CEISAM CNRS, UMR6230, EBSI team, Université de Nantes, BP 92208. 2 rue de la Houssinière, 44322 Nantes France.
CEISAM CNRS, UMR6230, EBSI team, Université de Nantes, BP 92208. 2 rue de la Houssinière, 44322 Nantes France; LUNAM Université, Oniris, Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), 44307 Nantes France.
Food Chem. 2018 Apr 1;244:153-158. doi: 10.1016/j.foodchem.2017.10.016. Epub 2017 Oct 6.
We report the use of an Ultrafast 2D NMR approach applied on a benchtop NMR system (43 MHz) for the authentication of edible oils. Our results demonstrate that a profiling strategy based on fast 2D NMR spectra recorded in 2.4 min is more efficient than the standard 1D experiments to classify oils from different botanical origins, since 1D spectra on the same samples suffer from strong peak overlaps. Six edible oils with different botanical origins (olive, hazelnut, sesame, rapeseed, corn and sunflower) have been clearly discriminated by PCA analysis. Furthermore, we show how this approach combined with a PLS model can detect adulteration processes such as the addition of hazelnut oil into olive oil, a common fraud in food industry.
我们报告了一种超快 2D NMR 方法的应用，该方法应用于台式 NMR 系统（43 MHz），用于鉴定食用油。我们的结果表明，基于快速 2D NMR 光谱记录的分析策略比标准 1D 实验更有效，可用于分类来自不同植物来源的油，因为同一样品的 1D 光谱存在强烈的峰重叠。六种具有不同植物来源的食用油（橄榄油、榛子油、芝麻油、菜籽油、玉米油和葵花籽油）通过 PCA 分析得到了明确区分。此外，我们展示了如何将这种方法与 PLS 模型结合起来，检测到诸如榛子油掺入橄榄油等掺假过程，这是食品行业中的常见欺诈行为。
