Estimation of Starch Hydrolysis in Sweet Potato (Beni Haruka) Based on Storage Period Using Nondestructive Near-Infrared Spectrometry

Sweet potatoes are a substantial source of nutrition and can be added to processed foods in the form paste. The moisture starch contents these affect physicochemical properties sweet potato In this study, changes moisture, starch, ?-amylase content were measured for eight weeks after harvest. Using nondestructive near-infrared analyses chemometric models, predicted. partial least squares (PLS) method was used prediction, while linear discriminant analysis (LDA) discrimination. To increase accuracy model, spectrum preprocessed using Savitzky–Golay derivative (S–G), standard normal variate (SNV), multiplicative scattering correction methods. When applying PLS content, best calibration model obtained S–G spectrum. Furthermore, SNV categorized into five classes LDA, with results indicating that internal quality predicted classified models through detection.