FT-MIR-ATR Associated with Chemometrics Methods: A Preliminary Analysis of Deterioration State of Brazil Nut Oil
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Published:2023-09-29
Issue:19
Volume:28
Page:6878
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ISSN:1420-3049
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Container-title:Molecules
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language:en
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Short-container-title:Molecules
Author:
da Silva Braian Saimon Frota1ORCID, Ferreira Nelson Rosa23ORCID, Alamar Priscila Domingues3ORCID, de Melo e Silva Thiago1ORCID, Pinheiro Wandson Braamcamp de Souza1ORCID, dos Santos Lucely Nogueira3ORCID, Alves Cláudio Nahum1ORCID
Affiliation:
1. Graduate Program in Chemistry, Federal University of Pará (PPGQ), Belém 66075-110, Brazil 2. Faculty of Food Engineering, Institute of Technology, Federal University of Pará (UFPA), Belém 66075-110, Brazil 3. Laboratory of Biotechnological Processes (LABIOTEC), Graduate Program in Food Science and Technology (PPGCTA), Institute of Technology (ITEC), Federal University of Pará (UFPA), Belém 66075-110, Brazil
Abstract
Brazil nut oil is highly valued in the food, cosmetic, chemical, and pharmaceutical industries, as well as other sectors of the economy. This work aims to use the Fourier transform infrared (FTIR) technique associated with partial least squares regression (PLSR) and principal component analysis (PCA) to demonstrate that these methods can be used in a prior and rapid analysis in quality control. Natural oils were extracted and stored for chemical analysis. PCA presented two groups regarding the state of degradation, subdivided into super-degraded and partially degraded groups in 99.88% of the explained variance. The applied PLS reported an acidity index (AI) prediction model with root mean square error of calibration (RMSEC) = 1.8564, root mean square error of cross-validation (REMSECV) = 4.2641, root mean square error of prediction (RMSEP) = 2.1491, R2cal (calibration correlation coefficient) equal to 0.9679, R2val (validation correlation coefficient) equal to 0.8474, and R2pred (prediction correlation coefficient) equal to 0, 8468. The peroxide index (PI) prediction model showed RMSEC = 0.0005, REMSECV = 0.0016, RMSEP = 0.00079, calibration R2 equal to 0.9670, cross-validation R2 equal to 0.7149, and R2 of prediction equal to 0.9099. The physical–chemical analyses identified that five samples fit in the food sector and the others fit in other sectors of the economy. In this way, the preliminary monitoring of the state of degradation was reported, and the prediction models of the peroxide and acidity indexes in Brazil nut oil for quality control were determined.
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Pró-Reitoria de Pesquisa e Pós-Graduação/UFPA
Subject
Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science
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