提高食醋电子鼻识别率方法的研究

以两种不同品牌的山西食醋为样品，通过对电子鼻测定数据的区间分析，确定样品处理方式，并采用正交试验方法对传感器的选用进行优化并建立模板；用欧氏距离、相关性、马氏距离和判别函数分析同时鉴别新样品的归属，误判率明显降低（由18.2%降低为5.4%），识别率得到较大提高（由81.8%提高至94.6%）。

Method improvement of vinegar identification rate by electronic nose

Using two different brands of Shanxi vinegar as samples, through the range analysis of determination data by electronic nose, the sample handling methods were determined, the sensors performance parameters were optimized by orthogonal experiment, and template was established. The new samples affiliations were simultaneous identified by Euclid distance, correlation, Mahalanobis distance and discriminate function analysis. Results showed that the misjudgment rate decreased from 18.2% to 5.4%, and the recognition rate increased from 81.8% to 94.6%.