Turrini Federica, Zunin Paola, Boggia Raffaella
Department of Pharmacy, University of Genoa, Viale Cembrano 4, 16148 Genoa, Italy.
Foods. 2021 Jan 18;10(1):183. doi: 10.3390/foods10010183.
A comprehensive data collection of authentic "specialty" or "gourmet" oils, namely cold-pressed industrial virgin oils, was performed. Eight different botanical species, i.e., Almond, Apricot, Avocado, Hazelnut, Mosqueta rose, Rosehip, Sunflower, and Walnut oils were studied plus Olive oil as the gold standard of cold-pressed virgin oils. Two different analytical approaches are proposed to rapidly verify the botanical species of the oil-based raw material. The first approach is based on a multivariate statistical analysis of conventional analytical data, namely their fatty acid composition. These data have been re-elaborated in a multivariate way by Principal Component Analysis (PCA) and classification methods. The second approach proposes a fast and non-destructive spectrophotometric analysis to determine the color of these oils to discriminate among different species. In this regard, the raw diffuse reflectance spectra (380-780 nm) obtained by a UV-Vis spectrophotometer with an integrating sphere was considered and elaborated by chemometrics. This information was compared with the results obtained by the most common approach based on the CIELab parameters. A data fusion of chromatographic and spectral data was also investigated. Either fatty acid composition or color of these oils demonstrated to be two promising markers of their botanical authenticity.
对正宗的“特种”或“美食”油，即冷榨工业初榨油进行了全面的数据收集。研究了八种不同的植物种类，即杏仁油、杏油、鳄梨油、榛子油、玫瑰果油、玫瑰籽油、向日葵油和核桃油，另外还研究了作为冷榨初榨油金标准的橄榄油。提出了两种不同的分析方法来快速验证油基原料的植物种类。第一种方法基于对常规分析数据（即其脂肪酸组成）的多变量统计分析。这些数据已通过主成分分析（PCA）和分类方法以多变量方式重新处理。第二种方法提出了一种快速且无损的分光光度分析方法，以确定这些油的颜色，从而区分不同的种类。在这方面，考虑了用带积分球的紫外可见分光光度计获得的原始漫反射光谱（380 - 780 nm），并通过化学计量学进行处理。将该信息与基于CIELab参数的最常用方法所获得的结果进行了比较。还研究了色谱和光谱数据的融合。这些油的脂肪酸组成或颜色都证明是其植物来源真实性的两个有前景的标志物。
