%A %T College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China %0 Journal Article %D 2018 %J SPECTROSCOPY AND SPECTRAL ANALYSIS %R 10.3964/j.issn.1000-0593(2018)02-0535-05 %P 535-539 %V 38 %N 02 %U {https://www.gpxygpfx.com/CN/abstract/article_9659.shtml} %8 2018-02-01 %X 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.