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斯洛伐克托卡伊葡萄酒基于产地的单类方法分类。

Slovak Tokaj wines classification with respect to geographical origin by means of one class approaches.

作者信息

Gomes Adriano A, Khvalbota Liudmyla, Machyňáková Andrea, Furdíková Katarína, Zini Claudia A, Špánik Ivan

机构信息

Instituto de Química, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves, 9500, 91501-970 Porto Alegre, RS, Brazil.

Institute of Analytical Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37 Bratislava, Slovakia.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2021 Aug 5;257:119770. doi: 10.1016/j.saa.2021.119770. Epub 2021 Apr 1.

Abstract

Tokaj wines could be produced only in so called Tokaj/Tokay wine region that falls within two countries Slovakia and Hungary. Thus, wines bearing Tokaj appellation must be produced only in Hungary and Slovakia by traditional process. Unfortunately, some counterfeit wines from neighbour region in Ukraine could be found in market. The aim of this work is to explore a simple UV-VIS spectrum to recognise true Tokaj/Tokay wines from counterfeits and try to differentiate wines based on their country of origin. This type of question can be duly answered using one class classification approach. Two different approaches, Data Driven Soft Independent Modelling of Class Analogy - DD-SIMCA and One-Class Partial Least Squares - OC-PLS were tested and evaluated for this purpose. In both cases, rigorous way models were built and optimized using only samples of the target class. A set of external samples containing samples from target class and non-target were used to validate the models ability to recognize Slovak samples and reject non-Slovak samples. Model based on DD-SIMCA showed better performance (97% correct rating) compared to OC-PLS models (80% correct rating). Comparing both approaches in terms of sensitivity and specificity, both exhibit high sensitivity (low false negative rate: DD-SIMCA 95% and OC-PLS 100%), however the OC-PLS based model showed low specificity (40%) while DD-SIMCA showed high specificity (100%) rejecting all samples out of Slovak origin. Therefore, the results found in this study show that it is possible to successfully combine UV-VIS spectra and DD-SIMCA models to discriminate Tokaj wine samples of Slovak origin from others. Equally important is environmentally friendly (fast, simple, absence of solvents) classification method in line with green chemistry.

摘要

托卡伊葡萄酒只能在斯洛伐克和匈牙利这两个国家境内的所谓托卡伊/托凯葡萄酒产区生产。因此,带有托卡伊 appellation 的葡萄酒必须仅在匈牙利和斯洛伐克采用传统工艺生产。不幸的是,市场上能发现一些来自乌克兰邻近地区的假冒葡萄酒。这项工作的目的是探索一种简单的紫外可见光谱,以从假冒品中识别出真正的托卡伊/托凯葡萄酒,并尝试根据其原产国对葡萄酒进行区分。这类问题可以使用单类分类方法得到恰当解答。为此测试并评估了两种不同的方法,即数据驱动的类分析软独立建模 - DD - SIMCA 和单类偏最小二乘法 - OC - PLS。在这两种情况下,仅使用目标类别的样本构建并优化严格的模型。一组包含目标类和非目标类样本的外部样本用于验证模型识别斯洛伐克样本并拒绝非斯洛伐克样本的能力。与 OC - PLS 模型(正确评级为 80%)相比,基于 DD - SIMCA 的模型表现更好(正确评级为 97%)。从灵敏度和特异性方面比较这两种方法,两者都具有高灵敏度(低假阴性率:DD - SIMCA 为 95%,OC - PLS 为 100%),然而基于 OC - PLS 的模型显示出低特异性(40%),而 DD - SIMCA 显示出高特异性(100%),拒绝所有非斯洛伐克原产的样本。因此,本研究的结果表明,可以成功地将紫外可见光谱和 DD - SIMCA 模型结合起来,以区分斯洛伐克原产的托卡伊葡萄酒样本与其他样本。同样重要的是符合绿色化学的环保(快速、简单、无溶剂)分类方法。

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