IRRIGATION WATER AS A POTENTIAL PREHARVEST SOURCE OF BACTERIAL CONTAMINATION OF VEGETABLES

Abstract

ABSTRACT The aim of this research is to determine the bacteriological quality of the irrigation canal from Loskopdam, the two rivers that feed it and vegetables (broccoli and cauliflower) in Mpumalanga, South Africa and also to predict the presence of selected bacterial pathogens in irrigation water and on vegetables with logistic regression analysis. Water and vegetable samples were examined for the presence of total coliforms, fecal coliforms, Escherichia coli, Listeria monocytogenes, Salmonella sp., Enterococcus, Staphylococcus aureus, aerobic spore formers, anaerobic spore formers and aerobic colony counts were done. Apart from bacterial analysis, the following physicochemical tests: temperature, pH, turbidity and chemical oxygen demand (COD) were determined in water samples. The average COD and turbidity in the two rivers and the canal were higher than the World health Organization (WHO) and South African water guidelines. Sampling and analyses were done for a period of 12 months. Levels of fecal coliforms and E. coli were higher than the WHO standard. S. aureus, intestinal enterococci, Salmonella, L. monocytogenes were recovered from the two rivers and the canal. Apart from L. monocytogenes, which was not recovered from cauliflower, all bacterial pathogens recovered from the surface water were recovered from the vegetables. PRACTICAL APPLICATION These results show that the rivers in Mpumalanga may contribute to the contamination in the irrigation canal which may be a possible preharvest source of contamination of broccoli and cauliflower, which may in turn constitute a health risk to consumers. Logistic regression analysis of the sampled data showed that chemical oxygen demand was statistically reliable to predict Listeria monocytogenes, turbidity reliable to predict intestinal enterococci and fecal coliform and coliform reliable to predict Salmonella in irrigation water. Aerobic colony count was statistically significant for the prediction of the three pathogens in vegetables.