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Impacts of Adoption of Improved Coffee Varieties on Farmers' Coffee Yield and Income in Jimma Zone

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Impacts of Adoption of Improved Coffee Varieties on Farmers' Coffee Yield and Income in Jimma Zone Research Article Agri Res & Tech: Open Access J Volume 21 Issue 4 - May 2019 Copyright © All rights are reserved by Samuel Diro DOI: 10.19080/ARTOAJ.2019.21.556169 Impacts of Adoption of Improved Coffee Varieties on Farmers’ Coffee Yield and Income in Jimma Zone Samuel Diro1* and Beza Erko2 1Holeta Agricultural Research Centre-EIAR, Ethiopia 2Jimma Agricultural Research Centre-EIAR, Ethiopia Submission: April 16, 2019; Published: May 14, 2019 *Corresponding author: Samuel Diro, Holeta Agricultural Research Centre-EIAR, Ethiopia Abstract of improved coffee varieties on adopters’ livelihood (income) and yield. Multistage sampling technique was employed to select the population for the studyThis study which was involved conducted both inpurposive four districts and randomof Jimma sampling zone namely techniques. Gera, Manna, Data was Limu collected Kosa and through Gomma structured to estimate questionnaire the relative benefits administered of use to sampled farmers. Both descriptive and inferential statistics, and econometric models were used to analyze the gathered and cleaned data. The impact of adoption of the improved coffee varieties on yield and income was estimated using propensity score matching (PSM) technique. The result of the survey revealed that the mean adoption rate of improved coffee cultivars was 53.56%. The mean overall clean coffee yield per hectare was 769kg/ha which is higher than the national average estimated by CSA (710kg/ha) by 8.3%. On other hands, the mean clean coffee yield per use of improved coffee varieties, PSM was run. Accordingly, from the total increment the use of improved coffee varieties increased clean coffee yieldhectare per of hectare land for by adopters 25.3-28.8% is significantly over the non-adopters. higher (861 Concomitantly, kg) than their non-adoptersthe use of improved counter coffee parts varieties (646kg). increased To extract coffee the net income increment by 33.6-46.6 due to % and total income by 25.8-44.1% over non-adopters using different matching algorithms. Government and non-government organizations need to emphasize on diffusion of improved coffee technologies to their maximum capacity. This would increase their productivity per unit of land which in turn raise farmers’ income and livelihood. Keywords: Adopter; Inferential; Non-adopter; Productivity and PSM Abbrevations: CIP: Coffee Improvement Project; CWD: Coffee Wild Disease; CBD: Coffee Berry Disease; PSM: Propensity Score Matching; ATE: Average Treatment Effect; ATT: Average Treatment Effect on the Treated; CIA: Conditional Independence Assumption; CSC: Common Support Condition Introduction The sustainable contribution of agriculture to economic Jimma agricultural research center has devoted consider- growth and development, poverty reduction and food security able effort and resource and developed several coffee technology enhancement could only be achieved through an increase in packages. To increase the contribution coffee to economic growth productivity of smallholder farmers using improved technologies through enhancing coffee production and productivity, coffee im- provement project (CIP) has been developed. The government poverty, lowering per unit costs of production [2], boosting [1]. Agricultural innovations play a significant role in fighting rural incomes and reducing hunger [1]. Many studies have project. The agreement was signed between EU and Ethiopian negotiated with European Union (EU) for a grant to finance the been conducted to assess the adoption of different agricultural government in 1977 and the implementation was carried out in technology and their impact on productivity, welfare and poverty different faces to introduce better coffee management practices reduction in rural areas [3-8]. The results of these empirical with intensive extension, to construct rural roads and cooperative studies revealed the positive impact of adoption of improved crop stores, to conduct intensive coffee research and to provide coffee varieties on households’ income, productivity and livelihoods. related farm inputs on credit basis. The contribution of CIP for cof- Coffee accounts over 35% of agricultural foreign exchange coffee development history of Ethiopia. Due to the establishment earnings and 4% of agricultural gross domestic product. It also fee producing areas of Ethiopia was substantial and significant in of CIP, several hectares of land were planted or replanted with provides income to over 15 million people in the country directly CBD resistant selections, many kilometers of access road were or indirectly through provision of jobs for farmers, local traders, constructed, thousands of hectares of old coffee trees rejuvenated, processors, transporters, exporters and bankers [9]. Agri Res & Tech: Open Access J 21(4): ARTOAJ.MS.ID.556169 (2019) 00152 Agricultural Research & Technology: Open Access Journal and generally coffee production and productivity had increased of the district’s agro climate does have tropical