电子鼻和电子舌结合模糊数学感官评价优化培根烟熏工艺

doi:10.3864/j.issn.0578-1752.2017.01.014

摘要/Abstract

摘要： 【目的】采用电子鼻嗅问指纹分析、电子舌滋味指纹分析及模糊数学感官评价，选出一种烟熏液使其在合适的添加量下制作的培根能够达到传统木屑烟熏培根的风味，同时探寻利用电子鼻和电子舌法优化培根烟熏工艺的可行性和准确性。【方法】采用电子鼻和电子舌法，通过主成分分析图对3种不同浓度烟熏液制作的培根与传统木屑烟熏的培根从整体气味和滋味上进行对比分析，结合模糊数学感官评价分析并验证电子鼻和电子舌的结果。【结果】对电子鼻数据进行主成分分析，主成分1和2的累积贡献率为99.760%，大于85%，说明主成分1和主成分2已经包含了很大的信息量，能够反映样品的整体信息。4号（3‰名花MH-SO152）样品的分布区域与1号（木屑烟熏）样品的分布区域分离较远，在气味上差别明显。5号（1‰名花SY-SO968）、7号（3‰名花SY-SO968）、9号（2‰金牛山Ⅱ号）和10号（3‰金牛山Ⅱ号）样品的分布区域与1号样品的分布区域分离较近，在气味上它们与1号样品比较接近。6号（2‰名花SY-SO968）样品的分布区域与1号样品的分布区域有部分重叠，说明6号样品在气味上与1号样品基本一致，即添加2‰的广州名花SY-SO968烟熏液制作的培根与传统木屑烟熏的培根在气味上基本一致。对电子舌数据进行主成分分析，主成分1和2的累积贡献率为88.903%，大于85%，能够反映样品的整体信息。2号（1‰名花MH-SO152）、3号（2‰名花MH-SO152）和4号样品的分布区域与1号样品的分布区域分离较远，在滋味上与1号样品差别明显。8号（1‰金牛山Ⅱ号）、9号、10号样品的分布区域与1号样品的分布区域分离较近，在滋味上它们与1号样品比较接近。5号、6号、7号样品的分布区域与1号样品的分布区域分离最近，说明在滋味上它们与1号样品最接近，即添加广州名花SY-SO968烟熏液制作的培根与传统木屑烟熏的培根在滋味上最接近。在培根模糊数学感官评价的综合得分和烟熏风味描述中，1号、6号、7号和10号样品的综合得分比较接近，分值都大于8，评价等级为很好，风味描述都为烟熏味浓郁，口感好。其中，6号样品与1号样品的模糊数学感官评价的综合得分最接近，仅相差0.05，与电子鼻和电子舌法的分析结果基本一致。【结论】通过电子鼻和电子舌法的主成分分析，得出添加2‰广州名花SY-SO968烟熏液制作的培根与木屑烟熏培根在气味上基本一致，在滋味上最接近，可以用来代替传统的木屑烟熏培根。其模糊数学感官评价法的综合得分与木屑烟熏培根最接近，与电子鼻、电子舌法结果基本一致，验证了电子鼻和电子舌法优化培根烟熏工艺的可行性和准确性，从整体风味上为肉制品的生产工艺优化提供了参考。

关键词: 培根, 电子鼻, 电子舌, 模糊数学感官评价法

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

王琼，徐宝才，于海，李聪. 电子鼻和电子舌结合模糊数学感官评价优化培根烟熏工艺[J]. 中国农业科学, 2017, 50(1): 161-170.

WANG Qiong, XU BaoCai, YU Hai, LI Cong. Electronic Nose and Electronic Tongue Combined with Fuzzy Mathematics Sensory Evaluation to Optimize Bacon Smoking Procedure[J]. Scientia Agricultura Sinica, 2017, 50(1): 161-170.

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