Identification of different brands of vinegar by electronic nose
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摘要: 以东湖陈醋、水塔米醋、海天白米醋、恒顺香醋、水塔陈醋、紫林陈醋六种食醋为实验材料,利用电子鼻技术对其挥发性成分进行检测,采用径向基函数神经网络和Fisher判别建立其预测模型。结果表明:传感器S7、S3对六种样品的响应值差异显著(p<0.05),即六种食醋的硫化氢、氨类物质的含量差异显著(p<0.05)。同时线性判别分析比主成分分析能更好地区分不同品牌的食醋。Fisher判别和径向基函数神经网络模型均能较好地预测不同品牌的食醋,但Fisher判别的效果更好,对六种食醋的正确判别率均为100%。由此说明利用电子鼻技术能实现食醋种类的快速识别,以维护食醋品牌的名誉和规范市场。Abstract: The electronic nose was used to measure the volatile compounds of different vinegars, including Eastlake vinegar, Shuita rice vinegar, Haitian rice vinegar, Hengshun aromatic vinegar, Shuita mature vinegar and Zilin mature vinegar.The radial basis function ( RBF) neural network and Fisher discriminant were applied to predict different brands of vinegar. The results showed that the response values of sensors S7 and S3 changed significantly ( p < 0.05) among different samples.That meant the contents of ammonia and hydrogen sulfide had significant differences among six kinds of vinegar.Moreover, linear discriminant analysis could better distinguish different brands of vinegar than principal component analysis. Both Fisher discriminant and RBF were able to predict different brands of vinegar.In contrast, Fisher discriminant had more accurate prediction. The correct discriminant rate of Fisher model was 100%. Therefore, the electronic nose could identify the brands of vinegar, maintain the brand reputation of vinegar and regulate the market.
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Keywords:
- electronic nose /
- vinegar /
- brand
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