Adoption of multiple agricultural technologies in maize production of the Central Rift Valley of Ethiopia

Ahmed, Musa Hasen

doi:10.7896/j.1521

Cited by 40 publications

(28 citation statements)

References 29 publications

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“…Other factors kept constant, being members of cooperatives was found to affect farmers' likelihood of the package adoption by the factor of 0.134, and the result was statistically significant at 1% level. The result conveys the message that cooperatives are among the strongest social institutions that play crucial roles in adoption of wheat technology packages, and also findings from the studies by Tesfaye et al (2001), Abebaw and Haile (2013) and Ahmed (2015) are consistent with this result.…”

Section: Econometric Results Determinants For Adoption Of Technology supporting

confidence: 84%

“…Many technology adoption studies emerging in crop sub-sector revealed that the gain from adoption is not satisfactory compared to the expectations, and hence further interventions on factors impeding these are suggested (Kotu et al, 2000;Dixon et al, 2006;Dercon and Christiaensen, 2011;Asfaw et al, 2012;Shiferaw et al, 2014;Ahmed, 2015;Jaleta et al, 2016;Yigezu et al, 2015;Beshir, 2016;Hagos, 2016;Seymour et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…For instance, wheat technology packages in East Hararghe and West Hararghe zones include improved planting methods (row planting), improved varieties, appropriate use of inorganic fertilizers, and applications of pesticides. However, many of the adoption studies focused on a single component of the technology package (Croppenstedt et al, 2003;Asfaw et al, 2011;Beshir et al, 2012;Ahmed, 2015;Amare and Bekele, 2016). In such cases, it is difficult to have a clear understanding of the adoption of technology packages.…”

Section: Introductionmentioning

confidence: 99%

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

Kebede

Ketema

Dechassa

et al. 2017

Turkish JAF Sci.Tech.

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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.

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Section: Econometric Results Determinants For Adoption Of Technology supporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Kebede

Ketema

Dechassa

et al. 2017

Turkish JAF Sci.Tech.

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“…Local polynomial regression depicts a positive relationship between adoption level and productivity implying that productivity was significantly higher for those farmers who adopted SAMP (Figure 3). Ahmed (2015) found similar result in the case of maize production. Gray & Shadbegian (1998), Thapa (2007), Belay et al (2014), Moreno and Surinach (2014), Asfaw & Shiferaw (2010) also found that productivity of high adopters were greater than that of less adopter.…”

Section: Relationship Between Adoption Level and Productivitysupporting

confidence: 75%

Management practice adoption and productivity of commercial aquaculture farms in selected areas of Bangladesh

Prodhan

Khan

2018

J Bangladesh Agric Univ

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Adoption of scientific management practice is the pre-condition for increasing productivity in any farm business. This study estimates the level of scientific aquaculture management practice (SAMP) adoption, factor affecting adoption and its relation with productivity. Sixty aquaculture farms were selected from 3 upazilas of Mymensingh district of Bangladesh. Adoption level was measured by following Sengupta (1967) while Tobit regression was used to assess the determinants of adoption level. Polynomial regression was employed to show the relationship among farm size, adoption level and productivity. Result revealed that average SAMP adoption level was 54% where 53% farmers were medium adopter. Training, experience, education and extension service had significant positive effect on level of adoption. Productivity was significantly higher for those farmers who adopted more SAMP. Adoption level, productivity and profitability of small farmers were higher than that of large farmers. The study suggests farmers for adopting scientific management practices in order to increase the aquaculture productivity and profitability.

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“…The MVP estimation technique considers the correlation in the error terms by jointly modelling the effects of a set of covariates on each of the improved agricultural technologies and estimates a set of binary probit models. It allows the relationship between the adoption of different improved production practices to be established, as well as potential correlations between unobserved disturbances (Ahmed, 2015;Kassie et al, 2009). Univariate models such as probit and logit ignore the correlation in the error terms of the adoption equation.…”

Section: Analytical Framework -The Multivariate Probit Modelmentioning

confidence: 99%

Adoption of improved agricultural technologies among rice farmers in Ghana: a multivariate probit approach

Donkoh¹,

Azumah²,

Awuni³

2019

Ghana J. Dev. Stud.

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The need for practising modern techniques in rice production has become increasingly important in Ghana as the per capita cultivable land continues to shrink. This study employed a multivariate probit model to estimate the determinants of adoption of improved agricultural technologies using household data collected from 543 rice farmers in the Upper East and Northern region of Ghana. There was complementarity among all the improved rice production technologies (i.e. nursery establishment, harrowing, line planting, spacing, urea briquette, irrigation, and bunding). Among the socioeconomic variables, education, household size, experience, farm size, sex, and age of the farmer play significant roles, with differing signs across technologies. Among the institutional factors, membership of farmer-based organisation, access to research service, training and credit were significant with differing signs across the improved technologies. Location also had significant and differing influence on adoption. Also, demonstration, TV, radio, video, mobile phones, and household extension methods had significant and differing influence on the adoption of improved technologies, providing significant justification for the review

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Adoption of multiple agricultural technologies in maize production of the Central Rift Valley of Ethiopia

Cited by 40 publications

References 29 publications

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

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

Management practice adoption and productivity of commercial aquaculture farms in selected areas of Bangladesh

Adoption of improved agricultural technologies among rice farmers in Ghana: a multivariate probit approach

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