Grey Correlation Degree for Analysis of the Correlation between Electronic Nose Responses to Meat Flavors and Their Sensory Scores
WEI Daiwei, WEI Chaokun*, ZHANG Huiling
Ningxia Key Laboratory of Food Microbial Application Technology and Safety Control, College of Food and Wine, Ningxia University, Yinchuan 750000, China
Abstract：To develop an objective evaluation method for meat flavors, electronic nose responses were employed as objective evaluation measures to compensate for the disadvantages of traditional sensory evaluation, such as strong randomness as well as poor repeatability and stability. In this study, Maillard reaction was used to prepare two meat flavors: barbecue-like and broth-like, and the correlation between sensory evaluation and electronic nose responses was established by using grey correlation degree, principal component analysis (PCA), and analysis of variance (ANOVA). The results showed that through Maillard reaction with 10.00 g/100 mL of glutamic acid, a strong broth-like flavor was obtained, and the sensors W5S, W6S, W1S, W1W, and W2S had higher response values to the broth-like flavor, and their correlation coefficients with the sensory evaluation scores were 0.738, 0.803, 0.822, 0.825 and 0.864, respectively; when 3.33 g/100 mL of glutamic acid was added to the reaction system, a strong barbecue-like flavor was obtained, and the sensors W5S, W6S, W1S, and W1W had higher response values to the barbecue-like flavor, and their correlation coefficients with the sensory evaluation scores were 0.744, 0.835, 0.847, and 0.854, respectively. On this basis, a regression model was developed between the correlation coefficients of the sensor response values with higher grey correlation degree and the sensory scores, which had excellent goodness of fit.
魏代巍，魏超昆，张惠玲. 基于灰色关联度分析肉味香精电子鼻响应值与感官评分之间的相关性[J]. 肉类研究, 2022, 36(5): 49-53.
WEI Daiwei, WEI Chaokun*, ZHANG Huiling. Grey Correlation Degree for Analysis of the Correlation between Electronic Nose Responses to Meat Flavors and Their Sensory Scores. Meat Research, 2022, 36(5): 49-53.
2022, Vol. 36 
