Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.     

电子鼻技术结合化学计量学快速鉴别掺假茶籽油

目的:建立茶籽油掺假的快速定性和定量检测方法。方法:采用电子鼻技术结合化学计量学，基于单因素方差分析筛选差异变量，通过主成分分析(PCA)和判别分析(DA)建立茶籽油掺假类型鉴别的定性模型；通过正交偏最小二乘法(OPLS)建立了茶籽油掺假类型和掺假度鉴别的定量模型。结果:模型的R²均高达0.98,RMSEE均低于0.005,RMSECV均低于0.01,具有较高性能指标。通过外部验证，DA模型对不同掺假类型的茶油样品定性识别率高达100%,OPLS模型具有良好的准确性。结论:电子鼻技术结合化学计量学能够实现茶籽油掺假的快速、无损鉴定。     

反向传播神经网络算法结合拉曼荧光光谱法定量检测特级初榨橄榄油掺假

目的 建立基于反向传播神经网络算法结合拉曼荧光光谱技术定量检测低等级橄榄油掺假特级初榨橄榄油的分析方法。方法 制备11种不同掺伪浓度的特级初榨橄榄油混合油样各10份，在相同时间、空间及目标的前提下，使用同台光谱探测系统，采集样品的拉曼光谱和荧光光谱。经过卷积神经网络去除拉曼光谱的基线，实现拉曼光谱和荧光光谱的数据预处理。根据分子光谱与电子光谱的特征差异，人为干预并设定拉曼光谱的权重，建立低等级橄榄油掺假特级初榨橄榄油的反向传播神经网络回归模型。结果 综合评估了反向传播神经网络回归模型的评价参数，特级初榨橄榄油掺假的反向传播神经网络模型的测试集决定系数为0.9716，均方根误差为0.0569，模型预测效果较好。结论 本研究提出的反向传播神经网络算法结合拉曼光谱与荧光的探测方法，满足快速检测低等级橄榄油掺假特级初榨橄榄油的定量分析需求，为评价或跟踪特级初榨橄榄油的品质提供了一种无损伤、高效率、低成本的新检测思路。     

Sniffing out adulteration in saffron: Detection methods and health risks

Saffron, the golden spice, is a medicinally and economically important crop that is used in a variety of cuisines to add colour, taste and aroma. Being the costliest spice, saffron is regularly adulterated through the use of various cheap synthetic colourants and natural adulterants. Mislabelling, presenting lower-grade saffron as superior and misrepresenting the geographic origin is a common practice. Adulteration not only reduces the quality of saffron, but also leads to serious health concern and economic loss. To ensure authenticity and quality of saffron, the development of effective detection methods is crucial. The present review provides an overview of common saffron adulterants, their effects, and several methods for identifying and quantifying these adulterants. Traditionally, saffron authentication is done using conventional physical methods. There are numerous high-end techniques such as molecular, chromatography, spectroscopy and sensor-based approaches that have been widely used for saffron adulteration detection. However, these methods have their advantages and disadvantages. Besides, their utility is restricted to the purpose of detection. In recent years, artificial intelligence/machine learning-based imaging approaches have emerged as rapid, cost effective and user-friendly detection approach. This allows end user to detect adulteration by simply clicking an image and receiving instant feedback regarding its authenticity. Further research and advancement in the detection methods will enable authenticity check and ensure integrity and quality of saffron.     

微晶纤维素掺假的快速鉴别方法

研究了微晶纤维素掺假的近红外光谱快速鉴别方法。基于微晶纤维素样品及掺假物(可溶性淀粉,小麦粉)的近红外光谱数据,分别创建材料谱数据库及掺假物光谱数据库,建立微晶纤维素分类模型及掺假物模型,采用Adulterant Screen算法技术进行计算分析,创建了微晶纤维素掺假快速鉴别方法。微晶纤维粉单一组份掺假的识别最低检出含量为:可溶性淀粉2%、小麦粉1%,双组分(可溶性淀粉+小麦粉)掺假量在单组份掺假检出限浓度的2～10倍时,准确的识别率均为100%,对未知样品微晶纤维素在检出限以上的准确识别率为100%。该方法简单、快速、可靠,可快速鉴别微晶纤维素样品的掺假,可以有效地应用于日常微晶纤维素样品的掺假检测和鉴定,为海关打击逃税漏税行为提供有力的技术支持。