Geographical identification of Italian extra virgin olive oil by the combination of near infrared and Raman spectroscopy: A feasibility study

偏最小二乘回归 线性判别分析 拉曼光谱 橄榄油 光谱学 分析化学(期刊) 近红外光谱 融合 模式识别(心理学) 交叉验证 化学计量学 灵敏度(控制系统) 数学 人工智能 化学 材料科学 统计 食品科学 计算机科学 色谱法 物理 光学 工程类 语言学 哲学 量子力学 电子工程
作者
Marco Bragolusi,Andrea Massaro,Carmela Zacometti,Alessandra Tata,Roberto Piro
出处
期刊:Journal of Near Infrared Spectroscopy [SAGE Publishing]
卷期号:29 (6): 359-365 被引量:11
标识
DOI:10.1177/09670335211051575
摘要

The potential of the combination of near infrared (NIR) spectroscopy and Raman spectroscopy to differentiate Italian and Greek extra virgin olive oil (EVOO) by geographical origin was evaluated. Near infrared spectroscopy and Raman fingerprints of both study groups (extra virgin olive oil from the two countries) were pre-processed, merged by low-level and mid-level data fusion strategies and submitted to partial least-squares discriminant analysis. The classification models were cross-validated. After low-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 93.9% accuracy, while sensitivity and specificity were 77.8% and 100%, respectively. After mid-level data fusion, the partial least-squares discriminant analysis correctly predicted the geographical origins of extra virgin olive oils in cross-validation with 97.0% accuracy, while sensitivity and specificity were 88.9% and 100%, respectively. In this preliminary study, improved discrimination of Italian extra virgin olive oils was achieved by the synergism of near infrared spectroscopy and Raman spectroscopy as compared to the discrimination obtained by the separate laboratory techniques. This pilot study shows encouraging results that could open a new avenue for the authentication of Italian extra virgin olive oil.
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