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Abstract：
Milk and dairy products are included in the list of the Food Security Doctrine and are of paramount importance in the diet of the human population. At the same time, the presence of many macro- and microcomponents in milk, as available sources of carbon and energy, as well as the high activity of water, cause the rapid development of native and pathogen microorganisms in it. The goal of the work was to assess the possibility of using an array of gas chemical sensors based on piezoquartz microbalances with polycomposite coatings to assess the microbiological indicators of milk quality and to compare the microflora of milk samples. Piezosensors with polycomposite coatings with high sensitivity to volatile compounds were obtained. The gas phase of raw milk was analyzed using the sensors; in parallel, the physicochemical and microbiological parameters were determined for these samples, and species identification of the microorganisms was carried out for the isolated microorganisms in milk. The most informative output data of the sensor array for the assessment of microbiological indicators were established. Regression models were constructed to predict the quantity of microorganisms in milk samples based on the informative sensors\' data with an error of no more than 17%. The limit of determination of QMAFAnM in milk was 243 ± 174 CFU/cm3. Ways to improve the accuracy and specificity of the determination of microorganisms in milk samples were proposed.
摘要：
牛奶和乳制品被列入粮食安全原则清单，在人类的饮食中至关重要。同时,牛奶中存在许多宏观和微观成分，作为碳和能源的可用来源，以及水的高活性，导致其中原生微生物和病原微生物的快速发展。这项工作的目的是评估使用基于压电石英微天平和多复合涂层的气体化学传感器阵列来评估牛奶质量的微生物指标并比较牛奶样品的微生物区系的可能性。获得了具有对挥发性化合物高灵敏度的多复合涂层的压电传感器。使用传感器分析原料奶的气相；并行，确定了这些样品的物理化学和微生物参数，并对乳中分离出的微生物进行了种类鉴定。建立了用于评估微生物指标的传感器阵列的最有用的输出数据。基于信息传感器数据构建回归模型来预测牛奶样品中微生物的数量，误差不超过17%。牛奶中QMAFAnM的检出限为243±174CFU/cm3。提出了提高牛奶样品中微生物测定准确性和特异性的方法。
