文献类型：期刊文献

英文题名：Rapid identification of adulterated cow milk by non-linear pattern recognition methods based on near infrared spectroscopy

作者：Zhang, Li-Guo[1];Zhang, Xin[2];Ni, Li-Jun[1];Xue, Zhi-Bin[1];Gu, Xin[2];Huang, Shi-Xin[2]

机构：[1]E China Univ Sci & Technol, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China;[2]Shanghai Municipal Control Inst Vet Drug & Feedst, Shanghai 201103, Peoples R China

年份：2014

卷号：145

起止页码：342

外文期刊名：FOOD CHEMISTRY

收录：;EI(收录号：20133916791574);WOS:【SCI-EXPANDED(收录号:WOS:000327685200047)】；

语种：英文

外文关键词：Rapid identification of adulterated cow milks; Near infrared spectroscopy; Uniform design; Improved support vector machine; Improved and simplified K nearest neighbours

摘要：More than 800 representative milk samples, which consisted of 287 raw cow milk samples from different pastures surrounding Shanghai of China and 526 adulteration milk samples containing different pseudo proteins and thickeners, were collected and designed to demonstrate a method for rapidly discriminating adulterated milks based on near infrared (NIR) spectra. The NIR classification models were built by two non-linear supervised pattern recognition methods of improved support vector machine (I-SVM) and improved and simplified K nearest neighbours (IS-KNN). Uniform design theory was applied to optimize the parameters of SVM and thus the computation amount was reduced 90%. Both two methods exhibit good adaptability in discriminating adulterated milks from raw cow milks. Further investigation showed that the correction ratio for discriminating milk samples increased with the increasing of adulteration solutions' level in the adulterated milk. The concentration of adulterants is an important factor of influencing milk discrimination results of the NIR pattern recognition models. The results demonstrated the usefulness of NIR spectra combined with non-linear pattern recognition methods as an objective and rapid method for the authentication of complicated raw cow milks. (C) 2013 Elsevier Ltd. All rights reserved.