近红外光谱技术在食用油掺伪检测中的研究进展

食用油是日常饮食的必需品, 可以为人体提供热能和脂肪酸, 是促进脂溶性维生素吸收的重要有机物。随着人们生活水平的提高, 高档食用油已走进大众百姓的餐桌, 并深受欢迎和喜爱。由于高档食用油市场售价高, 一些不法厂商为牟取暴利, 在高档食用油中掺入廉价食用油进行出售, 导致食用油掺伪事件时有发生, 已引起政府和民众的广泛关注。为保障消费者的合法利益和维护正常的食用油市场秩序, 快速有效地检测食用油掺伪已刻不容缓。近红外光谱技术以其简便、快速、无损、无需样品预处理的特点, 被广泛应用于食用油掺伪分析。概述了近红外光谱技术的基本原理, 综述了近十年来近红外光谱技术在橄榄油、山茶油、芝麻油、核桃油等食用油的掺伪检测研究进展, 包括采用不同的试验装置与试验方法、数据处理方法包括预处理、特征波长选择及建模方法, 对二元、三元及多元食用油掺伪进行检测研究, 从试验方法及数据处理等角度提高食用油掺伪检测的精度与适用范围, 以期建立较为有效的食用油掺伪定量检测与定性鉴别模型。总结了食用油掺伪近红外光谱检测目前存在的问题, 包括食用油掺伪检测机理不明晰, 制备的掺伪食用油样本难以满足实际的复杂掺伪形式, 采用取样方式的掺伪检测仅能实现现场部分抽检, 及未建立食用油掺伪检测的统一标准规范。展望了今后的发展趋势, 指出近红外光谱技术与其他快速检测技术融合获取更精准、可靠的检测模型, 与物联网和大数据相结合构建食用油近红外光谱数据库, 实现光谱数据的共享、掺伪检测模型的在线升级与远程更新, 将是未来的发展方向。

Abstract

Edible oil is a necessity in daily diet, providing heat energy and fatty acid for the human body. It is an important organic matter that promotes the absorption of fat-soluble vitamins. With the improvement of people’s living standards, high-grade edible oil has entered the table of the public and is deeply welcomed. Due to the high selling price of high-grade edible oil in the market, some illegal manufacturers mix cheap edible oil into high-grade edible oil for sale to make huge profits. And this leads to the adulteration of edible oil from time to time, which has aroused widespread concern of the government and the public. In order to protect the legitimate interests of consumers and maintain the normal order of the edible oil market, it is urgent to detect the adulteration of edible oil quickly and effectively. Near-infrared spectroscopy(NIR)has the advantages of simple, rapid, nondestructive and no sample pretreatment, and it is widely used in the analysis of adulteration of edible oil. This paper summarizes the basic principle of NIR technology and reviews the research progress of NIR technology in adulteration detection of edible oils such as olive oil, camellia oil, sesame oil and walnut oil in recent ten years. Different test devices, test methods and data processing methods(pretreatment, wavelength selection and modeling methods) are mainly used to detect the binary, ternary and multivariant adulteration of edible oil to improve the accuracy and application range of edible oil adulteration detection and establish a more effective quantitative detection and qualitative identification model for edible oil adulteration. Then, it summarizes the existing problems in the detection of adulteration of edible oil by near-infrared spectroscopy, such as the detection mechanism of adulteration of edible oil is unclear. The prepared adulterated edible oil samples are difficult to meet the actual complex adulteration forms, the adulteration detection by sampling can only realize part of the spot sampling inspection, and the unified standard specification of adulteration detection of edible oil is not established. At last, it points out the development trend in future to integrate NIR with other rapid detection technologies to obtain more accurate and reliable detection models, and the construction of edible oil NIR database using the internet of things and big data technology to realize spectral data sharing and online upgrade and remote update of adulteration detection models. This paper aims to provide references and solutions for detecting adulteration of edible oil in China.

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吴成招, 王一韬, 胡栋, 孙通. 近红外光谱技术在食用油掺伪检测中的研究进展[J]. 光谱学与光谱分析, 2023, 43(3): 685. WU Cheng-zhao, WANG Yi-tao, HU Dong, SUN Tong. Research Progress of Near-Infrared Spectroscopy in the Detection of Edible Oil Adulteration[J]. Spectroscopy and Spectral Analysis, 2023, 43(3): 685.

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