DETERMINANTS OF ADOPTION OF IMPROVED MAIZE TECHNOLOGY IN DAMOT GALE, WOLAITA, ETHIOPIA

The study was conducted in Damot Gale Woreda of Wolaita zone in Ethiopia. The study Woreda was selected purposively based on accessibility and production potential. Out of 51 peasant associations, 4 peasant associations were selected randomly. For selection of study units probability proportional to the size was applied and respondents were selected (adopters and non adopters) through systematic sampling technique. Descriptive statistics and Logit model was applied to estimate the factors affecting adoption of improved maize technology. The study results shows that small holders with more number of livestock, external funding, targeted extension services, unaffordable input price, timely supply of chemical fertilizer and improved seed and farm size are important determinants of adoption of maize technology. Further study reports that adoption is a cumulative effects of several factors. * Lecturer, Department of Extension and Rural Devlopment, Haramaya University, Dire Dawa, Ethiopia . ** Professor and Head, Department of Extension Education, RCA, Udaipur. INTRODUCTION Agriculture is the basis of Ethiopia economy. It contributes to over 50 percent of the GDP and 90 percent of raw materials requirement of the country's small and medium-sized industries. It is also estimated that agriculture provides employment for about 85% of labour force (MEDaC, 1999). The wide variability in agro-ecological conditions helps the country to produce different kinds of cereals, fruits and vegetables, and different species of livestock. However, Ethiopian agriculture is characterized by low productivity. Over the last two decades it was not able to produce sufficient food to feed the country's rapidly growing population. The level of technology is almost basic and productivity per hectare is perhaps among the lowest in the world. SG (Sasakawa Global) 2000 indicates that in high agricultural potential areas of Ethiopia (i.e. with high and reliable rainfall), in which crop based system predominates and population densities are highest, productivity is constrained by lack of knowledge, lack of finance and unavailability of appropriate improved technologies. A close look at the country's declining agricultural outputs and at the same time, everincreasing population growth begs for a search of alternatives. One of the alternatives to bridge this ever-increasing gap between the two is, increasing programs that focus primarily on the delivery of physical inputs such as fertilizer, high yielding varieties of seed, credit supply to small holders and training on improved agronomic practices. This can be done through government support to agriculture and extension by strengthening research extension linkages (SG, 2002). In order to achieve food security, a lot of attempts have been made by the government in Ethiopia over the last three decades but failed to increase the expected agricultural production and bring about noticeable change in the life of the smallholder farmers. In this regard, Belay (2002) suggested that one of the reasons for the existing structural food insecurity in the country is the lowlevel of technology development, which act as the principle barriers to the efficient utilization of the country's natural resource. Even though different extension approaches have been implemented in the country, it did not bring major or expected impacts on the productivity of smallholders and the utilization of modern inputs. Various types of cereal crops are being produced in different parts of Ethiopia that serve as a staple food for the majority of people. Maize is one of the most important cereal crops in Ethiopia in general and Southern Nation, Nationalities and Raj. J. Extn. Edu. 19 : 1-9, 2011 2 Raj. J. Extn. Edu. : 19, 2011 Peoples' Regional State (SNNPR) in particular. It serves as a source of both food and cash income. The study area has a long history of the implimentation of extension package. A lot of new technologies have been introduced starting from the establishment of WADU (Wolaita Agricultural Development Unit)the first comprehensive package project started in Ethiopia in 1970 next to CADU (Chilalo Agricultural Development Unit) in Aris region. However, majority of farmers are using their traditional way of farming practices that retarded progress in smallholders’ agriculture. A few farmers are using the recommended modern technologies, as a result they are facing food shortage. Therefore, the main focus of this study was to identify the factors influencing adoption of the new maize technologies in the study area. The specific objective of this study is: • To study the factors affecting adoption of maize production technology among farmers in the study area. RESEARCH METHODOLOGY The farmers were categorized as adopters when they adopted the recommended improved maize technology (either of three improved varieties being recommended in the area, namely Pioneer (PHB3253), BH540 