climate. The mean annual temperature of the district ranges from 18-23 . The mean annual rainfall of the district ranges from 1300-2300mm. Maize significantlySince then, [10,11]. the center has released 34 pure line and 6 hybrids ˚C and coffee are the main crops grown in the district. Gomma district totally 40 coffee varieties for different coffee belts of the country. extends between 7040’ to 8004’ north latitudes and 36017’ to 360 The varieties disseminated and diffused to both smallholder and 46’ east longitudes. It is bordered with Didesa district in north, commercial farmers through different forms and approaches of with Limmu Kosa district in east, with Manna district in southeast, coffee extension interventions. The improved coffee varieties re- with Seka Chekorsa in south and with Gera district in west. It is leased by Jimma agricultural research center offer new opportu- situated in the central part of the zone. Most part of the district be- nities for farmers because of their unique characteristics of high longs to subtropical and temperate agro climates. Sub-tropical and cup (sensory) quality, higher yield and huge tolerance to major temperate agro climates do respectively constitute 88% and 12% coffee disease such as CWD (coffee wild disease) and CBD (coffee of the district’s area. The mean annual temperature of the district berry disease) than the traditional cultivars/varieties. In addition ranges between 15 and 22 . The vast area of the district’s an- to these technologies, several recommendations have been devel- nual rainfall varies between 1700mm and 2100mm. Maize and oped on pest and disease management, agronomic and soil fertil- ˚C ˚C coffee are also the main crops grown in the district. Manna dis- ity management. Despite the diffusion and dissemination of these trict extends between 7038’ to 7054’ north latitudes and 36038’ - to 36053’ east longitudes. It is bordered with Gomma and Limmu proved coffee technologies has not been studied in Ethiopia. This improved coffee technologies, the relative benefits of use of im Kosa districts in north, with Kersa district in east, with Seka Che- study was designed to evaluate the economic contribution of the korsa district in south and with Gomma district in west. It is also use of improved coffee varieties on the livelihood of adopters of situated in the central part of the zone. Sub-tropical and temperate agro climates do respectively constitute 80% and 20% of the dis- the technology.a. To measure More specifically,the rates and the intensities study was ofset: adoption of im- trict’s total areas. The vast part of the district does have with mean proved coffee technologies on the study area. annual temperature ranges between 18 and 20 . The district has mean annual rainfall which lies between 1300 and 1700mm. b. To truck the impacts of coffee production technologies ˚C ˚C Maize and coffee are the main crops grown in the district JANRD (improved coffee varieties) on farmers’ coffee yields and in- (Figure 1). come. The result of the study could be helpful for coffee related bio- logical and physiological researchers, academicians, private inves- tors and policy makers. Methodology Study area description The study was conducted in four districts of Jimma zone name- ly Gera, Manna, Limu Kosa and Gomma districts. Gera district is found in the southwest of Jimma Zone. It shares border with Chek- orsa to the south east, with Gomma to the east, with Setema to the north east, with Sigmo to the north west, with Shebe Sombo to the south and the south Ethiopian people’s nations and nationalities to the west and south west. Its absolute location ranges between Figure 1: Map of the study districts. 7027’ to 7055’ north latitude and 38001’ to 36024’ east longitude. Tropical, Semi-tropical and temperate agro climates respectively Sampling procedure shares 15%, 35% and 50% of the district’s total area. The mean Multistage sampling technique was employed to select the annual temperature of the district ranges from 15-22 . The vast population for the study which involved purposive and random area of the district’s annual rainfall varies between 1300mm and sampling techniques. First, districts were purposively picked, ˚C 1700mm. Coffee and teff are the major local cash crops in the dis- and secondly kebeles were selected using lottery method. Finally, trict. Limu Kosa district extends between 7050’ to 8036’ north lat- households were randomly chosen from the sampling frame (list itudes and 36044’ to 37029’ east longitudes. It is bordered with of farmers) exist at kebele level. A total of 205 households were Limmu Seka district in north and West Shewa Zone in north east, selected for the study. with Tiro Afeta in southeast, with Manna and Kersa districts in south, with Buno Bedele zone and Gomma district in west. It is Data collection and analysis situated in the north central part of the zone. Data was collected through structured questionnaire admin- Sub-tropical and temperate agro climates do respectively con- istered to sampled farmers. Before the actual survey, the ques- stitute 70% and 15% of the district’s areas. The remaining 15% tionnaire was pretested in non-sampled villages. The pretest was How to cite this article: Samuel D, Beza E.
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