Abstract: 【Objective】Using Electronic Nose (E-nose), Electronic tongue (E-tongue) and Fuzzy Mathematics Sensory Evaluation to pick out a bacon smoked by a certain brand and concentration of smoking liquid which resembles the traditional wood chips smoking bacon in flavor, and study the feasibility and accuracy of optimizing the bacon smoking procedure with E-nose and E-tongue. 【Method】Bacons made with three brands and three concentrations of smoking liquid and traditional wood chips smoking were analyzed by E-nose and E-tongue and verified with fuzzy mathematics sensory evaluation.【Result】After analyzing the E-nose Principle Component Analysis (PCA) chart, the accumulating contribution of Principle Components (PC) 1 and 2 is 99.760%, much larger than 85%, which means PC1 and PC2 have contained enough information to reflect the whole sample information. The distribution areas of sample 4 (3‰ Minghua MH-SO152) and sample 1 (woodchips smoked) are obviously separated, which suggests that the odor of the two samples are clearly different. However, the distribution areas of sample 5 (1‰ Minghua SY-SO968), sample 7 (3‰ Minghua SY-SO968), sample 9 (2‰ Jinniushan Ⅱ), and sample 10 (3‰ Jinniushan Ⅱ) are close to that of sample 1, which means their smell is close to sample 1 as well. The distribution areas of sample 6 (2‰ Minghua SY-SO968) and sample 1 overlap partially, which means the smell of sample 6 (2‰ Minghua SY-SO968) and sample 1 (wood chips smoked) are basically the same, thus the bacon added with 2‰ Guangzhou Minghua SY-SO968 smoking liquid smells basically the same as the traditional one. By analyzing the E-tongue Principle Component Analysis (PCA) chart, the accumulating contribution of Principle Components 1 and 2 is 88.903%, larger than 85%, enough to reflect the general sample information. The distribution areas of sample 2 (1‰ Minghua MH-SO152), sample 3 (2‰ Minghua MH-SO152) and sample 4 (3‰ Minghua MH-SO152) are far away from sample 1, which shows that their taste can be effectively distinguished from woodchips smoked sample 1. And the distribution areas of sample 8 (1‰ JinniushanⅡ), sample 9 (2‰ Jinniushan Ⅱ) and sample 10 (3‰ Jinniushan Ⅱ) locate near sample 1, thus they taste relatively like sample 1. The distribution areas of samples 5 (1‰ Minghua SY-SO968), 6, and 7 (3‰ Minghua SY-SO968) are closest to sample 1, which means they taste closest to sample 1, thus the bacons added with Guangzhou Minghua SY-SO968 smoking liquid taste closest to the traditional one. In Fuzzy Mathematic Sensory Evaluation and flavor description, the comprehensive scores of samples 1, 6, 7 and 10 (3‰ Jinniushan Ⅱ) are close and higher than sample 8, and described as heavy smoking flavor and good taste. The Fuzzy Mathematic Sensory Evaluation score of sample 6 is closest to sample 1, and the difference is merely 0.05, which verifies the E-nose and E-tongue results.【Conclusion】After analyzing the E-nose and E-tongue Principle Component Analysis charts, the bacon added with 2‰ Guangzhou Minghua SY-SO968 smoking liquid smells basically the same as the traditional one, and tastes closest as well, which means it can be used to replace the traditional smoking technique. Fussy mathematics sensory evaluation scores verified the fact and proved E-nose and E-tongue can be used to optimize bacon smoking procedure efficiently, thus provides a reference method to optimize meat production technique from flavor perspective. 

Key words: bacon, electronic nose, electronic tongue, fuzzy mathematics sensory evaluation