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中国精品科技期刊2020
吴丹丹,其布勒,斯仁达来,等. 电子鼻对驼乳中牛乳掺假的快速检测[J]. 食品工业科技,2021,42(11):263−267. doi: 10.13386/j.issn1002-0306.2020100041.
引用本文: 吴丹丹,其布勒,斯仁达来,等. 电子鼻对驼乳中牛乳掺假的快速检测[J]. 食品工业科技,2021,42(11):263−267. doi: 10.13386/j.issn1002-0306.2020100041.
WU Dandan, QI Bule, SIRendalai , et al. Rapid Detection of Adulteration in Camel Milk by Electronic Nose[J]. Science and Technology of Food Industry, 2021, 42(11): 263−267. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020100041.
Citation: WU Dandan, QI Bule, SIRendalai , et al. Rapid Detection of Adulteration in Camel Milk by Electronic Nose[J]. Science and Technology of Food Industry, 2021, 42(11): 263−267. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020100041.

电子鼻对驼乳中牛乳掺假的快速检测

Rapid Detection of Adulteration in Camel Milk by Electronic Nose

  • 摘要: 为了迅速准确地鉴别掺假骆驼乳的气味特征,本研究以阿拉善双峰骆驼乳为研究对象,驼乳按照不同掺假浓度分为0.1%、1%、3%、5%、10%、15%、20%和100%的牛乳梯度进行制备。根据掺假驼乳的气味特征,通过电子鼻10个传感器和多变量结合分析更快速、准确的评价掺假驼乳。最后,对验证集中的掺假驼乳样品数据进行验证。结果表明:基于电子鼻对掺假乳样挥发性成分响应值的前两个主成分为85.1%、偏最小二乘判别模型的相关系数为R2X=0.842,R2Y=0.628,Q2=0.618;揭示电子鼻可有效区分驼乳或掺假驼乳样品,且检测驼乳中牛乳掺假的最低检测限为1%,影响驼乳气味识别的关键电子鼻传感器为W5S传感器。此外,验证集掺假乳样PLS-DA模型的相关系数为R2X=0.81,R2Y=0.659,Q2=0.641;结果进一步证实了电子鼻用于鉴别驼乳气味的有效性。综上,本研究采用电子鼻技术实现了对驼乳中牛乳掺假后气味特征的快速、准确鉴别,为后续掺假驼乳气味特征成分的研究提供理论依据,同时也为其它食品类的掺假检测提供一种参考价值。

     

    Abstract: In order to more quickly and accurately identify the odor characteristics of adulterated camel milk, this research takes ALaShan Bactrian camel milk as the object. The milk is prepared according to different adulteration concentrations into 0.1%, 1%, 3%, 5%, 10%, 15%, 20% and 100% milk gradients.According to the odor characteristics of adulterated camel milk, the evaluation of adulterated camel milk can be made more quickly and accurately through 10 electronic nose sensors and multivariate analysis.Finally, the data analysis of adulterated camel milk samples in the validation set was verified. The results showed that based on the response value of the electronic nose to the volatile components of adulterated milk samples, the first two principal components are 85.1%, and the correlation coefficient of the partial least squares discriminant model was R2X=0.842, R2Y=0.628, Q2=0.618. It was revealed that the electronic nose could effectively distinguish camel milk or adulterated camel milk samples, and the minimum detection limit for detecting adulterated milk in camel milk was 1%. The key electronic nose sensor that affects camel milk odor recognition was the W5S sensor. In addition, the correlation coefficients of the PLS-DA model of adulterated milk samples in the validation set were R2X=0.81, R2Y=0.659, Q2=0.641. The results further confirmed the effectiveness of the electronic nose for identifying the smell of camel milk. In summary, electronic nose technology was used to achieve rapid and accurate identification of odor characteristics of camel milk mixed with cow milk in this study, which provides a theoretical basis for the subsequent research on the odor characteristics of camel milk adulteration, and also for adulteration of other foods.

     

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