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当前位置: 首页 > 文章 > 电子鼻结合化学计量法对羊奶中蛋白质掺假的识别 食品科学 2017,38 (8) 308-312
Position: Home > Articles > Recognition of Goat Milk Adulterated with Proteins Using Electronic Nose Combined with Chemometric Methods FOOD SCIENCE 2017,38 (8) 308-312

电子鼻结合化学计量法对羊奶中蛋白质掺假的识别

作  者：
贾茹;张娟;王佳奕;丁武
单  位：
西北农林科技大学食品科学与工程学院
关键词：
羊奶;蛋白质掺假;电子鼻;化学计量法
摘  要：
利用电子鼻结合化学计量法对羊奶中的蛋白质掺假进行定性和定量的研究。用电子鼻检测掺入了不同蛋白质物质的羊奶,采用主成分分析、线性判别分析对电子鼻响应值进行定性分析,采用线性回归分析、Fisher判别分析以及K-最邻近值分析对电子鼻响应值进行定量分析。结果表明:主成分分析和线性判别分析都能够区分不同类别的掺假样品。线性回归分析的决定系数为84.5%,表明回归方程估测可靠程度较高。Fisher判别分析的原始分类的正确率达到100.0%,交叉验证的正确率为98.2%,说明其预测结果较好。K-最邻近值分析对训练集的分类正确率达到95.1%,对验证集的分类正确率为97.1%,说明模型的预测结果良好。说明应用电子鼻技术检测羊奶中的蛋白质掺假具有一定的可行性。
译  名：
Recognition of Goat Milk Adulterated with Proteins Using Electronic Nose Combined with Chemometric Methods
作  者：
JIA Ru;ZHANG Juan;WANG Jiayi;DING Wu;College of Food Science and Engineering,Northwest A&F University;
关键词：
goat milk;;protein adulteration;;electronic nose;;chemometric methods
摘  要：
Goat milk adulterated with proteins was qualitatively discriminated and quantitatively analyzed using electronic nose combined with chemometric methods. Milk samples adulterated with different proteins were detected by electronic nose and then the response values were analyzed qualitatively by principal component analysis(PCA), and linear discriminant analysis(LDA) and quantitatively by linear regression analysis, Fisher discriminant analysis(FDA) and K nearest neighbor(KNN) analysis. The results showed that PCA and LDA were able to distinguish different adulterants. The determination coefficient of linear regression analysis was 84.5%, indicating high reliability of the regression equation. The accuracy of the original classification by FDA reached 100.0%, and the accuracy of cross validation was 98.2%, indicating good predication performance. The classification accuracy of the training set by KNN analysis was 95.1%, and the classification accuracy of the validation set was 97.1%, indicating good prediction performance of the model. All of these results showed that it is feasible to apply electronic nose technology in recognition of protein adulteration in goat milk.

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