Abstract: This study was conducted to assess the improved forage production and Utilization. For this study, three kebeles were selected purposively based on their livestock potential and 160 households were selected from selected kebeles randomly. The major feed resource in the study area was crop residue and pasture land grazing. The dominant forage species adopted in the area were Desho and elephant grass. Primary problem for livestock production was the shortage of feed resources. Majority (66%) of the households were in the active productive age (31-45) about 60% of household heads were literate (primary school and above). The average land cultivated per household in the study area was 0.25 hectares. Crop production was the principal source of cash income in the region, followed by cattle production in second place and sheep production in third. Almost all households in the study area had experience in cultivating improved forage, particularly elephant and desho grasses. The main challenges related to livestock production identified in the area were primarily diseases, ranked first, followed by feed shortages in second place, and water shortages in third, along with issues related to poor breed performance to some extent. Among the main feed sources identified, grazing, crop residues, and desho grass were ranked first, second, and third, respectively, in the study area.
Abstract: This study was conducted to assess the improved forage production and Utilization. For this study, three kebeles were selected purposively based on their livestock potential and 160 households were selected from selected kebeles randomly. The major feed resource in the study area was crop residue and pasture land grazing. The dominant forage specie...Show More
Abstract: In parameter estimation techniques, several methods exist for estimating the distribution parameters in life data analysis. However, some of them are less efficient than Bayes’ method, despite its subjectivity to prior information other than data that can mislead subsequent inferences. Thus, the main objective of this study is to present optimal numerical iteration techniques, such as the Picard and the Runge-Kutta methods, which are more efficient than Bayes’ method. The proposed methods have been applied to the inverse Weibull distribution parameters and compared to the Bayes’ method based on the informative gamma prior and the non-parametric kernel and characteristic priors, via an extensive Monte Carlo simulation study through the absolute average bias and the mean squared errors for the parameter estimators. The simulation results indicated that the Picard and Runge-Kutta methods provide better estimates and outperform the Bayes’ method based on the dual generalized progressive hybrid censoring data. Finally, it has been shown that the inverse Weibull distribution gives a good fit to new areas of dataset applications, such as flood data and reactor pump data. We have analyzed and illustrated the proposed methods using these datasets to confirm the simulation results.
Abstract: In parameter estimation techniques, several methods exist for estimating the distribution parameters in life data analysis. However, some of them are less efficient than Bayes’ method, despite its subjectivity to prior information other than data that can mislead subsequent inferences. Thus, the main objective of this study is to present optimal nu...Show More