title: Sensing the quality parameters of Chinese traditional Yao-meat by using a colorimetric sensor combined with genetic algorithm partial least squares regression.
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.
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Xiaowei
authors: X
authors: Huang
authors: 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.
authors: Xiaobo
authors: X
authors: Zou
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Jiewen
authors: J
authors: Zhao
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Jiyong
authors: J
authors: Shi
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Xiaolei
authors: X
authors: Zhang
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Zhihua
authors: Z
authors: Li
authors: School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China.
authors: Lecheng
authors: L
authors: Shen
mesh_terms: D000465:Algorithms; D000818:Animals; D002151:Calorimetry / Q000379:methods*; D015169:Colony Count, Microbial; D005516:Food Microbiology; D016018:Least-Squares Analysis; D008460:Meat / Q000032:analysis* / Q000382:microbiology*; D008962:Models, Theoretical; D009573:Nitrites / Q000032:analysis; D013552:Swine; D055549:Volatile Organic Compounds / Q000032:analysis
chemical_list: D009573:Nitrites; D055549:Volatile Organic Compounds
keywords: Colorimetric sensor array chip; Genetic algorithm partial least squares regression; Quality parameters; Yao-meat