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使用多维荧光和化学计量学对西班牙受保护原产地名称(PDO)葡萄酒醋进行表征与认证

Characterization and authentication of Spanish PDO wine vinegars using multidimensional fluorescence and chemometrics.

作者信息

Ríos-Reina Rocío, Elcoroaristizabal Saioa, Ocaña-González Juan A, García-González Diego L, Amigo José M, Callejón Raquel M

机构信息

Área de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, C/P. García González n°2, E-41012 Sevilla, Spain.

Chemical and Environmental Engineering Department, Faculty of Engineering, University of the Basque Country, Alameda de Urquijo s/n, E-48013 Bilbao, Spain.

出版信息

Food Chem. 2017 Sep 1;230:108-116. doi: 10.1016/j.foodchem.2017.02.118. Epub 2017 Feb 27.

Abstract

This work assesses the potential of multidimensional fluorescence spectroscopy combined with chemometrics for characterization and authentication of Spanish Protected Designation of Origin (PDO) wine vinegars. Seventy-nine vinegars of different categories (aged and sweet) belonging to the Spanish PDOs "Vinagre de Jerez", "Vinagre de Montilla-Moriles" and "Vinagre de Condado de Huelva", were analyzed by excitation-emission fluorescence spectroscopy. A visual assessment of fluorescence landscapes pointed out different trends with vinegar categories. PARAllel FACtor analysis (PARAFAC) extracted the potential fluorophores and their values in the PDO vinegars. This information, coupled with different classification methods (Partial Least Square Discrimination Analysis "PLS-DA" and Support Vectors Machines "SVM"), was able to discriminate the wine vinegar category within each PDO, for which SVM models obtained better results (>92% of classification). In each category, SVM also allows the differentiation between PDOs. The proposed methodology could be used as an analysis method for the authentication of Spanish PDO wine vinegars.

摘要

这项工作评估了多维荧光光谱结合化学计量学用于西班牙受保护原产地名称(PDO)葡萄酒醋的表征和认证的潜力。通过激发-发射荧光光谱对属于西班牙PDO“赫雷斯醋”、“蒙蒂利亚-莫里莱斯醋”和“韦尔瓦侯爵领地醋”的79种不同类别(陈酿和甜型)的醋进行了分析。对荧光图谱的视觉评估指出了不同醋类别的不同趋势。平行因子分析(PARAFAC)提取了PDO醋中的潜在荧光团及其值。这些信息与不同的分类方法(偏最小二乘判别分析“PLS-DA”和支持向量机“SVM”)相结合,能够区分每个PDO内的葡萄酒醋类别,其中SVM模型取得了更好的结果(分类率>92%)。在每个类别中,SVM还能区分不同的PDO。所提出的方法可作为西班牙PDO葡萄酒醋认证的分析方法。

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