Multidimensional Patterns of Gas Sensors for Assessing the Microbiological Indicators of Raw Milk

IF 2.3 4区 化学 Q1 SOCIAL WORK
Anastasiia Shuba, Tatiana Kuchmenko, Ruslan Umarkhanov, Ekaterina Bogdanova, Ekaterina Anokhina, Inna Burakova
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引用次数: 0

Abstract

The paper discusses methods of using chemometrics methods for processing the output data of sensors with polycomposite coatings for analyzing the gas phase of raw milk and obtaining analytical information about its total microbiological contamination, the content of yeast and mold, and the presence of pathogenic microorganisms. To predict microbiological indicators of milk quality, the partial least squares regression and quadratic discriminant analysis were used. The initial data matrix included both an optimized set of sensor output data and calculated parameters at various data fusion levels. It is shown that multidimensional patterns of sensor output data differ depending on the task. A model for predicting the microbiological contamination of milk (QMAFAnM) with an error of 0.342 log CFU was obtained. It was shown that the sensitivity of classification of milk samples by the presence or absence of pathogenic microorganisms using discriminant analysis is 67%, and the specificity is 100% when using the calculated parameters of the sensor array. The proposed approaches can be applicable for processing data from various types of sensors when analyzing real objects with complex compositions.

原料奶微生物指标评价气体传感器的多维模式
本文讨论了用化学计量学方法处理复合涂层传感器输出数据,分析原料奶气相,获得原料奶微生物污染总量、酵母和霉菌含量、病原微生物存在等分析信息的方法。采用偏最小二乘回归和二次判别分析对牛奶品质微生物指标进行预测。初始数据矩阵包括一组优化的传感器输出数据和在不同数据融合水平下计算的参数。结果表明,传感器输出数据的多维模式随任务的不同而不同。建立了牛奶微生物污染预测模型(QMAFAnM),误差为0.342 log CFU。结果表明,利用该传感器阵列计算参数对牛奶样品进行病原微生物存在与否分类的灵敏度为67%,特异性为100%。所提出的方法可适用于分析具有复杂成分的真实物体时处理来自各种类型传感器的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Chemometrics
Journal of Chemometrics 化学-分析化学
CiteScore
5.20
自引率
8.30%
发文量
78
审稿时长
2 months
期刊介绍: The Journal of Chemometrics is devoted to the rapid publication of original scientific papers, reviews and short communications on fundamental and applied aspects of chemometrics. It also provides a forum for the exchange of information on meetings and other news relevant to the growing community of scientists who are interested in chemometrics and its applications. Short, critical review papers are a particularly important feature of the journal, in view of the multidisciplinary readership at which it is aimed.
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