Detection of crystalline taro abnormalities using two near-infrared (NIR) wavelengths

Crystalline taro anomality, which arises up to 50 %, is characterized by high water content. In pouch products factory, these abnormal taros are removed manually with a lot of labor, thus a nondestructive method for its detection is highly needed. In this study, we used near-infrared spectroscopy (700–1,300 nm) to discriminate crystalline taro. A correlation analysis and multivariate analysis (PCA and SVM) were employed to select wavelength(s) and develop a discrimination model. As a result, normal and crystalline taros showed spectra with features at around 700 and 980 nm. The SVM model showed an accuracy rate of 72 %. This study is important since in factories at most 70 % of labor reduction could be expected in future.