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Fast and non‐destructive determination of simultaneous physicochemical parameters of Manihot esculenta flour using FT‐NIR spectroscopy and multivariate analysis
Author(s) -
Pompeu Darly R.,
Souza Jesus N.S.,
Pena Rosinelson S.
Publication year - 2021
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/ijfs.14998
Subject(s) - multivariate statistics , calibration , manihot esculenta , partial least squares regression , near infrared spectroscopy , spectroscopy , analytical chemistry (journal) , chemistry , multivariate analysis , water content , mathematics , chromatography , statistics , botany , physics , biology , optics , quantum mechanics , geotechnical engineering , engineering
Summary 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.