基于便携式拉曼光谱的进口散装橄榄油品质现场快速无损鉴别方法

随着食品全球产业链的整合和大众生活水平提高，进口植物油在日常饮食中占比逐步增加，具有丰富营养价值的橄榄油在植物油产品中备受关注。在进口散装橄榄油的跨境运输和通关过程中，由于环境、温度和时间等因素的影响，分仓储运的橄榄油中不饱和脂肪酸可能发生氧化，以及初榨橄榄油中果肉碎渣沉淀在多次换仓时进行累积，导致橄榄油不同分仓和同一仓位不同位置的植物油品质出现较大差异，给橄榄油口岸现场的抽样监管和质量评价带来较大困扰。针对散装橄榄油现场快速品质评价的需求，在偏最小二乘法的基础上，将拉曼响应强度转换为向量空间角度值，建立橄榄油品质指标分析预测模型，针对不同抽样点样本进行橄榄油品质的快速现场预判，确保散装橄榄油在进出口环节的精准监管。首先采用传统方法分别测定经过220，240和260 ℃温度下，加热不同时长的橄榄油的酸价、过氧化值和亚麻酸的实测值，同时采用便携式拉曼光谱仪检测对应油样的拉曼光谱，通过平滑滤波求导等手段对光谱数据进行预处理，采用偏最小二乘法及角度度量法，对橄榄油的酸价、过氧化值、亚麻酸三种指标进行建模分析，两种方法建立的指标模型相关系数均达到0.99以上，其中角度度量法的相对误差范围不超过-5.43%。在进口散装橄榄油中随机抽取七个不同的样品进行验证，角度度量法建立的三种模型预测结果均方根误差分别为0.025 8，0.222 8和17.064 1，相对误差范围在-4.71%~5.98%之间，结果显示角度度量法建立的模型更准确，具有更好的预测性及稳定性。该方法可应用于进口散装橄榄油品质的现场快速品质鉴别，提升口岸现场监管环节质量评价的精准性，为进出口散装橄榄油质量综合评价提供技术保障。

On-Site Rapid and Non-Destructive Identification Method for Imported Bulk Olive Oil Quality Based on Portable Raman Spectroscopy

With the integration of the global food industry chain and the improvement of people’s living standards, the proportion of imported vegetable oil in the daily diet has gradually increased. Olive oil with rich nutritional value has attracted much attention in vegetable oil products. During the cross-border transportation and customs clearance of imported bulk olive oil, due to the influence of factors such as environment, temperature and time, the unsaturated fatty acids in the olive oil transported in storage may be oxidized. The pulp residue in the virgin olive oil may precipitate in The accumulation of multiple warehouse exchanges has resulted in large differences in the quality of vegetable oil in different locations of the olive oil warehouses and in the same warehouse, which has caused great difficulties for the on-site sampling supervision and quality evaluation of olive oil ports. In response to the need for rapid quality evaluation of bulk olive oil on-site, this paper converts the Raman response intensity into a vector space angle value based on the partial least square method, establishes an olive oil quality index analysis and prediction model, and conducts olive oil based on samples from different sampling points. The fast on-site prediction of quality ensures the precise supervision of bulk olive oil in the import and export links. Firstly, the traditional method is used to measure the acid value, peroxide value and linolenic acid value of olive oil heated for different durations at 220, 240 and 260 ℃ respectively. At the same time, a portable Raman spectrometer is used to detect the corresponding oil sample. Mann spectroscopy, preprocessing the spectral data by means of smoothing filtering and derivation, combining the partial least squares method and the angle measurement method to model and analyze the acid value, peroxide value, and linolenic acid of olive oil. The correlation coefficients of the index models established by the method are all above 0.99, and the relative error range of the angle measurement method does not exceed -5.43%. Seven different samples were randomly selected from imported bulk olive oil for verification. The root means square errors of the three models established by the angle measurement method were 0.025 8, 0.222 8, and 17.064 1 respectively, and the relative error range was -4.71%~5.98%. The results show that the model established by the angle measurement method is more accurate, with better predictability and stability. This method can be applied to the on-site rapid quality identification of imported bulk olive oil quality, improve the quality evaluation of the port on-site supervision link, and provide technical guarantee for the comprehensive evaluation of imported and exported bulk olive oil quality.