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基于光谱法的特级初榨橄榄油快速鉴伪技术
引用本文:唐聪,邵士俊,温玉洁,梁卿,董树清.基于光谱法的特级初榨橄榄油快速鉴伪技术[J].食品工业科技,2023,44(9):309-316.
作者姓名:唐聪  邵士俊  温玉洁  梁卿  董树清
作者单位:1.中国科学院兰州化学物理研究所,中国科学院西北植物资源化学重点实验室,甘肃省天然药物重点实验室,甘肃兰州 7300002.中国科学院大学,北京 100049
基金项目:国家重点研发计划(No.2019YFD1002403);甘肃省重点研发计划(No.20YF8FA003)。
摘    要:本文研究了特级初榨橄榄油中掺入不同比例橄榄果榨油(精炼橄榄油)、菜籽油、玉米油和大豆油的光谱特征,采用荧光光谱和紫外光谱,对掺假样品及纯油样品进行了快速检测。结果表明,特级初榨橄榄油的光谱特征与其他植物油之间差异较大,且掺假体积与吸光度之间存在良好的线性关系(R2>0.89),实现了特级初榨橄榄油的定性鉴别与定量检测,建立了特级初榨橄榄油质量控制体系及其掺假检测分析技术,最低检出限为1%,线性范围为5%~100%(v/v)。系统聚类分析将所有特级初榨橄榄油准确地分为一个亚类,也佐证了此方法的稳定性与可靠性。这种简单快捷的检测技术,有助于特级初榨橄榄油实时、在线橄榄油检测分析技术的研发,为我国橄榄油品质鉴定及产业发展提供有利的技术保障。

关 键 词:特级初榨橄榄油  荧光光谱  吸收光谱  鉴伪
收稿时间:2022-06-15

Rapid Identification of Extra Virgin Olive Oil by Spectrometry
TANG Cong,SHAO Shijun,WEN Yujie,LIANG Qing,DONG Shuqing.Rapid Identification of Extra Virgin Olive Oil by Spectrometry[J].Science and Technology of Food Industry,2023,44(9):309-316.
Authors:TANG Cong  SHAO Shijun  WEN Yujie  LIANG Qing  DONG Shuqing
Affiliation:1.CAS Key Laboratory of Chemistry of Northwestern Plant Resources and Key Laboratory for Natural Medicine of Gansu Province, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China2.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:In this paper, the spectral characteristics of extra virgin olive oil mixed with different proportions of olive oil (refined olive oil), rapeseed oil, corn oil and soybean oil were investigated. The adulterated samples and pure oil samples were rapidly detected by fluorescence spectroscopy and ultraviolet spectroscopy. The results showed that the spectral characteristics of extra virgin olive oil were quite different from other vegetable oils, and there was a good linear relationship between the adulteration volume and absorbance of adulterated extra virgin olive oil (R2>0.89), which realized the qualitative identification and quantitative detection of extra virgin olive oil. The quality control system of extra virgin olive oil and its adulteration detection and analysis technology was established. The minimum detection limit was 1% and the linear range was 5%~100% (v/v). Systematic cluster analysis accurately classified all extra virgin olive oils into one subclass, which also confirmed the stability and reliability of this method. This simple and fast detection technology is conducive to the research and development of real-time, online olive oil detection and analysis technology for extra virgin olive oil portable detection equipment, and provides a favorable technical guarantee for Chinese olive oil quality identification and industrial development.
Keywords:
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