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 ...

https://www.tandfonline.com/doi/pdf/10.1080/23322039.2017.1416896

Adoption of improved maize variety among farm households in the northern region of Ghana

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.

http://www.agrifoodscience.org/index.php/TURJAF/article/download/1041/494

Determinants of Adoption of Wheat Production Technology Package by Smallholder Farmers: Evidences from Eastern Ethiopia

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

Factors influencing the adoption of improved wheat varieties by rural households in Sindh, Pakistan

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.

/pdf/factors-affecting-adoption-of-upland-rice-in-tselemti-gjzzj1b8qc.pdf

Factors affecting adoption of upland rice in Tselemti district, northern Ethiopia

Agriculture takes the lion’s share in the economic development of many developing countries, including Ethiopia. Agricultural policy of the years has focused on supporting the introduction of improved technologies to boost production and reduce food insecurity. However, outcomes of such agricultural policies have been influenced by different factors of which low adoption of improved agricultural technology is a major constraint. The objective of this study was therefore, to analyze the determinants of adoption and intensity of use of row planting for wheat production. Data were obtained from both primary and secondary sources. Multi-stage sampling technique was used to select 140 wheat producer household heads from the Munesa district of Oromia region, Ethiopia.  Data were collected through the administration of semi-structured questionnaires. Data were analyzed using both descriptive statistics and the Tobit econometric model. Descriptive result shows that, from 140 sampled households 97 are adopters of wheat row planting while the remaining are non-adopters. The model was used in estimating the determinants of adoption and intensity of use of row planting for wheat production. The model results revealed that education level, labor availability, extension contact, credit use, participation in training and access to improved seed had positively and significantly influenced adoption and intensity of use of row planting for wheat production. Based on the results of this study, it can be concluded that, policy and development interventions should focus on improving economic and institutional support system for high rates of adoption and intensity leading to improved productivity and income among smallholder farmers.

	Key words: Adoption, row planting, Tobit model, Munesa, wheat.

/pdf/adoption-determinants-of-row-planting-for-wheat-production-62fihhyqid.pdf

Adoption determinants of row planting for wheat production in Munesa District of Oromia Region, Ethiopia

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.

/pdf/factors-determining-allocation-of-land-for-improved-wheat-1ik6pgonvv.pdf

Leake Gebresilassie

Papers

Factors determining allocation of land for improved wheat variety by smallholder farmers of northern Ethiopia