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中国精品科技期刊2020
唐聪,邵士俊,温玉洁,等. 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. doi: 10.13386/j.issn1002-0306.2022060131.
引用本文: 唐聪,邵士俊,温玉洁,等. 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. doi: 10.13386/j.issn1002-0306.2022060131.
TANG Cong, SHAO Shijun, WEN Yujie, et al. Rapid Identification of Extra Virgin Olive Oil by Spectrometry[J]. Science and Technology of Food Industry, 2023, 44(9): 309−316. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022060131.
Citation: TANG Cong, SHAO Shijun, WEN Yujie, et al. Rapid Identification of Extra Virgin Olive Oil by Spectrometry[J]. Science and Technology of Food Industry, 2023, 44(9): 309−316. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022060131.

基于光谱法的特级初榨橄榄油快速鉴伪技术

Rapid Identification of Extra Virgin Olive Oil by Spectrometry

  • 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。

     

    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.

     

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