Staphylococcus aureus in cow milk and milk products in Ambo and Bako towns,Oromia, Ethiopia: prevalence,associated risk factors,hygienic quality,and antibiogram

International Microbiology - Staphylococcus aureus (S. aureus) is a foodborne bacterial pathogens that can cause staphylococcal food poisoning and contaminate food of animal origin worldwide. The...     

Livestock Diversification: an Adaptive Strategy to Climate and Rangeland Ecosystem Changes in Southern Ethiopia

Pastoral cattle production in southern Ethiopia is becoming increasingly vulnerable to impacts of climate variability and rangeland resource degradation, giving rise to livestock diversification. Using a household (n?=?242) survey among herders, the relative functions, adaptability and vulnerability of four livestock species and factors influencing livestock diversification were analyzed. The stated major drivers of livestock diversification were recurrent droughts, bush encroachment, increased vulnerability of cattle and growing demand for adaptive species. Different livestock species are kept to fulfill various livelihood priorities with subsistence objectives outweighing production goals of the herders. Adaptability and vulnerability analyses of the livestock species showed camels and cattle to be the most and least adaptable species, respectively. Livestock species diversification varied significantly with family size and per capita holding of cattle, implicating the influence of labor and economic factors on adoptions. Multispecies herding emerged as the dominant local adaptation strategy, likely because it enhances resilience of households to climate and rangeland ecosystem changes by broadening the set of existing strategies.     

Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process

The biological treatment process is responsible for removing organic and inorganic matter in wastewater. This process relies heavily on microorganisms to successfully remove organic and inorganic matter. The aim of the study was to model biomass growth in the biological treatment process. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to model biomass growth. Three metrics: coefficient of determination (R²), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the model. Sensitivity analysis was applied to confirm variables that have a strong influence on biomass growth. The results of the study showed that MLP ANN algorithm was able to model biomass growth successfully. R² values were 0.844, 0.853, and 0.823 during training, validation, and testing phases, respectively. RMSE values were 0.7476, 1.1641, and 0.7798 during training, validation, and testing phases respectively. MSE values were 0.5589, 1.3551, and 0.6081 during training, validation, and testing phases, respectively. Sensitivity analysis results showed that temperature (47.2%) and dissolved oxygen (DO) concentration (40.2%) were the biggest drivers of biomass growth. Aeration period (4.3%), chemical oxygen demand (COD) concentration (3.2%), and oxygen uptake rate (OUR) (5.1%) contributed minimally. The biomass growth model can be applied at different wastewater treatment plants by different plant managers/operators in order to achieve optimum biomass growth. The optimum biomass growth will improve the removal of organic and inorganic matter in the biological treatment process.     

Cattle brucellosis in traditional livestock husbandry practice in Southern and Eastern Ethiopia,and its zoonotic implication

Background  

Cattle brucellosis has significant economic and zoonotic implication for the rural communities in Ethiopia in consequence of their traditional life styles, feeding habits and disease patterns. Hence, knowledge of brucellosis occurrence in traditional livestock husbandry practice has considerable importance in reducing the economic and public health impacts of the disease.     

An ethnobotanical study of medicinal plants in Wayu Tuka District,East Welega Zone of Oromia Regional State,West Ethiopia

Background

Himalayan forests are the most important source of medicinal plants and with useful species for the local people. Kedarnath Wildlife Sanctuary (KWLS) is situated in the interior part of the Garhwal Himalayan region. The presented study was carried out in Madhmeshwar area of KWLS for the ecological status of medicinal plants and further focused on the ethnomedicinal uses of these plants in the study area.

Methods

Ecological information about ethnomedicinal plants were collected using random quadrats in a random sampling technique along an altitudinal gradient in the KWLS. Information on medicinal properties of plants encountered in the present study was generated by questionnaire survey and was also compared with relevant literature.

Results

A total of 152 medicinally important plant species were reported, in which 103 were found herbs, 32 shrubs and 17 were tree species which represented 123 genera of 61 families. A total of 18 plant species fell into the rare, endangered (critically endangered) and vulnerable status categories.

Conclusion

The present study documented the traditional uses of medicinal plants, their ecological status and importance of these plants in the largest protected area of Garhwal Himalaya. This study can serve as baseline information on medicinal plants and could be helpful to further strengthen the conservation of this important resource.