| Title: | Sensing the quality parameters of Chinese traditional Yao-meat by using a colorimetric sensor combined with genetic algorithm partial least squares regression |
| Author(s): | Huang X; Zou X; Zhao J; Shi J; Zhang X; Li Z; Shen L; |
| Address: | "School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China. School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China; Key Laboratory of Modern Agricultural Equipment and Technology, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China. Electronic address: zou_xiaobo@ujs.edu.cn" |
| DOI: | 10.1016/j.meatsci.2014.05.033 |
| ISSN/ISBN: | 1873-4138 (Electronic) 0309-1740 (Linking) |
| Abstract: | "Yao-meat is a traditional Chinese salted meat. Total volatile basic nitrogen content (TVB-N), total viable bacterial count (TVC), and residual nitrite (RN) level are important indexes of freshness for Yao-meat. This paper attempted the feasibility to determine TVB-N content, TVC and RN level in Yao-meat by a colorimetric sensor array chip. A color change profile for each sample was obtained by differentiating the image of sensor array before and after exposure to Yao-meat's volatile organic compounds. Genetic algorithm partial least squares regression (GA-PLS) was proposed to build the relationship between the TVB-N content, TVC, RN and the color change profiles of sensor array, and to select informative chemically responsive dyes for the three quality parameters. The GA-PLS models were achieved with RTVB-N=0.812, RTVC=0.856, RRN=0.855, in prediction set. This study demonstrated that colorimetric sensory array with GA-PLS algorithm could be used successfully to analyze the quality of Chinese traditional Yao-meat" |
| Keywords: | "*Algorithms Animals Calorimetry/*methods Colony Count, Microbial Food Microbiology Least-Squares Analysis Meat/*analysis/*microbiology Models, Theoretical Nitrites/analysis Swine Volatile Organic Compounds/analysis Colorimetric sensor array chip Genetic a;" |
| Notes: | "MedlineHuang, Xiaowei Zou, Xiaobo Zhao, Jiewen Shi, Jiyong Zhang, Xiaolei Li, Zhihua Shen, Lecheng eng Research Support, Non-U.S. Gov't England 2014/06/28 Meat Sci. 2014 Oct; 98(2):203-10. doi: 10.1016/j.meatsci.2014.05.033. Epub 2014 Jun 8" |
