在小麦核中检测隐藏的害虫米 (Sitophilus oryzae) 使用高光谱成像
Lei Yan1,2,3, Taoying Luo1, Chao Zhao1,2,3
1School of Food and Strategic Reserves, Henan University of Technology, Zhengzhou 450001, China.
Foods (Basel, Switzerland)
|February 13, 2026
概括
这项研究引入了一种非破坏性的高光谱成像方法,用于在小麦中检测米 (Sitophilus oryzae). 开发的模型准确地识别了受感染的谷粒,从而可以在储存的谷物中早期检测害虫.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 频谱学是一种光谱学.
背景情况:
- 像小麦这样的储存谷物容易受到诸如大米虫 (Sitophilus oryzae) 等害虫的伤害.
- 传统的检测方法难以识别内核内隐藏的昆虫生命阶段.
- 早期和非破坏性检测对于防止重大作物损失至关重要.
研究的目的:
- 开发一种非破坏性的方法来检测小麦核中的Sitophilus oryzae感染.
- 为了优化高光谱成像,光谱预处理和分类模型用于害虫检测.
- 评估开发的检测模型的准确性和稳定性.
主要方法:
- 超光谱成像用于收集各种感染阶段的健康和S. oryzae感染的小麦粒的数据.
- 使用SG平滑,乘数散射校正 (MSC) 和标准正常变量转换 (SNV) 预处理了光谱数据.
- 使用特征提取 (CARS,SPA,IRIV) 和分类 (DT,KNN,SVM) 模型来识别受感染的核.
主要成果:
- 多倍散射校正 (MSC) 预处理增强了模型性能.
- 在MSC-CARS-SVM模型中,在早期和晚期的感染阶段实现了高精度 (高达96.61%).
- 在MSC-IRIV-SPA-SVM模型中,对于中间感染阶段,表现强 (高达94.92%).
结论:
- 超光谱成像,结合优化预处理和特征选择,是用于在小麦中非破坏性检测S. oryzae的可行方法.
- 开发的模型为在储存的谷物中早期检测害虫提供了更高的准确性和稳定性.
- 这项技术为先进的,非侵入性的存储产品害虫监测提供了基础.
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