Abstract：Moldy peanuts are likely to contain a strong carcinogen-aflatoxin. Identifying and separating the moldy peanuts quickly can prevent aflatoxin entering the food chain at the source, and reduce the risk of human ingesting aflatoxin. The study is to determine spectral features or index models to identify moldy peanuts efficiently by spectral analysis in Visible and Near-Infrared (VIR) hyperspectral images. Totally 253 moldy peanuts samples and 247 healthy samples were selected to obtain hyperspectral images, and a mean spectrum was calculated from each peanut kernel to represent the moldy or healthy sample. The continuous continuum removal was carried out on the spectra pixel-by-pixel. The modified first-order differential with different step-length was conducted, and the index of Area500～650 was calculated among dominantly separable spectral region of 500~650 nm. Then, the continuous Wavelet transform was applied to extract the spectral information of shapes and locations. Also, the index of Indexcwt was proposed to extract mold information. Results showed that the J-M distance was 1.95 in Area500-650 and 1.99 in Indexcwt, which indicates that the performance of both Area500～650 and Indexcwt is good enough to separate the moldy peanuts from the healthy.
Key words：Moldy peanuts; Hyperspectral image; Spectral analysis; Spectral index
乔小军，蒋金豹，李 辉，亓晓彤，袁德帅. 高光谱图像识别霉变花生的光谱特征分析与指数模型构建[J]. 光谱学与光谱分析, 2018, 38(02): 535-539.
QIAO Xiao-jun, JIANG Jin-bao, LI Hui, QI Xiao-tong, YUAN De-shuai. College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 535-539.
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