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/z55～191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 hquor 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.
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