Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis

Abstract

Manihot esculenta flour (MEF) is the main energetic source for a major part of the population in the Amazonian region. In this study, near-infrared spectroscopy (NIRS) was used, for the first time, to predict physicochemical parameters of MEF. The water activity (a W ), ash content, bulk density, moisture content, pH, geometric mean diameter (GMD) and colour parameters of L*, C * ab and h ab were determined for 106 samples of MEF. Calibration equations with independent validation were developed to predict all parameters using the partial least square regression method. The performance of models was evaluated by the root mean standard error of calibration (RMSEC) and validation (RMSEV), and R 2 values. The a W (RMSEC = RMSEV = 0.05), moisture content (RMSEC = 0.35%; RMSEV = 0.45%) and pH (RMSEC = 0.16; RMSEV = 0.18) could be predicted (R 2 > 0.727) by NIRS coupled to multivariate analysis. NIRS and multivariate analysis proved to be a powerful tool to predict multiple physicochemical parameters of MEF.