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首页> 外文期刊>International journal of food science & technology >Discrimination of pork/chicken adulteration in minced mutton by electronic taste system
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Discrimination of pork/chicken adulteration in minced mutton by electronic taste system

机译:用电子味觉系统鉴别羊肉中的猪肉/鸡肉掺假

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摘要

The adulteration of minced mutton was studied by an electronic taste system with cross-sensitive sensor array, providing a global liquid and taste perception to soluble flavour compounds in meat. The responses of taste sensors to adulterated mutton were collected, and analysed by multivariate data analysis methods. For discrimination of meat species and adulterated mutton with different content of pork/chicken, canonical discriminant analysis (CDA) and bayes discriminant analysis (BDA) and principle component analysis (PCA) were employed. The PCA and CDA results showed that meat of different species could be distinguished by E-tongue responses. The CDA and BDA results showed effective classification results. For prediction of pork/chicken content in adulterated mutton, Multiple linear regression (MLR), Partial least square analysis (PLS) and Least Squares Support Vector Machines (LS-SVM) were used, and the results were compared, finding that LS-SVM was proved to be the most effective method for the prediction of pork/chicken content.
机译:通过带有交叉敏感传感器阵列的电子味觉系统研究了切碎的羊肉的掺假情况,从而为肉类中的可溶风味化合物提供了全面的液体和味道感知。收集味觉传感器对掺假羊肉的反应,并通过多元数据分析方法进行分析。为了区分不同猪肉/鸡肉含量的肉类和adult杂羊肉,采用了标准判别分析(CDA)和贝叶斯判别分析(BDA)和主成分分析(PCA)。 PCA和CDA结果表明,可以通过电子舌反应区分不同种类的肉。 CDA和BDA结果显示出有效的分类结果。为了预测掺假羊肉中猪肉/鸡肉的含量,使用了多元线性回归(MLR),偏最小二乘分析(PLS)和最小二乘支持向量机(LS-SVM),并对结果进行了比较,发现LS-SVM被证明是预测猪肉/鸡肉含量的最有效方法。

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