电子鼻对不同存储时间纯牛奶的检测分析

利用电子鼻系统的气体传感器阵列对牛奶的响应曲线特征值来表示牛奶新鲜度变化,采用SPSS中逐步判别对特征进行优化,分别用最小二乘法和Bayes判别算法分析牛奶新鲜度变化情况。结果表明:逐步判别法能有效地降低数据维数,Bayes判别法和偏最小二乘法相比,把数据分布密度函数加入牛奶新鲜度识别中,提高了电子鼻对牛奶新鲜度的识别的正确率,Bayes判别法能鉴别出存储间隔12 h的商品纯牛奶新鲜度的变化。因此,利用电子鼻和Bayes判别算法是分析牛奶新鲜度的一种有效的手段。

Critical analysis of electronic nose on pure milk of different storage time

A gas sensor array of electronic nose system is used to characteristic values of response curves to detect the freshness change of milk.Stepwise discriminant analysis of SPSS is used to optimize the characteristics,and least squares method and the Bayes discriminant algorithm are used to analyze changes of milk freshness respectively.The results show that stepwise discrimination method can effectively reduce data dimension numbers. Compared with the partial least squares method,the Bayes discriminant algorithm adds data distribution density function to recognize milk freshness,the correctness rate of the recognition is improved.The Bayes algorithm can discriminate the change of freshness of pure milk of goods which are in the storage interval of 12 h.So it is an effective method to analyze the change of milk freshness with an electronic nose and the Bayes discriminant algorithm.