关键词:
花生, 霉变, 出芽, 近红外光谱, Si-PLS, KNN

Abstract:

A nondestructive testing method was studied for moldy and budding peanuts by Fourier transform near infrared spectroscopy combined with K Nearest Neighbor pattern recognition method. According to the sensory characteristics of peanut and previous research experience, the samples were divided into 4 classes: normal, mild mildew, putrefactive spoilage and budding. Integrating sphere diffuse method was used for the collection of peanut spectra, the wave band was from 4 000~10 000 cm-1. Second order derivative method was applied for spectroscopy data pretreatment and Synergy Interval Partial Least Squares (Si-PLS) method was used for the spectral variables selection.  The principal components analysis (PCA) was used for the data space dimensionality reduction. Then KNN recognition model was established. The identification rates of KNN model training set and forecast set were both 98.84%. The result indicated that near infrared spectroscopy technology plus KNN method was feasible for nondestructive testing of moldy and budding peanuts with good effect.

Key words: peanuts, moldy, budding, near infrared spectroscopy, Si-PLS, KNN