Prediction of total viable counts on chilled pork using an electronic nose combined with support vector machine

被引：81

作者：

Wang, Danfeng ^{[1
]}

Wang, Xichang ^{[1
]}

Liu, Taiang ^{[2
]}

Liu, Yuan ^{[1
]}

机构：

[1] Shanghai Ocean Univ, Coll Food Sci & Technol, Shanghai 201306, Peoples R China

[2] Shanghai Univ, Dept Chem, Coll Sci, Shanghai 200444, Peoples R China

来源：

MEAT SCIENCE | 2012年 / 90卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Pork; Electronic nose; Total viable counts; Prediction; Support vector machine; SPOILAGE CLASSIFICATION; QUALITY ASSESSMENT; FILLETS; BEEF; PCA;

D O I：

10.1016/j.meatsci.2011.07.025

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

The aim of this study was to predict the total viable counts (TVC) in chilled pork using an electronic nose (EN) together with support vector machine (SVM). EN and bacteriological measurements were performed on pork samples stored at 4 degrees C for up to 10 days. Bacterial numbers on pork were determined by plate counts on agar. Principal component analysis (PCA) was used to cluster EN measurements. The model for the correlation between EN signal responses and bacterial numbers was constructed by using the SVM, combined with partial least squares (PLS). Correlation coefficients for training and validation were 0.94 and 0.88, respectively, which suggested that the EN system could be used as a simple and rapid technique for the prediction of bacteria numbers in pork. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：373 / 377

页数：5

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