食品科学 ›› 2019, Vol. 40 ›› Issue (16): 177-184.doi: 10.7506/spkx1002-6630-20180923-244

• 成分分析 • 上一篇    下一篇

基于电子鼻的红肠风味评价

杨 鑫,郑丽敏,杨 璐   

  1. 1.中国农业大学信息与电气工程学院,北京 100083;2.食品质量与安全北京实验室,北京 100083
  • 出版日期:2019-08-25 发布日期:2019-08-26
  • 基金资助:
    “十三五”国家重点研发计划重点专项(2016YFD0401504);生猪产业技术体系北京市创新团队项目(BAIC02-2018)

Evaluation of Red Sausage Flavor Based on Electronic Nose

YANG Xin, ZHENG Limin, YANG Lu   

  1. 1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China; 2. Beijing Laboratory of Food Quality and Safety, Beijing 100083, China
  • Online:2019-08-25 Published:2019-08-26

摘要: 为应用电子鼻快速、客观地评价红肠风味,使用电子鼻以及顶空固相微萃取和气相色谱-质谱联用对3 个不同生产批次的各批次3 种不同红肠中挥发性物质进行检测分析,并对其进行感官指标评定。采用支持向量机方法对不同红肠样品的电子鼻数据进行识别分类;利用相对气味活度值确定不同红肠中的关键风味物质;用主成分分析方法对红肠挥发性物质整体分析;利用正交偏最小二乘判别分析方法对电子鼻传感器和红肠关键风味的相关性进行分析,并使用逐步回归建立电子鼻与关键风味物质和感官评价指标数据的回归模型。通过支持向量机分析结果可知,电子鼻对不同种类红肠以及不同生产批次同种类红肠均具有良好的区别能力;气相色谱-质谱联用检测出不同种类化合物共117 种;通过相对气味活度值可知不同红肠中的关键风味物质种类差异较大,仅烯丙硫醇是各红肠的共有关键风味物质;主成分分析表明不同种类红肠在总体风味成分上明显不同;感官分析表明不同红肠在不同口感风味评价上存在差异,烟熏味和咸味为红肠最主要的风味;正交偏最小二乘判别分析显示电子鼻传感器数据与关键风味物质具有良好的相关性;建立电子鼻与关键风味物质和感官评价指标回归模型(R2>0.8,P<0.01)表明应用电子鼻可以对红肠风味进行评价预测分析。

关键词: 红肠风味, 电子鼻, 风味物质, 气相色谱-质谱法, 相对气味活度值, 感官评价

Abstract: This study was devised to rapidly and objectively evaluate the flavor of red sausages using an electronic nose. A total of 9 samples of three kinds of sausages were collected from three batches for each and their volatile components were identified using head space solid phase micro extraction (HS-SPME) followed by gas chromatography-mass spectrometry (GC-MS). Both sensory evaluation and an electronic nose were used to evaluate the flavor attributes of sausages. The ability of the electronic nose to differentiate sausages was evaluated by support vector machine (SVM). Relative odor activity value (ROAV) was used to evaluate the critical flavor compounds in different sausages. The volatile components were recognized by principal components analysis (PCA). The correlation between critical flavor components and the electronic nose was established by orthogonal partial least squares discrimination analysis (OPLS-DA). Regression models between the electronic nose and critical flavor compounds and sensory evaluation were established by stepwise regression. According to the SVM results, the electronic nose had good distinguishing ability for different kinds of sausages and different batches of the same kind of sausage. A total of 117 volatile flavor compounds were identified in all the sausages. According to the ROAV, the critical flavor substances in different sausages varied widely. Allyl mercaptan was the only critical flavor substance found in each sausage. PCA showed that different kinds of sausages were significantly different in overall flavor components. Sensory analysis showed that there were differences in the taste and flavor of different sausages, and the smoky and salty tastes were the most i mportant flavors. The OPLS-DA showed that the electronic nose sensor data showed a good correlation with the critical flavor substances; the regression models between the electronic nose and critical flavor substances and sensory attributes (R2 > 0.8, P < 0.01) indicated that the electronic nose could evaluate and predict the flavor of sausage s.

Key words: red sausage flavor, electronic nose, flavor compounds, gas chromatography-mass spectrometry (GC-MS), relative odor activity value (ROAV), sensory evaluation

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