不同等级白酒的鉴别对控制白酒质量和保护消费者权益有重要意义,运用顶空固相微萃取质谱(HS-SPME-MS)技术获取3个不同等级的120个洋河大曲酒样质荷比m/z 55～191范围内的离子丰度值数据,结合偏最小二乘-判别分析和逐步线性判别分析法筛选出14个重要特征离子,且交叉验证的预测准确率达100%;然后将筛选出的14个特征离子作网络输入层,酒样的不同等级做网络输出层,构建神经网络等级鉴别模型,其在±0.3的误差范围内,预测准确率达100%,实现了白酒等级的数字化鉴别。

Grade discrimination of Chinese liquor was benefit for controlling liquor quality and safeguarding the interests of consumers.In the study,the abundance of ions mass-to-charge ratio(m/z) ranging from 55 to 191 of 120 Yanghe Daqu liquor samples were easily collected by the headspace(HS)-solid phase microextraction(SPME)-mass spectrometry(MS) technique,without pre-treatment or chromatographic separation.By combination of partial least squares discriminant analysis(PLS-DA) and stepwise linear discriminant analysis(SLDA) method,14 characteristic ions were finally picked out and the prediction accuracy of cross validation was up to 100%.And then an artificial neural network(ANN) recognition model using the 14 ions as inputs and different grades as outputs was built,whose prediction accuracy was up to 100% within the error range of ±0.3.