Abstract:
For the last 20 years, several applications of electronic nose (e-nose) have
been reported in the area of microbiology, environmental and agricultural
monitoring or medical diagnosis. E-noses were used to detect contaminants
or for quality control. However, little has been reported about complex
methodological problems which are strongly linked to the e-nose
performance.
This thesis summarises various e-nose systems and alternatives for gas and
headspace analysis, highlights the essential problems associated with e-nose
analysis and explains why these devices have a potential for the detection of
trace gas molecules but also why a stable and reliable analysis is not possible
yet. Methodological weaknesses such as changes in mass flow rates, filter
application or sampling methods are addressed. Understanding these
enables analysis of serum and urine samples from cattle or badgers either
naturally or experimentally infected with the zoonotic diseases caused by
Mycoplasma bovis, Mannheimia haemolytica A1, Mycobacterium bovis,
Mycobacterium avium ssp. paraTuberculosis and Brucella sp. The
circumstances under which meaningful results can be obtained using the
ST214 e-nose (Scensive Tech. Ltd., UK) are assessed which show the
current limitations for discriminating between samples. Alternative methods for
analysing e-nose data are mentioned and reasons are given why under the
stated circumstances no straightforward multivariate statistics is possible.
However, despite various difficulties, meaningful results at a group level were
obtained and could be correlated with other results obtained using alternative
analytical methods. This indicates the positive proof-of-principle character of
this project.
