One of the most important challenges in the authentication of olive oil is the determination of the geographical origin of virgin olive oil. In this work, we evaluated the capacity of two spectroscopic techniques, UV-Visible and ATR-FTMIR, coupled with chemometric tools to determine the geographical origin of olive oils. These analytical approaches have been applied to samples that have been collected during the period of olive oil production, in the Moroccan region of Beni Mellal-Khenifra. To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. The application of the PCA-LDA method on the spectral data of UV-Visible and ATR-FTMIR shows a good ability to classify olive oils according to their geographical origin with a percentage of correct classification that represents 90.24% and 85.87%, respectively, and the processing of the spectral data of UV-Visible and ATR-FTMIR by PCA-SVM allows differentiating correctly between five olive oils with a correct classification rate of 100% and 97.56, respectively. This study demonstrated the feasibility of UV-Visible and ATR-FTMIR fingerprinting (routine technique) for the geographical classification of olive oils in the Moroccan region of Beni Mellal-Khenifra. Such developed methods can be proposed as alternative and complementary methods to authenticate the geographical origin of virgin olive oil.

中文翻译：

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水平ATR-FTMIR和紫外-可见光谱法在区分贝尼·梅拉尔-凯尼夫拉摩洛哥地区的初榨橄榄油中的能力评估

橄榄油认证中最重要的挑战之一是确定原始橄榄油的地理来源。在这项工作中，我们评估了两种光谱技术（UV-Visible和ATR-FTMIR）的能力以及化学计量工具来确定橄榄油的地理来源。这些分析方法已应用于在贝尼·梅拉尔-克尼夫拉（Beni Mellal-Khenifra）摩洛哥地区橄榄油生产期间收集的样品。为了开发一种能够鉴定来自贝尼梅拉尔-赫尼夫拉（Beni Mellal-Khenifra）摩洛哥地区五个地理区域的原始橄榄油的地理来源的快速分析工具，通过化学计量学算法处理了UV-Visible和ATR-FTMIR光谱数据。将PCA应用于光谱数据集以表示非常小的空间中的数据，然后对PCA合成的主要成分进行判别。PCA-LDA方法在UV-Visible和ATR-FTMIR光谱数据上的应用显示出了根据其地理来源对橄榄油进行分类的良好能力，正确分类的百分比分别为90.24％和85.87％，并且通过PCA-SVM对UV-Visible和ATR-FTMIR的光谱数据进行处理，可以正确区分五种橄榄油，正确分类率分别为100％和97.56。这项研究证明了UV-Visible和ATR-FTMIR指纹图谱（常规技术）在贝尼梅拉尔-凯尼夫拉摩洛哥地区的橄榄油地理分类中的可行性。