Differentiation of mezcales from four agave species using FT-MIR and multivariate statistical analysis
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Published:2024-05-02
Issue:
Volume:26
Page:293-305
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ISSN:1665-1456
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Container-title:Biotecnia
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language:
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Short-container-title:BIOTECNIA
Author:
López Aguilar Rosa,Hernández Núñez Emanuel,Hernández Montes Arturo,Zuleta Prada Holber,Herbert Pucheta José Enrique
Abstract
Fourier Transform Mid-Infrared (FT-MIR) spectroscopy and multivariate statistical analysis were used to differentiate mezcales elaborated with four agave species. The FT-MIR data matrix was subjected to spectral transformations using first and second derivatives. The Partial Least Squares (PLS)-Discriminant Analysis (DA) with the matrix transformed by the first and second derivative allowed the differentiation of mezcales. While Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was more robust when it was analyzed with second-derivative data. Pairwise comparisons by OPLS-DA allowed mezcales to be correctly discriminated, mainly between Agave karwinskii and Agave potatorum (Q2 = 0.654 and p – value < 0.01; R2Y = 0.985 and p-value < 0.01) and between Agave angustifolia and Agave karwinskii (Q2 = 0.563 and p-value = 0.01; R2Y = 0.989 and p-value = 0.01). FT-MIR spectrophotometry and the PLS-Regression (PLS-R) were applied to predict the ethanol percentage (% v/v) of mezcales collected in 2022 based on the PLS-R model previously run on samples evaluated in 2021.
Publisher
Universidad de Sonora
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