Several parameters for improving volatile metabolite analysis using headspace gas chromatography-mass spectrometry (GC-MS) analysis of volatile metabolites were evaluated in the framework of identification of mastitis-causing pathogens. Previous research showed that the results of such volatile metabolites analysis were comparable with those based on bacteriological culturing. The aim of this study was to evaluate the effect of several method changes on the applicability and potential implementation of this method in practice. The use of a relatively polar column is advantageous, resulting in a faster and less complex chromatographic setup with a higher resolving power yielding higher-quality data. Before volatile metabolite analysis is applied, a minimum incubation of 8h is advised, as reducing incubation time leads to less reliable pathogen identification. Application of GC-MS remained favorable compared with regular gas chromatography. The complexity and cost of a GC-MS system are such that this limits the application of the method in practice for identification of mastitis-causing pathogens.
Keywords: artificial neural network; incubation; mastitis; metabolites; pathogens.
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