RIKILT, Wageningen University and Research Centre, Wageningen, The Netherlands.
J Agric Food Chem. 2011 Aug 24;59(16):8816-21. doi: 10.1021/jf2016682. Epub 2011 Aug 3.
The origin and authenticity of feed for laying hens is an important and fraud-susceptible aspect in the production of organic eggs. Chemical fingerprinting in combination with chemometric methods is increasingly used in conjunction with administrative controls to verify and safeguard the authenticity of food commodities. On the basis of fatty acid fingerprinting data of 36 organic and 60 conventional feeds, we have developed a chemometric classification model to discriminate between organic and conventional chicken feed. A two-factor partial least squares-discriminant analysis (PLS-DA) model was developed using 70% of the original data. External validation of the model with the remaining 30% of the data showed that all of the organic feeds and 90% of the conventional feeds (18 of 20) were correctly identified by the model. These results indicate that the PLS-DA model developed in this study could be routinely used to verify the identity of unknown or suspicious feed for laying hens.
蛋鸡饲料的来源和真实性是有机鸡蛋生产中一个重要且容易出现欺诈的方面。化学指纹图谱分析结合化学计量学方法，越来越多地与行政控制相结合，用于验证和保障食品商品的真实性。在对 36 种有机饲料和 60 种常规饲料的脂肪酸指纹图谱数据进行分析的基础上，我们开发了一种化学计量分类模型，用于区分有机和常规鸡饲料。使用原始数据的 70%建立了双因素偏最小二乘判别分析（PLS-DA）模型。用剩余的 30%数据对模型进行外部验证的结果表明，该模型正确识别了所有有机饲料和 90%的常规饲料（20 个中的 18 个）。这些结果表明，本研究中开发的 PLS-DA 模型可常规用于验证未知或可疑蛋鸡饲料的身份。
