Differentiation of mezcales from four agave species using FT-MIR and multivariate statistical analysis
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)Discr...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | México |
| Institución: | Instituto Politécnico Nacional |
| Repositorio: | Redalyc-IPN |
| OAI Identifier: | oai:redalyc.org:672978747040 |
| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=672978747040 https://www.redalyc.org/journal/6729/672978747040/ https://www.redalyc.org/journal/6729/672978747040/html/ https://www.redalyc.org/journal/6729/672978747040/672978747040.epub https://www.redalyc.org/journal/6729/672978747040/movil |
| Access Level: | acceso abierto |
| Palabra clave: | Multidisciplinaria (Ciencias Naturales y Exactas) agave Mezcal spectroscopy discrimination |
| Sumario: | 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). FTMIR 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. |
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