油菜蚜虫可造成油菜籽的严重减产, 及早进行油菜蚜虫判别以及其侵染定位识别有助于精准喷药。 采用可见-近红外高光谱成像技术结合图像分析对185个蚜虫侵染以及138个健康油菜角果进行判别, 并进行蚜虫的定位分析。 首先采用主成分分析法(PCA)对两类样本的平均光谱进行聚类分析, 并基于X-loading得出737 nm波段可作为判断蚜虫的重要波段, 采用Boxplot进行两类样本间单波段处的统计分析, 同时得出基于737 nm波段判断蚜虫侵染油菜角果的线性公式为y=2.917 6-3.345 7x(x为样本在737 nm处的光谱值, y为样本的分类预测值)。 采用此公式对实验样本进行判别分析, 可以发现角果蚜虫识别率为99.0%。 同时基于737 nm处的油菜角果单波段灰度图进行蚜虫的定位识别, 可以得到蚜虫的识别率为81.1%。 结果表明, 采用737 nm处的单波段光谱信息以及图像信息可进行油菜角果蚜虫侵染的定位识别, 为进一步开发便携仪检测仪以及精准喷药提供理论和方法依据。

Rape aphids can reduce the production and quality of rapeseed seriously, so early discrimination of the rape aphids and identification of the infection location are helpful for precisely spraying pesticide. In this study, hyperspectral imaging in visible and near-infrared region combined with imaging processing were employed to discriminate the healthy and aphid infected rape pods, as well as identify the location of rape aphids. Here, a total of 323 samples covering 138 healthy and 185 aphid-infected rape pods was investigated. Firstly, principal component analysis (PCA) was used to conduct the cluster analysis of the two groups rape pods, and the wavelength at 737 nm selected by X-loading was considered as an important waveband for the purpose of aphid discrimination. Then, statistical analysis of spectral data from the two groups’ samples at single band (737 nm) was finished by boxplot. At the same time, a linear equation y=2.917 6-3.345 7x (x represented the spectral data of 737 nm, y denoted the predicted dummy classes) was obtained based on above analysis. Relying on the linear equation, discriminant analysis was carried out for the 323 samples and the recognition accuracy reached 99.0%. Next, the location of rape pods was identified based on the single band grayscale images. For the infected rape pods, the method led to an overall detection accuracy of 81.1%. The results revealed that the spectral data at 737 nm and its image information is a promising tool for identifying the location of aphids in rape pods, which could provide a theoretical reference and basis for designing the handheld detection system and the precise spraying of rape industry in the further work.