利用电子鼻响应结合理化方法检测贮藏过程中花生的内部品质。

Detecting internal quality of peanuts during storage using electronic nose responses combined with physicochemical methods.

机构信息

Department of Biosystems Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China.

出版信息

Food Chem. 2015 Jun 15;177:89-96. doi: 10.1016/j.foodchem.2014.12.100. Epub 2015 Jan 6.

DOI:10.1016/j.foodchem.2014.12.100

Abstract

In this study, the changes in the quality of unshelled peanuts and peanut kernels during storage were analyzed using an electronic nose (e-nose). The physicochemical indexes (acid and peroxide values) of peanut kernels were tested by traditional method as a reference. The storage time of peanut kernels increases from left to right in the cluster analysis plot based on the physicochemical indexes. The "maximum values", "area values", and "70th s values" methods were applied to extract the feature data from the e-nose responses. Principal component analysis (PCA) results indicated that the "70th s values" method produced the most accurate results, furthermore, unshelled peanut and peanut kernel samples presented similar characteristics in the PCA plots; the partial least squares regression (PLSR) results showed that the features of unshelled peanuts and peanut kernels are highly correlated with acid and peroxide values, respectively.

摘要

本研究采用电子鼻（e-nose）分析了未去壳花生和花生仁在贮藏过程中的品质变化。用传统方法检测了花生仁的理化指标（酸值和过氧化值）作为参考。基于理化指标的聚类分析图中，花生仁的贮藏时间从左到右逐渐增加。从电子鼻响应中提取特征数据时应用了“最大值”、“面积值”和“70 秒值”方法。主成分分析（PCA）结果表明，“70 秒值”方法得出的结果最准确，此外，未去壳花生和花生仁样品在 PCA 图中呈现出相似的特征；偏最小二乘回归（PLSR）结果表明，未去壳花生和花生仁的特征与酸值和过氧化值高度相关。