期刊
JOURNAL OF DAIRY SCIENCE
卷 92, 期 10, 页码 4901-4905出版社
ELSEVIER SCIENCE INC
DOI: 10.3168/jds.2008-1818
关键词
mastitis; metabolite; pathogen; artificial neural network
The possibility to detect mastitis-causing pathogens based on their volatile metabolites was previously studied. In that study, the mastitis samples were incubated overnight. To minimize the total analysis time, no incubation, or a short incubation, would be preferred. We therefore investigated the effect of the incubation time on the formation of volatile metabolites in mastitis samples. A selection of 6 volatile metabolites with the highest impact on the prediction model for identifying the mastitis-causing pathogen, was compared at different incubation times between 0 and 24 h. Identification of the pathogens was not possible without incubation. The minimum incubation time for detection of most of the 6 metabolites was 4 to 8 h. Although a longer incubation time increased the differences between pathogens, after 8 h all metabolites could be detected and the pathogens could be differentiated. Eight hours was therefore selected as the optimal incubation time. This optimal incubation time was evaluated with a set of 25 mastitis samples, of which 88% were correctly classified after 8 h of incubation. The total analysis time for this method is therefore considerably shorter than current microbiological culturing.
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