Herrero-Latorre Carlos, Barciela-García Julia, García-Martín Sagrario, Peña-Crecente Rosa M
IAA-Institute for Food Analysis and Research, Dpto. Química Analítica, Nutrición y Bromatología, Facultad de Ciencias, Universidade de Santiago de Compostela, Lugo, Spain.
Food Chem X. 2019 Jul 5;3:100046. doi: 10.1016/j.fochx.2019.100046. eCollection 2019 Sep 30.
A method has been developed to authenticate aged high-quality wines and to quantify their potential adulterations through multivariate analysis and regression techniques applied to the obtained RGB digital images. Wines of pure , , and Rioja as well as synthetic adulterated samples were studied. Digital images were obtained by a single and inexpensive lab-made device. Each sample was characterized by means of the 256 channels intensities from the RGB-colorgram. Multivariate image analysis revealed differences among the wine classes, and between genuine-aged and adulterated samples. Partial least squares regression was used to develop a model for estimating the adulteration degree of wines. The model achieved good prediction (RMSEP = 1.6), appropriate precision (RSD = 2.5%) and suitable LOD (2.3%) to quantify cost-effective adulterations. The present method, due to simplicity and low cost, could provide an appropriate alternative to the traditional chemical authentication methods.
已开发出一种方法，通过对获取的RGB数字图像应用多变量分析和回归技术，来鉴定陈年优质葡萄酒并量化其潜在掺假情况。研究了纯的、、里奥哈葡萄酒以及合成掺假样品。数字图像由一个简单且成本低廉的实验室自制设备获取。每个样品通过RGB色图的256个通道强度进行表征。多变量图像分析揭示了葡萄酒类别之间以及正品陈年葡萄酒和掺假样品之间的差异。使用偏最小二乘回归建立了一个用于估计葡萄酒掺假程度的模型。该模型在量化具有成本效益的掺假方面实现了良好的预测（RMSEP = 1.6）、适当的精度（RSD = 2.5%）和合适的检测限（2.3%）。由于方法简单且成本低廉，本方法可为传统化学鉴定方法提供合适的替代方案。
