NIR spectroscopy and chemometrics for the typification of Spanish wine vinegars with a protected designation of origin

NIR spectroscopy and chemometrics for the typification of Spanish wine vinegars with a protected... High-quality wine vinegars protected by the indication “Protected Designation of Origin” (PDO) need efficient tools to protect their brands and prevent adulteration and unfair competition. In this sense, Near-Infrared spectroscopy (NIRs) combined with chemometrics has demonstrated its usefulness in food authentication. This work assessed NIRs and Chemometrics as a rapid and non-destructive methodology for this purpose. In this study, 83 high-quality wine vinegars of the Spanish PDOs “Vinagre de Jerez”, “Vinagre de Condado de Huelva” and “Vinagre de Montilla-Moriles” of different categories, and 11 wine vinegars without PDO, were analyzed in the range 12000-4000 cm−1. Principal component analysis (PCA) was performed to explore the spectra and Partial Least Squares-Discriminant Analysis (PLS-DA) was used to build classification models. The high ability of prediction obtained (>90% correct classification) demonstrated the usefulness of this methodology for authentication of PDO wine vinegars and their categories. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Food Control Elsevier

NIR spectroscopy and chemometrics for the typification of Spanish wine vinegars with a protected designation of origin

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0956-7135
eISSN
1873-7129
D.O.I.
10.1016/j.foodcont.2018.01.031
Publisher site
See Article on Publisher Site

Abstract

High-quality wine vinegars protected by the indication “Protected Designation of Origin” (PDO) need efficient tools to protect their brands and prevent adulteration and unfair competition. In this sense, Near-Infrared spectroscopy (NIRs) combined with chemometrics has demonstrated its usefulness in food authentication. This work assessed NIRs and Chemometrics as a rapid and non-destructive methodology for this purpose. In this study, 83 high-quality wine vinegars of the Spanish PDOs “Vinagre de Jerez”, “Vinagre de Condado de Huelva” and “Vinagre de Montilla-Moriles” of different categories, and 11 wine vinegars without PDO, were analyzed in the range 12000-4000 cm−1. Principal component analysis (PCA) was performed to explore the spectra and Partial Least Squares-Discriminant Analysis (PLS-DA) was used to build classification models. The high ability of prediction obtained (>90% correct classification) demonstrated the usefulness of this methodology for authentication of PDO wine vinegars and their categories.

Journal

Food ControlElsevier

Published: Jul 1, 2018

References

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