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Gewählte Master / Diploma Thesis:

Christina Ukowitz (2018): Methodenspektrum zur Identifizierung der Bakterienpopulationen in Extraktionssystemen der Rübenzuckerproduktion.
Master / Diploma Thesis - Institut für Lebensmittelwissenschaften, BOKU-Universität für Bodenkultur, pp 114. UB BOKU obvsg

Data Source: ZID Abstracts
Abstract:
In the extraction process of beet sugar production, sucrose is extracted with a countercurrent aqueous extraction from the beet cossettes at temperatures around 70 °C. Despite the high temperatures, the growth of bacterial populations in these areas can lead to direct and indirect sugar losses. Therefore, the microbial growth is controlled by the application of disinfectants and the knowledge of the microbiota in the beet sugar production process is essential. The aim of this work was to define and test a set of methods that allow an insight and accurate description of the composition and dynamic of the bacterial population in the extraction process. Next to classical microbiological approaches, data generated by NGS (next generation sequencing) technique of 16S rDNA amplicons of a metagenome analysis were used for the identification of bacterial communities in samples from tower and trough extraction systems. The received results indicate that the metagenome analysis based on 16S rDNA amplicons is a suitable method for the identification of bacterial populations in different extraction systems of beet sugar production. In addition, the investigation of specific bacterial counts allowed the quantitative description of the bacterial contaminations in raw juice. Both, the microbiological and molecular biological methods demonstrated that lactic acid bacteria and bacilli were the dominant bacterial genera identified in all samples tested. Furthermore, NGS-based analysis revealed a possible influence of different applied disinfectants on composition and dynamics of bacterial populations. Further investigations are necessary to confirm the observations of this work and to describe them in more detail.

Beurteilende(r): Domig Konrad

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