Ma Te, Jiang Hao, Tsuchikawa Satoru, Inagaki Tetsuya
Graduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 4648601, Japan.
Shaanxi Union Research Center of University and Enterprise for Grain Processing Technologies, College of Food Science and Engineering, Northwest A&F University, Yangling 712100, China.
Food Chem. 2025 Feb 15;465(Pt 2):142125. doi: 10.1016/j.foodchem.2024.142125. Epub 2024 Nov 18.
Adulteration identification in extra virgin olive oil (EVOO) is a significant concern in the olive oil industry. This study aimed to detect low-level adulteration of EVOO with other edible oils by using a novel time-resolved laser-induced fluorescence (TRLIF) fingerprinting method. Five EVOO brands were first analyzed to assess its potential for classification based on their differing fluorophore content. The developed method effectively reduces the effects associated with the optical path length and excitation light intensity. Subsequently, three sets of binary mixtures were tested: EVOO adulterated with refined olive oil, soybean oil, and sunflower oil. Quantitative analysis was performed using parallel factor analysis, which achieved a cross-validation coefficient of determination (R) exceeding 0.90, with a prediction error < 1.40 %. These findings demonstrate that this method has the potential to determine the purity and quality of EVOO.
特级初榨橄榄油（EVOO）中的掺假鉴定是橄榄油行业的一个重大问题。本研究旨在通过一种新型的时间分辨激光诱导荧光（TRLIF）指纹图谱方法检测EVOO与其他食用油的低水平掺假。首先对五个EVOO品牌进行分析，以评估基于其不同荧光团含量进行分类的潜力。所开发的方法有效降低了与光程长度和激发光强度相关的影响。随后，测试了三组二元混合物：掺有精炼橄榄油、大豆油和向日葵油的EVOO。使用平行因子分析进行定量分析，交叉验证决定系数（R）超过0.90，预测误差<1.40%。这些结果表明，该方法有潜力确定EVOO的纯度和质量。
