Identification of Adulterated Cooking Oil by Raman Spectroscopy

IF 2.6 3区 农林科学 Q2 FOOD SCIENCE & TECHNOLOGY
Hina Shehnaz, Ayesha Ashraf, Muhammad Irfan Majeed, Haq Nawaz, Maira Afzal, Muhammad Zeeshan Majeed, Muhammad Idrees Jilani, Muhammad Waseem Akram, Rabeea Razaq, Eiman Sultan, Naeema Kanwal, Urwa Shahid
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Abstract

A better quality of life comes with a healthy diet without adulteration or contamination. As much as the demand for purity in diet increases, the risk of adulteration also increases in daily edibles. The present study proposed Raman spectroscopy for the identification of used cooking oils to overcome adulteration. Unused cooking oil with different concentrations of used oil (waste oil) as an adulterant was examined by Raman spectroscopy along with principal component analysis (PCA). Increasing the concentration of used oil causes changes in Raman spectral features. The changes can be observed at 1413 cm−1, 1521 cm−1, and 1745 cm−1 in Raman mean spectra of unused oil with the addition of different concentrations of the adulterant. Raman spectroscopy with PCA gives qualitative analysis and helps to monitor the quality of the cooking oil. PCA is a statistical tool that is used to examine variations in the given Raman spectral dataset. PC-1 shows more variability about 93.8% for the differentiation of the Raman spectral groups of the used and unused oil, while for unused oil and its different concentrations with adulterant, it shows a variability of 88.8%. These results demonstrate that Raman spectroscopy can be applied for the identification of adulterated oil. In the future, this spectroscopic technique can be used in the field of food chemistry because of its non-invasiveness and non-destructive analysis.

Abstract Image

利用拉曼光谱鉴别掺假食用油
没有掺假或污染的健康饮食能带来更好的生活质量。随着人们对饮食纯度的要求越来越高,日常食品中掺假的风险也随之增加。本研究建议使用拉曼光谱鉴别使用过的食用油,以防止掺假。通过拉曼光谱和主成分分析法(PCA)对掺入不同浓度废油的未使用食用油进行了检测。废油浓度的增加会导致拉曼光谱特征发生变化。添加不同浓度的掺杂剂后,未使用过的油的拉曼光谱平均值在 1413 厘米-1、1521 厘米-1 和 1745 厘米-1 处会发生变化。利用 PCA 进行拉曼光谱定性分析,有助于监测食用油的质量。PCA 是一种统计工具,用于研究给定拉曼光谱数据集的变化。PC-1 在区分使用过的油和未使用过的油的拉曼光谱组方面显示出更大的变异性,约为 93.8%,而对于未使用过的油及其不同浓度的掺杂物,则显示出 88.8%的变异性。这些结果表明,拉曼光谱可用于鉴别掺假油。由于这种光谱技术具有非侵入性和非破坏性分析的特点,因此今后可用于食品化学领域。
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来源期刊
Food Analytical Methods
Food Analytical Methods 农林科学-食品科技
CiteScore
6.00
自引率
3.40%
发文量
244
审稿时长
3.1 months
期刊介绍: Food Analytical Methods publishes original articles, review articles, and notes on novel and/or state-of-the-art analytical methods or issues to be solved, as well as significant improvements or interesting applications to existing methods. These include analytical technology and methodology for food microbial contaminants, food chemistry and toxicology, food quality, food authenticity and food traceability. The journal covers fundamental and specific aspects of the development, optimization, and practical implementation in routine laboratories, and validation of food analytical methods for the monitoring of food safety and quality.
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