and CG4141). The study Woreda was selected purposively based on accessibility, potential to maize production and representativeness of the Zone. The Woreda consists 51 Peasant Associations. Out of these, 4 PAs were selected by using simple random sampling techniques. To give equal chance in selection of study units from each concerned PA, probability proportional to size (PPS) was applied. Finally, through systematic sampling techniques sampling units were selected from each PA for both adopters and non-adopters. Total 150 farmers were selected. Out of this adopter and non-adopter were 64 and 86 respectively. Variables Description and measurement Age Age of household head (year). FMLSZ Family size of household (number). LABR Labor availability (man equivalent). EDUCTN Formal education of household head (grades or number of years in school). EXPRC Farm experience of household (years). HOUSE Ownership of house, dummy variable, 1; if a farmer owns corrugated metal-roofed house, 0 otherwise. FRMSZ Farm size of household (hectare). OXEN The number of oxen owned (number). TRLU Total livestock owned by the farm household (TLU). AVALFER Availability of fertilizer on time, dummy variable, 1; if fertilizer is available on time, 0 otherwise. CASH Cash shortage faced by household head, dummy variable, (=1, if yes; =0, otherwise) CREDIT Access of farmer to fertilizer and seed on credit (=1, if yes; =0, otherwise) EXVST Number of time extension agent visited/advised farmer ( number). DMOSTN Farmer attended on demonstration of improved maize production technology, dummy variable (=1, if yes; =0, otherwise). FIELDHS Farmers host demonstration on their farm, dummy variable (=1, if yes; =0, otherwise). RADIO Owning radio at home, dummy variable (=1, if yes; =0, otherwise). TRAIN Farmer attended formal agricultural training, dummy variable (1=, if yes; =0, otherwise). OFFRM Farmers engaged in off farm activities, dummy variable (=1, if yes; =0, otherwise) INPRICE The price condition of agricultural inputs (fertilizer and improved maize seed), dummy variable (=1, expensive; =0, other wise). DISTNCE Distance of the respondents' house from input and output market (km). Table 1. Definition and units of measurement of the variables in the logistic regression Determinants of Adoption of Improved Maize Technology in Damot Gale, Wolaita, Ethiopia 3 Both primary and secondary data were used for this study. Analytical Framework Different analytical techniques were applied to examine the survey data. These include, t-tests, chi-square tests, and logistic regression model. Frequency and means computed for different variables. The chisquare was used to see if there is systematic association between adoption and some of the farm characteristics. The logit model applied in this study to assists in estimating the probability of adoption of improved maize technologies that can take one of the two values adopt or do not adopt the technologies. RESULTS AND DISCUSSION According to descriptive analysis, some variations were observed between adopters and non-adopter in terms of household characteristics, farm and institutional factors (table 2). The two groups differ to some extent in their farm experience, level of education, farm size, livestock possession, income generated from on-farm and off-farm, access to credit, extension information. The study revealed that adopters have better educational background than non-adopters. In terms of farm experience, average farm experience of adopter was about 20.8 years while non-adopters comprise 18 years of farm experience. Average farm size of adopters' was more than non-adopters. Livestock ownership was another important household's characteristic. Average livestock owned by the total sampled households was 3.5 TLU. Proportionally, adopters owned almost twice greater livestock than nonadopters. Variations were also observed in other socio-economic and institutional factors. This study also examined the extent of adoption of improved maize technologies and chemical fertilizers among users. Even though, many factors constraints farmers from using improved maize varieties and chemical fertilizer, more proportion of cultivated land was allocated during 2004/05 cropping season. Most of the farmers did not follow the recommendations of rate of seed, type of fertilizer and rate of application. The rate of improved maize seed applied per hectare was slightly above the recommended rate. The study showed that the rate of fertilizer applied below the recommended rate. In addition, farmers tend to use DAP fertilizer than using both types as per the recommendations. Ttests and chi-square (?2) tests were used to make sure presence or absence of difference between the two groups of farmers, when appropriate. Variable Adopters Non adopters Total sample t-value Mean St.dv. Mean St.dv. Mean St.dv. 1. AGE 40.27 10.11 37.51 9.65 38.69 9.89 1.697* 2. FMLSZ 7.92 3.55 6.53 2.079 7.13 2.89 2.98*** 3. LABR 3.66 1.82 3.3 1.5 3.43 1.66 1.42 4. EDUCTN 3.97 3.99 3.06 3.25