基于电子舌技术不同超声处理时间的奶酪滋味区分  

Discriminating the Taste of Cheese under Different Ultrasonic Treatment Durations by Using Electronic Tongue

作　　者：丛艳君[1,2] 易红[1,3] 郑福平[1,2] 

机构地区：[1]北京工商大学食品学院,北京100048 [2]北京工商大学北京市食品风味化学重点实验室,北京100048 [3]北京工商大学食品添加剂与配料北京市高校工程研究中心,北京100048

出　　处：《食品科学》2015年第6期114-118,共5页Food Science

基　　金：国家自然科学基金青年科学基金项目(31101236);国家高技术研究发展计划(863计划)项目(2011AA100903);北京市自然科学基金项目(6132004);北京市科技新星计划项目(Z131102000413005)

摘　　要：为探讨奶酪智能化品质评价的可行性,研究了电子舌专一选择型传感器检测5种传统奶酪和2种进口奶酪过程中的响应信号的特征。采用不同的模式识别方法对奶酪进行分类鉴别,通过主成分分析(principal component analysis,PCA)法、偏最小二乘法将感官评定值与响应值做相关性分析,并探讨了超声处理奶酪对电子舌响应信号的影响。结果表明:应用PCA能够大体反映各类样品的分类信息,PCA降维后的数据能够很好地反映原始数据信息。奶酪的前处理时间不同电子舌传感器的响应值也不同,本实验超声处理条件下对PCA辨别结果影响不大,UMS、GPS和SPS三根传感器与苦、咸味,以PC1为轴呈显著负相关,SWS与甜味以PC2为轴呈正相关。This paper aimed to study the feasibility of quality assessment of cheeses taste by using electronic tongue. Five traditional cheeses and two import cheeses were tested. Simultaneously, the influence of ultrasonic treatment on sensor response signals was studied. The cheeses were discriminated by different pattern recognition methods. Partial least squares regression(PLSR) and principal component analysis(PCA) were used to establish the relationship between sensor signals and the total taste score value of cheeses. Results showed that PCA could provide general classification information on the various cheese samples and the reduced dimension data provided enough information on the raw data. The ultrasonic processing significantly affected the sensor signals. The signals of sensors named as UMS, GPS, and SPS all correlated negatively with bitterness and saltiness based on principal component 1(PC1), and the response of SWS sensor positively with sweetness based on PC2. The results will provide a basic for the intelligent evaluation of cheese quality.

关 键 词：电子舌 奶酪 滋味 模式识别 感官评定 

分 类 号：TS252.7[轻工技术与工程—农产品加工及贮藏工程]