Geremew Bultosa

Handling Practices and Safety of Street-Vended Milk in and Around Addis Ababa City

Forty five milk producers (MP) and 45 street-vendors (SV) of milk were selected randomly from three locations (Kotebe, Bishoftu and Chancho), Ethiopia and interviewed using semi-structured questionnaire. A total of 30 samples purposively selected from MP (15) and SV (15) were used for milk quality determinations. Milk producers in the study area generally followed unhygienic milking and improper milk handling practices. Average total bacterial (TBC) and coliform counts (CC) of milk from SV were 8.69 ± 0.15 and 6.61 ± 0.16 log 10 cfu/ml and from MP the corresponding values were 6.98 + 0.15 and 4.88 ± 0.16 log 10 cfu/ml, respectively. TBC and CC of milk samples obtained from streetvendors were significantly (P < 0.05) higher (1.71 and 1.73 log units, respectively) than milk samples obtained from dairy farmers. Dominant microflora isolated from raw milk belonged to the genera Bacillus (11.7%), Micrococcus (8.3%), Pseudomonas (7.8%), Staphylococcus (24.4%), Streptococcus (5%) and family Enterobacteriaceae (lactose- (32.8%) and non-lactose fermentative (10%)). The results showed poor hygienic quality of milk that may pose public health hazards. This calls for milk quality and safety improvement in the study area.

Effect of rice variety and blending proportion on the proximate compositions, minerals and phytic acid contents of bread from rice-teff blend

Development of bakery products containing rice ( Oryza sativa, Linn.) and teff ( Eragrostis tef) could have potential health benefits due to their gluten free nature. Nine experimental runs were generated using custom design by JMP 8 software. The effect of two factors, rice variety (Edeget, X-jigna and Nerica-4) and blending proportions of rice and teff (0.5:0.5, 0.7:0.3 and 0.9:0.1) were studied. The data analysis was conducted using SAS software package for the mean comparison and custom design by JMP 8 software. Response surface methodology was applied to study the interaction effect of the main factors and to generate the predictive equations. An optimal value (1.60%) of fiber was obtained when the proportion of the blend was 50% Edeget and 50% teff because teff grain is high in fiber. A maximum value (10.75%) of protein was obtained when the proportion of the blend was 70% Nerica-4 and 30% teff. Carbohydrate was optimal (81.37%) when 90% Edeget and 10% teff were blended because rice grain is high in carbohydrate. Optimal iron content (12.97 mg/100g) was obtained when the proportion of the blend was 50% Nerica-4 and 50% teff because teff grain is high in iron. Optimal zinc content (4.14 mg/100g) was obtained when the proportion of the blend was 50% X-jigna and 50% teff. The optimal value (61.25 mg/100g) of calcium was obtained when the proportion of the blend was 50% Edeget and 50% teff. Optimum (lower) value (0.31mg/g) of phytic acid was obtained when the proportion of the blend was 90% Nerica-4 and 10% teff because rice grain is lower in phytic acid content. It was concluded that rice variety and rice-teff blending proportion had a significant effect on the physico-chemical properties of rice-teff blend bread. An optimal nutrient blend (high in nutrients, low in anti-nutrients) was obtained when 70% Edeget rice variety was blended with 30% teff. All the derived mathematical models for the various responses were found to fit significantly to the predicted data.