Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

Abstract

The paper demonstrates a new approach to identify healthy calves (“healthy”) and naturally occurring infectious bronchopneumonia (“sick”) calves by analysis of the gaseous phase over nasal secretions using 16 piezoelectric sensors in two portable devices. Samples of nasal secretions were obtained from 50 red-motley Holstein calves aged 14–42 days. Calves were subjected to rectal temperature measurements, clinical score according to the Wisconsin respiratory scoring chart, thoracic auscultation, and radiography (Carestream DR, New York, USA). Of the 50 calves, we included samples from 40 (20 “healthy” and 20 “sick”) in the training sample. The remaining ten calves (five “healthy” and five “sick”) were included in the test sample. It was possible to divide calves into “healthy” and “sick” groups according to the output data of the sensor arrays (maximum sensor signals and calculated parameters Ai/j) using the principal component linear discriminant analysis (PCA–LDA) with an accuracy of 100%. The adequacy of the PCA–LDA model was verified on a test sample. It was found that data of sensors with films of carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, and Triton X-100 had the most significance for dividing samples into groups. The differences in the composition of the gaseous phase over the samples of nasal secretions for such a classification could be explained by the appearance or change in the concentrations of ketones, alcohols, organic carboxylic acids, aldehydes, amines, including cyclic amines or those with a branched hydrocarbon chain.

Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

“…These numbers were calculated automatically by the software [ 57 ]. The description of the basic version of the software was presented in [ 58 ]. The description of kinetic “visual prints” and the principle of choosing a time mask were described in [ 46 , 59 ].…”

Drift Compensation of the Electronic Nose in the Development of Instruments for Out-of-Laboratory Analysis

“…A gaseous phase analysis of distilled water and blood samples was conducted on the gas analyzer Diagnost-Bio-8 (LLC SenSino, Kursk, Russia) using frontal analyte input mode [14]. The sensor array consisted of eight piezoelectrical quartz BAW-type resonators with a 10.0 MHz basic oscillation frequency, with coatings from solid nanostructured sorbents ('living system' set): Sensor 1 and 8 are carboxylated carbon nanotubes of different masses, marked in the tables and text as MCNT1, MCNT2; Sensor 2 and 7 are phases of nitrate of zirconium oxide of different masses (Zr1, Zr2); Sensor 3 is dicyclohexano-18crown-6 (DCH18C6); Sensor 4 and 5 are biohydroxyapatite phases of different masses (HA1, HA2); and Sensor 6 is polyethylene glycol succinate (PEGsc).…”

“…The blood or water sample (volume: 0.5 cm 3 ) was placed on a glass petri plate and then covered by a detection cell of Diagnost-Bio-8. The measurement mode involved combined 80 s sorption and 120 s spontaneous desorption [14].…”

Bovine Respiratory Syncytial Virus (BRSV) Infection Detected in Exhaled Breath Condensate of Dairy Calves by Near-Infrared Aquaphotomics

“…By comparison, analysis using reverse transcription-polymerase chain reaction (RT-PCR), which is currently considered the gold standard for BRSV diagnosis, has 99% sensitivity and specificity [1,3,11]. More recently, analytical techniques such as nuclear magnetic resonance (NMR) and gas chromatography based mass spectrometry (GC-MS) have been used in blood plasma, blood serum, nasal secretions, and exhaled breath condensate to identify biomarkers related to BRDC to create new diagnostic tools that facilitate appropriate treatment [12][13][14][15][16][17].…”