检测山茶油真伪和掺假的先进技术综述

IF 1.9 4区 农林科学 Q3 CHEMISTRY, APPLIED
Shahzad Farooq, Muhammad Ijaz Ahmad, Usman Ali, Yang Li, Cui Shixiu, Hui Zhang
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引用次数: 0

摘要

山茶油是全球四大木本油料之一,因其含有大量不饱和脂肪酸以及生育酚、酚类和叶绿素等功能性化合物,而具有极高的营养价值。遗憾的是,由于需求量大、成本高,欺诈者故意在山茶油中混入质量较差的植物油,以牟取暴利。这引起了利益相关者的担忧,促使人们需要强有力的鉴定方法。本综述简要概述了用于评估山茶油真伪、质量和潜在掺假情况的各种分析技术。文中讨论了几种技术,如色谱法、同位素比质谱法 (IRMS)、离子迁移谱法 (IMS)、差示扫描量热法 (DSC)、基于等离子体和脱氧核糖核酸 (DNA) 的技术,以及电子鼻和电子舌等新兴方法。值得注意的是,传统色谱技术(气相色谱和高效液相色谱)耗时费力,使用有毒化学物质,需要复杂的样品预处理。由于山茶油的精炼过程复杂,包括高温脱色和除臭,DNA含量会降低并引起降解,因此DNA技术在检测掺假物方面也面临挑战。相比之下,荧光光谱、核磁共振和红外(近、中、远)光谱等光谱技术与化学计量分析相结合,已成为山茶油质量控制中可靠、快速、简单、灵敏和准确的替代分析工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review of advanced techniques for detecting the authenticity and adulteration of camellia oil

Camellia oil, one of the four major woody oils globally, possesses exceptional nutritional value due to its high contents of unsaturated fatty acids and functional compounds like tocopherols, phenolics, and chlorophyll. Unfortunately, due to high demand and cost, fraudsters deliberately mix lower-quality vegetable oils with camellia oil for profits. This has raised concerns among stakeholders, prompting the need for robust authentication methods. This review provides a concise overview of various analytical techniques employed to assess the authenticity, quality, and potential adulteration of camellia oil. Several techniques, such as chromatography, isotope-ratio mass spectrometry (IRMS), ion mobility spectrometry (IMS), differential scanning calorimetry (DSC), plasma-based and deoxyribonucleic acid (DNA)-based techniques, as well as emerging methods like electronic noses and electronic tongues, are discussed. Notably, traditional chromatographic techniques (GC and HPLC) are reported to be time-consuming, laborious, employ toxic chemicals, and require complicated sample pretreatments. DNA techniques also face challenges in detecting adulterants due to the complex refining processes of camellia oil, including high-temperature decolorization and deodorization, which reduce DNA content and induce degradation. In contrast, spectroscopic techniques such as fluorescence spectroscopy, nuclear magnetic resonance, and infrared (near, mid, far) spectroscopy combined with chemometric analyses, have emerged as reliable, rapid, simple, sensitive, and accurate alternative analytical tools for the quality control of camellia oil.

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来源期刊
CiteScore
4.10
自引率
5.00%
发文量
95
审稿时长
2.4 months
期刊介绍: The Journal of the American Oil Chemists’ Society (JAOCS) is an international peer-reviewed journal that publishes significant original scientific research and technological advances on fats, oils, oilseed proteins, and related materials through original research articles, invited reviews, short communications, and letters to the editor. We seek to publish reports that will significantly advance scientific understanding through hypothesis driven research, innovations, and important new information pertaining to analysis, properties, processing, products, and applications of these food and industrial resources. Breakthroughs in food science and technology, biotechnology (including genomics, biomechanisms, biocatalysis and bioprocessing), and industrial products and applications are particularly appropriate. JAOCS also considers reports on the lipid composition of new, unique, and traditional sources of lipids that definitively address a research hypothesis and advances scientific understanding. However, the genus and species of the source must be verified by appropriate means of classification. In addition, the GPS location of the harvested materials and seed or vegetative samples should be deposited in an accredited germplasm repository. Compositional data suitable for Original Research Articles must embody replicated estimate of tissue constituents, such as oil, protein, carbohydrate, fatty acid, phospholipid, tocopherol, sterol, and carotenoid compositions. Other components unique to the specific plant or animal source may be reported. Furthermore, lipid composition papers should incorporate elements of year­to­year, environmental, and/ or cultivar variations through use of appropriate statistical analyses.
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