RUFFINO Srl, 50065 Pontassieve, Firenze, Italy.
Department for Sustainable Process, Agricultural Faculty, Università Cattolica del Sacro Cuore of Piacenza, 29212 Piacenza, Italy.
Food Chem. 2020 Jun 15;315:126248. doi: 10.1016/j.foodchem.2020.126248. Epub 2020 Jan 21.
Chianti is a precious red wine and enjoys a high reputation for its high quality in the world wine market. Despite this, the production region is small and product needs efficient tools to protect its brands and prevent adulterations. In this sense, ICP-MS combined with chemometrics has demonstrated its usefulness in food authentication. In this study, Chianti/Chianti Classico, authentic wines from vineyard of Toscana region (Italy), together samples from 18 different geographical regions, were analyzed with the objective of differentiate them from other Italian wines. Partial Least Squares-Discriminant Analysis (PLS-DA) identified variables to discriminate wine geographical origin. Rare Earth Elements (REE), major and trace elements all contributed to the discrimination of Chianti samples. General model was not suited to distinguish PDO red wines from samples, with similar chemical fingerprints, collected in some regions. Specific classification models enhanced the capability of discrimination, emphasizing the discriminant role of some elements.
基安蒂酒是一种珍贵的红葡萄酒,在世界葡萄酒市场上以其高品质享有盛誉。尽管如此,其生产地区较小,产品需要有效的工具来保护其品牌并防止掺假。从这个意义上说,ICP-MS 结合化学计量学已证明在食品鉴定方面非常有用。在这项研究中,基安蒂/经典基安蒂(Chianti Classico)葡萄酒,来自托斯卡纳地区(意大利)的葡萄园的正宗葡萄酒,与来自 18 个不同地理区域的样本一起进行了分析,目的是将它们与其他意大利葡萄酒区分开来。偏最小二乘判别分析(PLS-DA)确定了用于区分葡萄酒地理来源的变量。稀土元素(REE)、常量和微量元素都有助于区分基安蒂葡萄酒样本。一般模型不适合区分 PDO 红葡萄酒和在某些地区收集的具有相似化学指纹的样本。特定的分类模型增强了区分能力,强调了某些元素的判别作用。