Analysis of the volatile compounds’ condensate exhaled air 'electronic nose' based on piezoelectric sensor to assess the status of calves

Autor: E S Dorovskaya, Anastasiia Shuba, A E Chernitskiy, Tatiana Kuchmenko, Ruslan Umarkhanov
Rok vydání: 2021
Předmět:
Zdroj: IOP Conference Series: Earth and Environmental Science. 640:072028
ISSN: 1755-1315
1755-1307
DOI: 10.1088/1755-1315/640/7/072028
Popis: The article discusses general principles of obtaining diagnostic information using eight chemical piezoelectric gas sensors with nanostructural coverings from exhaled breath condensate for health assessment of the upper respiratory tract of pre-month-old calves. Multidimensional information of an e-nose can be presented in various numeric and visualized matrices, characteristics of which are an integral analytical signal of the sensor array. The research devoted to the search for the techniques of extracting analytical information from multidimensional e-nose data to assess upper respiratory tract state from the appearance of the first sign of respiratory disease to tracheobronchitis and bronchopneumonia. The piezoelectric sensor array is characterized by high sorption activity with priority biomolecules (which are the markers of the abnormal metabolic processes), low cost along with reliable repeatability of sorption properties from batch to batch, the simplicity of application, and fast response and recovery time. Here we present the results of simple algorithms used for assessment of upper respiratory tract state by a 2-minute analysis of odour over 1-ml biosample without sample preparation. It was shown that traditional quantitative parameters of e-nose are not adequate for simultaneous sample grouping and volatile compounds qualitative composition establishing. The additionally calculated sorption parameters Aij are more informative in the analysis of biosamples volatile: using for identification of volatile biomarkers, describe the health state correlating with clinical diagnosis. The sequence of information processing: signals of each sensor, integral characteristic, “visual prints,” additional sorption parameters–allows assessing the calf health virtually in situ without transporting samples to specialized laboratories.
Databáze: OpenAIRE
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