| Summary: | 碩士 === 國立中興大學 === 生命科學院碩士在職專班 === 106 === Salmonella spp. is one of the common zoonosis in the worldwide. However, food poison caused by Salmonella spp., causes severe vomiting, diarrhea and other symptoms, and lead to other complications leading to death. In livestock ranches, it is one of the main reasons of serious economic losses. Therefore, to diagnose rapidly and accurately Salmonella become particularly important. There are many kind of serotypes of Salmonella spp. and the classification are very complicated. According to ISO 6579:2002 standards, detection methods need to identify of Salmonella isolates, it often takes a lot of examination time. In this study, we would like to develop a rapid and accurate detection method surface enhanced raman spectroscopy, to detect and identify different serotypes of Salmonella. The results of this study, surface enhanced raman spectroscopy (SERS) spectra of the eight Salmonella serotypes, namely S. choleraesuis, S. enteritidis, S. typhi, S. 到B, several wavenumbers including 558 cm-1, 726-735 cm-1,950 cm-1 , 1043-1051 cm-1, and 1272-1293 cm-1 were observed. According to resemblances between characteristic peaks, Salmonella samples can be seperated to 3 groups: S. paratyphi A and S. paratyphi B; S. enteritidis, S. typhi, S. typhimurium and S. Newport; S. choleraesuis and S. dublin. Additional analytic process followed the principal component analysis (PCA) method, the specificity of SERS can be improved to achieve the purpose of distinguishing at least about six Salmonella serotypes. In addition, the detection time for distinguishing Salmonella serotypes can be shortened to 1 hour after the pre-incubation culture.We demonstrated that SERS is a simplely, specificity and effectively method for detecting Salmonella serotypes. After developing SERS wavenumber reference databank of Salmonella serotypes, which can be applied to quality control for food processing plants, meat processing factories, environmental monitoring of Salmonella serotypes. In specific target detection, SERS has the potential to replace traditional detection methods.
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