Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, Karlsruhe, Germany.
Department of Food Chemistry and Phytochemistry Institute, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
Magn Reson Chem. 2019 Sep;57(9):579-588. doi: 10.1002/mrc.4838. Epub 2019 Feb 26.
Both the German and European organic food markets are growing fast, and there is also a rising demand for organic chicken eggs. Consumers are willing to pay higher prices for organic eggs produced in an animal-appropriate environment considering animal welfare. Strict labelling requirements do not prevent chicken eggs from being a subject of food fraud. Conventionally produced (barn/free-range) eggs can easily be mislabeled as organic eggs. Especially because the demand for organically produced chicken eggs is likely to exceed supply in the future, mislabeling appears to be a realistic scenario. Therefore, there is a need for analytical methods that are suitable to classify eggs as being either conventionally or organically produced. Nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis is a suitable tool to screen eggs according to the different systems of husbandry. Sample preparation is based on a fat extraction method, which was optimised for application to freeze-dried egg yolk. Samples were analysed using typical q-NMR parameters. A nontargeted approach was used for the analysis of the H NMR data. Principal component analysis (PCA) was applied followed by a linear discriminant analysis (PCA-LDA) and Monte Carlo cross-validation. In total, 344 chicken eggs (214 barn/free-range eggs and 130 eggs from organic farms), most of them originating from Germany, were used to build and validate the prediction model. The results showed that the prediction model allowed for the correct classification of about 93% of the organic eggs.
德国和欧洲的有机食品市场增长迅速,对有机鸡蛋的需求也在上升。考虑到动物福利,消费者愿意为在适宜动物环境中生产的有机鸡蛋支付更高的价格。严格的标签要求并不能阻止鸡蛋成为食品欺诈的对象。传统生产的(谷仓/散养)鸡蛋很容易被贴上有机鸡蛋的标签。特别是由于未来有机生产的鸡蛋的需求可能超过供应,因此标签错误似乎是一种现实情况。因此,需要有合适的分析方法来区分传统生产和有机生产的鸡蛋。核磁共振(NMR)光谱结合多元数据分析是根据不同的饲养系统筛选鸡蛋的合适工具。样品制备基于一种脂肪提取方法,该方法经过优化,适用于冻干蛋黄。使用典型的 q-NMR 参数对样品进行分析。采用无目标分析方法对 1 H NMR 数据进行分析。应用主成分分析(PCA),然后进行线性判别分析(PCA-LDA)和蒙特卡罗交叉验证。总共使用了 344 个鸡蛋(214 个谷仓/散养鸡蛋和 130 个有机农场鸡蛋),其中大部分来自德国,用于建立和验证预测模型。结果表明,该预测模型能够正确分类约 93%的有机鸡蛋。