Application of linear/non-linear classification algorithms in discrimination of pork storage time using Fourier transform near infrared (FT-NIR) spectroscopy

作     者：Chen, Quansheng Cai, Jianrong Wan, Xinmin Zhao, Jiewen 

作者机构：Jiangsu Univ Sch Food & Biol Engn Zhenjiang 212013 Jiangsu Provinc Peoples R China 

出 版 物：《LWT-FOOD SCIENCE AND TECHNOLOGY》 (LWT)

年 卷 期：2011年第44卷第10期

页      面：2053-2058页

核心收录：

学科分类：0832[工学-食品科学与工程（可授工学、农学学位）] 08[工学] 

基　　金：Natural and Science Foundation of Jiangsu Province [BK2009216] China Postdoctoral Science Foundation [201003559, 20090461071] Priority Academic Program Development of Jiangsu Higher Education Institutions 

主　　题：Pork Storage time Determination FT-NIR spectroscopy Classification algorithm 

摘      要：To address the rapid and nondestructive determination of pork storage time associated with its freshness, Fourier transform near infrared (FT-NIR) spectroscopy technique, with the help of classification algorithm, was attempted in this work. To investigate the effects of different linear and non-linear classification algorithms on the discrimination results, linear discriminant analysis (LDA), K-nearest neighbors (KNN), and back propagation artificial neural network (BP-ANN) were used to develop the discrimination models, respectively. The number of principal components (PCs) and other parameters were optimized by cross-validation in developing discrimination models. Experimental results showed that the performance of BP-ANN model was superior to others, and the optimal BP-ANN model was achieved when 5 PCs were included. The discrimination rates of the BP-ANN model were 99.26% and 96.21% in the training and prediction sets, respectively. The overall results sufficiently demonstrate that the FT-NIR spectroscopy technique combined with BP-ANN classification algorithm has the potential to determine pork storage time associated with its freshness. (C) 2011 Elsevier Ltd. All rights reserved.