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Adam Bekele

Bio: Adam Bekele is an academic researcher. The author has contributed to research in topics: Gross margin. The author has an hindex of 2, co-authored 3 publications receiving 31 citations.
Topics: Gross margin

Papers
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Journal ArticleDOI
TL;DR: In this article, the Tobit model was used to analyze factors influencing adoption of improved wheat technology econometrically, and a total of thirteen explanatory variables were included in the model including education level of household head, family size, tropical livestock unit, distance from main road and nearest market, access to credit service, extension contact and perception of household towards cost of the technology.
Abstract: This study was conducted in Northern Ethiopia, Adwa district. The main objective of the study was to examine factors influencing allocation of land for improved wheat variety by smallholder farmers of the study area. Descriptive, inferential and econometric methods were used to analyze data. Results of descriptive and inferential analyses showed that; adopters had high family size in adult-equivalent, high number of tropical livestock unit, large land size, high frequency of extension contact, access to credit service, they were followed formal schooling, and they were nearest to main road and market as compared to non-adopters. Tobit model was used to analyze factors influencing adoption of improved wheat technology econometrically. A total of thirteen explanatory variables were included in the model. From the tested variables only eight variables (education level of household head, family size, tropical livestock unit, distance from main road and nearest market, access to credit service, extension contact and perception of household towards cost of the technology) were found to be the significant factors affecting adoption of improved wheat variety. Implication of results of this study is that any development intervention through improved wheat technologies should consider the aforementioned socioeconomic characteristics and determinants of adoption for success. Key words: Adoption of Improved wheat variety, Adwa, smallholder farmers, Topit model.

42 citations

Journal ArticleDOI
TL;DR: In this paper, a study was conducted to assess costs and patterns of input use and determine the profitability of soybean production in Assosa zone of Benishangul-Gumuz region.
Abstract: In Ethiopia, the demand for soybean product is increasing as a result of increasing population growth, agro-processing and urbanization. Research needs to provide farm level evidence that could guide informed production decision-making. This research was conducted to assess costs and patterns of input use and determine the profitability of soybean production in Assosa zone of Benishangul-Gumuz region. Data for the study were collected from 59 randomly selected soybean farmers using a well-structured questionnaire. Descriptive statistics and enterprise budgets are used to analyze the data. Results of the gross margin analysis showed that total gross revenue of Birr 10566.38 ha-1 is generated from sales of soybean grain. The average variable cost incurred is 6634.43 Birr/ha. The gross margin and net-farm income was estimated to be 3931.956 and 3629.956 Birr/ha, respectively. The benefit cost ratio amounted to 1.52 which implies for every Birr incurred in costs, the farmer can expect a benefit of 1.52 Birr. Moreover, the sensitivity analysis indicated that profitability of soybean production is more sensitive to reduction in price than to increases in yield. The study therefore concluded that soybean production in Assosa Zone of Benishangul-Gumuz region is profitable enterprise. It is suggested that consistent government policies that would favor soybean production and market linkage between producers and soybean agro-industries in the area would attract investors and small-scale farmers would gain reasonable economic benefits from soybean production in Assosa zone. Key words: Soybean, production, profitability, costs, returns, Benishangul-Gumuz.

6 citations

Journal ArticleDOI
11 May 2019
TL;DR: In this article, Nwafor et al. show that climate change is global, likewise its impacts; but the most adverse effects will be felt mainly by developing countries, especially those in Africa, due to their low level of coping capabilities.
Abstract: Available evidence shows that climate change is global, likewise its impacts; but the most adverse effects will be felt mainly by developing countries, especially those in Africa, due to their low level of coping capabilities (Nwafor 2007; Jagtap 2007). Adaptation to new climatic conditions is, hence, a necessary strategy for those living in the affected parts of the world. Adaptation comprises measures of prevention as well as measures of adopting a change in a traditional way of life.

