新兴的植物疾病检测技术.
- 要突出光谱学,生物传感器和人工智能辅助方法的进步.
- 讨论转向对早期病原体检测的照顾点设备的转变.
主要方法:
- 对酶相关免疫吸收试验 (ELISA),侧流试验 (LFA),聚合酶连锁反应 (PCR) 的审查.
- 探索用于直接检测的光谱技术和生物传感器.
- 分析用于疾病识别的图像处理中的人工智能 (AI) 和神经网络.
主要成果:
- 既有方法 (ELISA,PCR) 是敏感的,但费力和耗时.
- 光谱技术和生物传感器提供了快速,非侵入性的检测潜力.
- 人工智能支持的图像分析显示,对早期和高效的疾病诊断有很大的希望.
结论:
- 越来越多的需求是现场适应性,点的护理诊断设备.
- 人工智能和先进的成像技术正在彻底改变植物疾病的早期检测.
- 整合这些技术可以显著减少作物损失和经济影响.
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