Use of piezosensors for determining the composition of the equilibrium gas phase of aqueous protein solutions

Кучменко, Т. А.; Asanova, Yu. A.

doi:10.1134/s1070427209070064

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, chitosan is often used to create biocompatible films that are safe for products, including those commonly distributed in milk [ 43 ], and it has a high sensitivity to ketones and aldehydes [ 44 , 45 ], which are present in the gas phase of milk [ 46 ]. Chromatographic phases were also selected, taking the use of these sorbents in the analysis of aroma-forming components of milk into account [ 47 ]. Deep eutectic solvents were also used to determine the residues of antibiotics and hormones in milk and dairy products [ 48 , 49 ].…”

Section: Methodsmentioning

confidence: 99%

Possibilities of an Electronic Nose on Piezoelectric Sensors with Polycomposite Coatings to Investigate the Microbiological Indicators of Milk

Shuba,

Umarkhanov,

Bogdanova

et al. 2024

Sensors

View full text Add to dashboard Cite

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.

show abstract