1 citations


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01 Jan 2009

8,216 citations

Journal ArticleDOI
TL;DR: In this paper, the determinants of adoption of improved maize variety (IMV) among farmers in the northern region of Ghana and subsequently assess the factors influencing the intensity of adoption.
Abstract: This study aims to identify the determinants of adoption of improved maize variety (IMV) among farmers in the northern region of Ghana and subsequently assess the factors influencing the intensity ...

82 citations

Journal ArticleDOI
TL;DR: In this article, a Two-limit Tobit model was used to elucidate factors affecting adoption of technology packages measured based on an index derived from five components of wheat technologies which included row planting, pesticide application, use of improved varieties, and application of inorganic fertilizers, namely, Diammonium Phosphate (DAP) and Urea.
Abstract: A study was conducted to analyze factors influencing adoption of wheat technology packages by smallholder farmers in Gurawa, Meta and Habro districts in eastern Ethiopia. The analysis was based on a household survey data collected from 136 randomly selected households. A Two-limit Tobit model was used to elucidate factors affecting adoption of technology packages measured based on an index derived from five components of wheat technologies which included row planting, pesticide application, use of improved varieties, and application of inorganic fertilizers, namely, Diammonium Phosphate (DAP) and Urea. Among the variables included in the model, variation in district, gender, age of the household head, education status of the household head, farm size, distance to market, distance to FTC (Farmers’ Training Centers), cooperative membership, dependency ratio, and annual income of the households were found to significantly affect the adoption of wheat technology packages. Policy makers, planners and development practitioners should give due attention to these determinants to support smallholder farmers in wheat production and enhance gains derived from it.

20 citations

Journal ArticleDOI
06 Jul 2018
TL;DR: In this article, the authors examined the factors affecting the adoption of high-yield wheat varieties by wheat farmers in Sindh, Pakistan and found that the adoption was positively and significantly influenced by education, farming experience, landholding size, tube-well ownership, extension contact and access to credit.
Abstract: This study examines the factors affecting the adoption of high-yield wheat varieties by wheat farmers in Sindh, Pakistan A cross-sectional data of randomly selected 240 wheat farmers from Shaheed Benazirabad and Naushahro Feroze districts in the middle region of Sindh, Pakistan were collected for this study We performed the probit model to estimate factors that influence the adoption of improved wheat varieties The results drawn from the estimations show that the adoption of improved wheat varieties by farmers in the study area was positively and significantly influenced by education, farming experience, landholding size, tube-well ownership, extension contact and access to credit The study recommends that public and private sectors should encourage access to extension service to improve of dissemination of certified seed of wheat crop among the growers through trainings, workshops and seminars

16 citations

Journal ArticleDOI
TL;DR: In this article, a multistage sampling technique was employed to select 150 sample households for a study intended to identify factors affecting adoption of rice technologies in Tselemti district of Tigray region, Ethiopia.
Abstract: Rice cultivation is a new practice to Tselemti district of Tigray region, Ethiopia. Adoption of rice technologies is very slow in spite of its potential in the area. This research intended to identify factors affecting adoption of rice technologies. A multistage sampling technique was employed to select 150 sample households for this study. Descriptive statistics and inferential statistics were employed to see mean and percentage differences between adopter and non-adopter categories. Besides, binary logistic regression model was employed to identify the factors affecting adoption of rice technology. Result of the descriptive and inferential analysis showed that adopters had better farm size, livestock holding, farm income, labor availability, education level, perception on rice yield, access to credit service, contacts with extension agents, participation in off-farm activities, participation in training and field days as compared to non-adopters. Moreover, the binary logistic regression model result showed that the level of education, perception on rice yield, access to credit service, participation in off-farm activities, participation on field day and participation in training were found to positively and significantly influence the adoption decision of rice technology at 1%, 5% and 10% significant level. However, market distance influences rice technology adoption negatively and significantly at 10% significant level. The variables education, rice yield, access to credit, off-farm activities, market distance, participation on field day and training determine the farmers’ continued adoption decision behavior of rice technology. Therefore, the adoption of rice technology should be sustained by paying attention and moving along with those variables which influenced the adoption significantly.

15 citations