Cottenet Geoffrey, Cavin Christophe, Blancpain Carine, Chuah Poh Fong, Pellesi Roberta, Suman Michele, Nogueira Sofia, Gadanho Mario
Institute of Food Safety and Analytical Sciences, Nestlé Research, Vers-chez-les-Blanc, 1000 Lausanne, Switzerland.
Nestlé Quality Assurance Center, Quality Road, 618802 Singapore.
J AOAC Int. 2022 Dec 22;106(1):65-72. doi: 10.1093/jaoacint/qsac099.
Spices and herbs are food categories regularly cited as highly susceptible to be adulterated. To detect potential adulteration with undeclared species, DNA-based methods are considered the most suitable tools.
In this study, the performance of the ready-to-use Thermo Scientific™ NGS Food Authenticity Workflow (Thermo Fisher Scientific)-a commercial DNA metabarcoding approach-is described. The tool was further applied to analyze 272 commercial samples of spices and herbs.
Pure samples of spices and herbs were analyzed with the Thermo Scientific NGS Food Authenticity Workflow to assess its specificity, and spikings down to 1% (w/w) allowed evaluation of its sensitivity. Commercial samples, 62 and 210, were collected in Asian and European markets, respectively.
All tested species were correctly identified often down to the species level, while spikings at 1% (w/w) confirmed a limit of detection at this level, including in complex mixtures composed of five different spices and/or herbs. The analysis of 272 commercial samples showed that 78% were compliant with the declared content, whereas the rest were shown to contain undeclared species that were in a few cases allergenic or potentially toxic.
The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable to identify food plant species in herbs and spices, not only when tested on pure samples, but also in mixtures down to 1% (w/w). The overall workflow is user-friendly and straightforward, which makes it simple to use and facilitates data interpretation.
The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable for species identification in herbs and spices, and it allowed the detection of undeclared species in commercial samples. Its ease of use facilitates its implementation in testing laboratories.
香料和药草是经常被认为极易掺假的食品类别。为了检测未申报物种的潜在掺假情况，基于DNA的方法被认为是最合适的工具。
在本研究中，描述了即用型赛默飞世尔科技™NGS食品真实性工作流程（赛默飞世尔科技）——一种商业DNA宏条形码方法的性能。该工具进一步应用于分析272个商业香料和药草样品。
用赛默飞世尔科技NGS食品真实性工作流程分析香料和药草的纯样品，以评估其特异性，并将加样量降至1%（w/w）以评估其灵敏度。分别在亚洲和欧洲市场收集了62个和210个商业样品。
所有测试物种通常都能准确鉴定到物种水平，而1%（w/w）的加样量证实了该水平的检测限，包括在由五种不同香料和/或药草组成的复杂混合物中。对272个商业样品的分析表明，78%符合申报内容，而其余样品被证明含有未申报物种，其中一些在某些情况下具有致敏性或潜在毒性。
发现赛默飞世尔科技NGS食品真实性工作流程不仅适用于纯样品测试，也适用于低至1%（w/w）混合物中香料和药草的食用植物物种鉴定。整个工作流程用户友好且简单直接，易于使用并便于数据解读。
发现赛默飞世尔科技NGS食品真实性工作流程适用于香料和药草中的物种鉴定，并能检测商业样品中的未申报物种。其易用性便于在检测实验室中实施。
