Multiparametric analysis and authentication of Argentinian vinegars from spectral sources
Ultraviolet-visible (UV-Vis) and near infrared (NIR) spectroscopies allied to chemometrics were investigated for quality control and authentication of Argentinean wine and balsamic vinegars. First, a multiparametric approach was conducted to acquire predictive models by using partial least squares r...
| Autores principales: | , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/16041 https://www.sciencedirect.com/science/article/pii/S0889157523006750 https://doi.org/10.1016/j.jfca.2023.105801 |
| _version_ | 1855485667076734976 |
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| author | Wagner, Marcelo Zaldarriaga Heredia, Jorgelina Montemerlo, Antonella Ortiz, Daniela Alejandra Camina, José Garrido, Mariano Azcarate, Silvana |
| author_browse | Azcarate, Silvana Camina, José Garrido, Mariano Montemerlo, Antonella Ortiz, Daniela Alejandra Wagner, Marcelo Zaldarriaga Heredia, Jorgelina |
| author_facet | Wagner, Marcelo Zaldarriaga Heredia, Jorgelina Montemerlo, Antonella Ortiz, Daniela Alejandra Camina, José Garrido, Mariano Azcarate, Silvana |
| author_sort | Wagner, Marcelo |
| collection | INTA Digital |
| description | Ultraviolet-visible (UV-Vis) and near infrared (NIR) spectroscopies allied to chemometrics were investigated for quality control and authentication of Argentinean wine and balsamic vinegars. First, a multiparametric approach was conducted to acquire predictive models by using partial least squares regression (PLS) to quantify total acidity, volatile acidity, fixed acidity, pH and total polyphenols that are the main quality parameters used to control products. Individual UV-Vis and NIR sensors as well as merged data were assessed. Reliability models with correlation coefficients higher than 0.99 and prediction error lesser than 2.2 were acquired for the UV-Vis data. Furthermore, a classification approach was performed on wine vinegar samples to classify them according to their acetification process. At first, the data provided by each individual sensor (UV-Vis and NIR) were separately analyzed by PLS-iscriminant analysis. Then, datasets were jointly analyzed by applying sequential and orthogonalized PLS coupled with linear discriminant analysis (SO-PLS-LDA). The overall accuracy of the fused model reached an optimal performance with a value of 0.92 in the prediction stage. Finally, according to the analysis proposed, this work reveals when it is proper to conduct a data fusion methodology. |
| format | Artículo |
| id | INTA16041 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA160412024-01-08T16:31:02Z Multiparametric analysis and authentication of Argentinian vinegars from spectral sources Wagner, Marcelo Zaldarriaga Heredia, Jorgelina Montemerlo, Antonella Ortiz, Daniela Alejandra Camina, José Garrido, Mariano Azcarate, Silvana Vinagre Control de Calidad Análisis Vinegar Quality Control Analysis Argentina Vinagre de Vino Vinagre Balsámico Análisis Multiparamétrico Ultraviolet-visible (UV-Vis) and near infrared (NIR) spectroscopies allied to chemometrics were investigated for quality control and authentication of Argentinean wine and balsamic vinegars. First, a multiparametric approach was conducted to acquire predictive models by using partial least squares regression (PLS) to quantify total acidity, volatile acidity, fixed acidity, pH and total polyphenols that are the main quality parameters used to control products. Individual UV-Vis and NIR sensors as well as merged data were assessed. Reliability models with correlation coefficients higher than 0.99 and prediction error lesser than 2.2 were acquired for the UV-Vis data. Furthermore, a classification approach was performed on wine vinegar samples to classify them according to their acetification process. At first, the data provided by each individual sensor (UV-Vis and NIR) were separately analyzed by PLS-iscriminant analysis. Then, datasets were jointly analyzed by applying sequential and orthogonalized PLS coupled with linear discriminant analysis (SO-PLS-LDA). The overall accuracy of the fused model reached an optimal performance with a value of 0.92 in the prediction stage. Finally, according to the analysis proposed, this work reveals when it is proper to conduct a data fusion methodology. Se investigaron las espectroscopias ultravioleta-visible (UV-Vis) e infrarroja cercana (NIR) aliadas a la quimiometría para control de calidad y autenticación de vinos y vinagres balsámicos argentinos. Primero, un enfoque multiparamétrico. se llevó a cabo para adquirir modelos predictivos mediante el uso de regresión de mínimos cuadrados parciales (PLS) para cuantificar el total acidez, acidez volátil, acidez fija, pH y polifenoles totales que son los principales parámetros de calidad utilizados para productos de control. Se evaluaron sensores UV-Vis y NIR individuales, así como datos combinados. Modelos de confiabilidad con coeficientes de correlación superiores a 0,99 y error de predicción inferior a 2,2 fueron adquiridos para el UV-Vis datos. Además, se realizó un enfoque de clasificación en muestras de vinagre de vino para clasificarlas según a su proceso de acetificación. Al principio, los datos proporcionados por cada sensor individual (UV-Vis y NIR) fueron analizados por separado mediante análisis discriminante PLS. Luego, los conjuntos de datos se analizaron conjuntamente aplicando secuencial y PLS ortogonalizado junto con análisis discriminante lineal (SO-PLS-LDA). La precisión general de la El modelo fusionado alcanzó un rendimiento óptimo con un valor de 0,92 en la etapa de predicción. Finalmente, según A partir del análisis propuesto, este trabajo revela cuándo es adecuado llevar a cabo una metodología de fusión de datos. EEA Anguil Fil: Wagner, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina Fil: Zaldarriaga Heredia, Jorgelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina Fil: Montemerlo, Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Química de San Luis (INQUISAL); Argentina. Universidad Nacional de San Luis. Instituto de Química de San Luis (INQUISAL); Argentina Fil: Ortiz, Daniela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina Fil: Camiña, José. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina Fil: Garrido, Mariano Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; Argentina Fil: Azcarate, Silvana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina 2023-11-28T12:58:57Z 2023-11-28T12:58:57Z 2024-01 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/16041 https://www.sciencedirect.com/science/article/pii/S0889157523006750 0889-1575 https://doi.org/10.1016/j.jfca.2023.105801 eng info:eu-repograntAgreement/INTA/2019-PE-E7-I148-001, Procesos y tecnologías sostenibles para el agregado de valor en las cadenas y regiones info:eu-repo/semantics/restrictedAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Elsevier Journal of Food Composition and Analysis 125 : 105801 (January 2024) |
| spellingShingle | Vinagre Control de Calidad Análisis Vinegar Quality Control Analysis Argentina Vinagre de Vino Vinagre Balsámico Análisis Multiparamétrico Wagner, Marcelo Zaldarriaga Heredia, Jorgelina Montemerlo, Antonella Ortiz, Daniela Alejandra Camina, José Garrido, Mariano Azcarate, Silvana Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title | Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title_full | Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title_fullStr | Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title_full_unstemmed | Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title_short | Multiparametric analysis and authentication of Argentinian vinegars from spectral sources |
| title_sort | multiparametric analysis and authentication of argentinian vinegars from spectral sources |
| topic | Vinagre Control de Calidad Análisis Vinegar Quality Control Analysis Argentina Vinagre de Vino Vinagre Balsámico Análisis Multiparamétrico |
| url | http://hdl.handle.net/20.500.12123/16041 https://www.sciencedirect.com/science/article/pii/S0889157523006750 https://doi.org/10.1016/j.jfca.2023.105801 |
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