8–11 Sept 2026
Unversity of Eldoret
Africa/Nairobi timezone
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Comparison of Microbial Contamination Levels and Milk Shelf Life Along the Dairy Value Chain in Rungwe District, Tanzania

Not scheduled
12m
Rimoi (EKA Hotel)

Rimoi

EKA Hotel

Eldoret Town
Agriculture & Food Systems Agriculture & Food Systems

Speaker

Israel Stephen Mwingira (Department of Animal Science and Management, School of Agriculture and Biotechnology, University of Eldoret, Kenya)

Description

This study compared microbial contamination levels and shelf life of the raw milk along the dairy value chain in Rungwe District, Tanzania. Four (04) wards namely Ikuti, Nkunga, Lufingo, and Kiwira and three (03) milk value chains namely Value chain one (VC1), Value chain two (VC2) and Value chain three (VC3) were purposively selected in this study. One hundred and seventy-six (176) milk samples were collected and examined for Total Plate Count (TPC) and Total Coliform Count (TCC) along with milk shelf life (MSL). The Statistical Package for the Social Sciences (SPSS) was used to analyse the data. The results showed that, bacterial loads (TPC and TCC) of milk samples in all stages of the value chains were within the East African standards (EAS) for quality raw milk. However, TPC at farmers level decreased significantly from farmers who sell milk directly to consumers in VC1 (Farmer A After) 3.10 log10 CFU/ml ± 0.59 log10 CFU/ml to farmers who sell milk to the milk collection point (MCP) through milk transporters in VC3 (Farmer C After) 2.85 log10 CFU/ml ± 0.35 log10 CFU/ml while for the intermediate actors, the highest contamination was observed in consumers who buy milk from MCP operators in VC3 (Consumer C Before) 5.06 log10 CFU/ml ± 0.26 log10 CFU/ml. The highest MSL in most stages of the value chain was 4 h when stored at 25 C. Milk samples stored in refrigeration temperatures had shelf life beyond 4 h indicating important role of cold chain in milk microbiological quality control. The study concluded that, microbial contamination levels and MSL varied significantly across value chains in Rungwe District. These fluctuations are driven by distinct, node specific factors rather than a uniform set of drivers affecting the entire chain. Consequently, the study recommends a need for node-specific interventions rather than a singular district wide hygiene strategy to improve milk quality and stability.

Authors

Israel Stephen Mwingira (Department of Animal Science and Management, School of Agriculture and Biotechnology, University of Eldoret, Kenya) Eunice Akello Mewa (Department of Animal Science and Management, School of Agriculture and Biotechnology, University of Eldoret, Kenya) Joseph Amesa Omega (Department of Animal Science and Management, School of Agriculture and Biotechnology, University of Eldoret, Kenya)

Presentation materials

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