Browsing by Author "Britz, Trevor J."

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    Escherichia coli with virulence factors and multidrug resistance in the Plankenburg River
    (Academy of Science of South Africa, 2014) Lamprecht, Corne; Romanis, Marco; Huisamen, Nicola; Carinus, Anneri; Schoeman, Nika; Sigge, G. O.; Britz, Trevor J.
    Escherichia coli is a natural inhabitant of the gut and E. coli levels in water are considered internationally to be an indication of faecal contamination. Although not usually pathogenic, E. coli has been linked to numerous foodborne disease outbreaks, especially those associated with fresh produce. One of the most common ways through which E. coli can be transferred onto fresh produce is if contaminated water is used for irrigation. In this study, a total of 81 confirmed E. coli strains were isolated from the Plankenburg River as part of three separate studies over 3 years. During sampling, E. coli levels in the river were above the accepted levels set by the World Health Organization and the South African Department of Water Affairs and Forestry for safe irrigation of fresh produce, which indicates that transfer of E. coli during irrigation is highly probable. Multiplex polymerase chain reaction screening for pathogenic gene sequences revealed one enteroaggregative positive strain and four enteropathogenic positive strains. The four enteropathogenic strains were also found to be resistant to three or more critically and highly important antibiotics and were therefore classified as multidrug resistant strains. These results show that E. coli with enteropathogenic potential and multiple antimicrobial resistance properties has persisted over time in the Plankenburg River.
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    Near infrared (NIR) hyperspectral imaging and multivariate image analysis to study growth characteristics and differences between species and strains of members of the genus fusarium
    (SpringerLink, 2012-08) Williams, Paul J.; Geladi, Paul; Britz, Trevor J.; Manley, Marena
    Near-infrared (NIR) hyperspectral imaging was used to study three strains of each of three Fusarium spp. (Fusarium subglutinans, Fusarium proliferatum and Fusarium verticillioides) inoculated on potato dextrose agar in Petri dishes after either 72 or 96 h of incubation. Multivariate image analysis was used for cleaning the images and for making principal component analysis (PCA) score plots and score images and local partial least squares discriminant analysis (PLS-DA) models. The score images, including all strains, showed how different the strains were from each other. Using classification gradients, it was possible to show the change in mycelium growth over time. Loading line plots for principal component (PC) 1 and PC2 explained variation between the different Fusarium spp. as scattering and chemical differences (protein production), respectively. PLS-DA prediction results (including only the most important strain of each species) showed that it was possible to discriminate between species with F. verticillioides the least correctly predicted (between 16 and 47 % pixels correctly predicted). For F. subglutinans, 78–100 % pixels were correctly predicted depending on the training and test sets used. Similarly, the percentage correctly predicted values of F. proliferatum were 60–80 %. Visualisation of the mycelium radial growth in the PCA score images was made possible due to the use of NIR hyperspectral imaging. This is not possible with bulk spectroscopy in the visible or NIR regions.