Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H₃O⁺, NO⁺ and O₂⁺ as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90–100%) and prediction accuracy (96.70–100% accuracy for cross validation and 97.30–100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases).

选定的离子流管质谱分析法（SIFT-MS）与化学计量学相结合，用于鉴定以地理起源标签生产的地中海原始橄榄油（VOOs）的地理起源。特别是，考虑了来自六个不同地中海地区（卡拉马塔（希腊）；托斯卡纳（意大利）；梅克内斯和蒂奥特（摩洛哥）；普列戈·科尔多瓦和巴埃纳（西班牙））的130个油样。通过SIFT-MS在H ₃ O ⁺，NO ⁺和O ₂ ^+的全扫描中测量顶空挥发性指纹作为前体离子，并对结果进行化学计量处理。主成分分析（PCA）用于初步的多元数据分析，偏最小二乘判别分析（PLS-DA）用于构建不同的模型（考虑三种试剂离子），以便根据原产国和地区对样品进行分类（在同一国家/地区）。多类PLS-DA模型在拟合精度（98.90–100％）和预测精度（交叉验证的准确度为96.70–100％，外部验证（测试集）的准确性为97.30–100％）方面显示出非常好的性能。考虑到两类PLS-DA模型，一个用于西班牙样品的模型在校准，交叉验证和外部验证中显示出100％的灵敏度，特异性和准确性；