Schmitt Caroline, Schneider Tobias, Rumask Laura, Fischer Markus, Hackl Thomas
Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, Hamburg 20146, Germany.
HAMBURG SCHOOL OF FOOD SCIENCE-Institute of Food Chemistry, University of Hamburg, Grindelallee 117, Hamburg 20146, Germany.
J Agric Food Chem. 2020 Dec 30;68(52):15526-15534. doi: 10.1021/acs.jafc.0c05827. Epub 2020 Dec 15.
Walnuts, with their health-promoting ingredients, are among the most popular nuts, and practicable methods for determining their geographical origin are needed to tackle food fraud. Authentic walnut samples (235, L.) from different harvest years (2016-2019) and countries were analyzed by H NMR spectroscopy in combination with chemometric methods to determine their geographical origin. Two sample groups were analyzed at a time with a support vector machine algorithm to obtain two-class classifier models. In total, nine two-class models were built (e.g., Germany/China, France/Germany, and USA/Switzerland), and a repeated nested cross-validation was performed. The models obtained showed high accuracies from 78.0% (±2.3%) to 96.6% (±0.6%). Furthermore, identification of potential chemical markers in the walnut extract was performed.
核桃因其有益健康的成分而成为最受欢迎的坚果之一，为应对食品欺诈问题，需要切实可行的方法来确定其地理来源。采用核磁共振氢谱（H NMR）光谱结合化学计量学方法，对来自不同收获年份（2016 - 2019年）和国家的正宗核桃样品（235，L.）进行分析，以确定其地理来源。每次使用支持向量机算法分析两个样本组，以获得两类分类器模型。总共建立了九个两类模型（例如，德国/中国、法国/德国和美国/瑞士），并进行了重复嵌套交叉验证。所获得的模型显示出较高的准确率，从78.0%（±2.3%）到96.6%（±0.6%）。此外，还对核桃提取物中的潜在化学标志物进行了鉴定。
