DETERMINANTS OF ARTIFICIAL INSEMINATION USE BY SMALLHOLDER DAIRY FARMERS IN LEMU-BILBILO DISTRICT, ETHIOPIA

ABSTRACT
Despite Ethiopia possessing the highest number of livestock in Africa, its benefit to the country and smallholder farmers is small. This is to a large extent attributed to the dominance of low producing local cattle breeds. Though the government introduced Artificial Insemination (AI) technology to improve this condition, the adoption rate by smallholder farmers is still low. The main objective of this study was, therefore, to examine the adoption of AI technology by smallholder dairy farmers in Lemu-Bilbilo district, Ethiopia. The specific objectives were to characterize adopters and non-adopters of AI, to determine factors affecting adoption of AI and to determine the extent of adoption and factors affecting the extent of adoption. Purposive selection of the area and random sampling procedures were employed to select a sample of 196 smallholder dairy farmers. Data was collected using interview schedule via semi-structured questionnaires. The data was analyzed using Statistical Package for Social Sciences and STATA. Adopter and non-adopter farmers were significantly different with respect to education level, off-farm income, membership in dairy cooperatives, extension contacts, experience with crossbreeds, feeding concentrates to cows, access to credit, income from milk products sales and distance from AI station. The double-hurdle model was used for econometric analysis whereby the two stages were run separately as Probit and truncated regression, respectively. Contacts with extension agents, access to credit, income from milk sales, feeding concentrate to cows and family size influenced the probability of adoption without affecting the extent of adoption. While membership in dairy cooperatives and off-farm income positively affected the probability and extent of AI adoption, distance from AI station and access to crossbred bull services influenced both variables negatively. A further walking distance of one hour to the AI station was associated with 27% and 14.4% reduction in the probability and extent of adoption, respectively. Membership in dairy cooperatives and off-farm income can be instrumental in AI adoption due to milk market guarantee and the strengthening of financial capacity from off-farm income. Farmers located at farther distances from AI station and those with access to crossbred bulls preferred to use bulls than AI. Access to AI should be improved by expanding AI stations throughout the district along with training more AI technicians. Awareness creation especially on the difference between using AI and bull service must be done. Deploying adequate number of extension workers, educating farmers in farmers' training centres and field day visits can be the way forward. Dairy cooperatives and microfinance institutions must be established and strengthened. Ways of milk marketing at farm-gate should be designed, infrastructural development (especially road) should be considered.

CHAPTER ONE 
INTRODUCTION 
Background of the Study 
Ethiopia is an agrarian economy located in the horn of Africa. Agriculture sector employs more than 80 percent of the population and contributes about 43 percent to the total GDP and 90 percent to the foreign exchange earnings (MoARD, 2010). With its 49.33 million heads of cattle, Ethiopia is the leading country in cattle population in Africa and ninth on the world (CSA, 2008). The contribution of livestock and livestock products to the agricultural GDP of Ethiopia accounts for 40 percent, excluding the values of draught power, transport and manure. Smallholder farming is considered one of the most important in the agricultural sector in Ethiopia. It is a source of income, food security and indicates prestige and social status in the rural community (Kedija et al., 2008). More than 99 percent of Ethiopia's cattle have been reported to be indigenous breeds and small Zebu types that are poor in major economically important traits. Crossbreeds and pure exotic breeds constitute only 0.5 and 0.1 percent of the total cattle population, respectively (EASE, 2003). 

In the previous decades, the productivity of livestock sector dominated by traditional practices failed to satisfy the food security needs of the country’s population at times resulting in severe food scarcity. The development strategy of the Ethiopian government recognizes the leading role of agriculture in the economy and stipulates that for the country to register rapid economic prosperity, it should follow the path of Agricultural Development Led Industrialization (FDRE, 2002; Abraham, 2009). 

The per capita milk consumption of Ethiopia estimated at 19 kg per year; is lower than African and world per capita averages, which are 27 kg and 100 kg per year, respectively (ESAP, 2004). In Ethiopia, one of the leading causes of infant mortality is malnutrition. Although milk is considered nature’s perfect food for the growing infant, the ever rising scarcity and high cost of milk and dairying has made it impossible to meet the demand. Reports also showed that there is increasing trend in import of milk and dairy products and a considerable amount of foreign exchange is spent on the import of dairy products (Felleke, 2003). The value of imports of milk products in the first half year increased from 48 billion Birr in 2005 to over 114 billion Birr in 2010. The price of milk in Ethiopia is more than tripled in 10 years. This clearly depicts the presence of a wide gap between the supply and demand of milk and milk products (Land O’Lakes, 2010; NBE, 2011). 

In order to improve the low productivity of the indigenous Zebu cattle, selection of the most promising breeds and crossbreeding of these indigenous breeds with high producing exotic cattle has been considered as a practical solution (Mekonnen, T. et al., 2010). Selection and controlled breeding of superior animals has been found to increase productivity. The development and use of Artificial Insemination technique has also revolutionized cattle production and genetic improvement, particularly in the dairy sector in developed countries (Henning et al., 2010). Artificial insemination is the single most important technique ever devised for genetic improvement of animals in all aspects including milk and beef production (Kaaya et al., 2005). 

While more than 70 percent of animals are bred using AI in the developed world, the technology is almost practically not available in 25 developing countries 16 of which are found in Africa (Kaaya et al., 2005). In Ethiopia, AI technology was introduced 5 decades ago through Chilalo Agricultural Development Unit (CADU) project which was importing semen. But later on, because of the importance of the technology, National Artificial Insemination Centre (NAIC) was established in Addis Ababa in the year 1981 (ESAP, 2008; Abraham, 2009). In Arsi zone, where Lemu-Bilbilo district is located, cattle rearing along with land cultivation is the most common economic activity as 99.6 percent of the households in the zone own cattle (MoARD, 2007). Artificial insemination was started in the Lemu-Bilbilo district in 1971 soon as the technology was introduced in to the country. 

Although Ethiopia has the largest livestock population in Africa, productivity and production have remained low. Unlike other African countries such as the neighbour Kenya, the large cattle population of Ethiopia has relatively limited numbers of exotic dairy cattle and their crosses. Less than 1 percent of the dairy cattle population of Ethiopia is exotic or crossbred cows (EASE, 2003). According to the Tegegne and Hoekstra (2011), Kenya has more than 100 times crossbred cows than Ethiopia. Consequently, milk productivity in Ethiopia is low. According to CSA (2008) report, the total annual milk production from about 10 million milking cows in Ethiopia is estimated at about 3.2 billion litres, which is translated into 1.54 litres per cow per day (Kedija et al., 2008).

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Item Type: Kenyan Postgraduate Material  |  Attribute: 75 pages  |  Chapters: 1-5
Format: MS Word  |  Price: KSh900  |  Delivery: Within 30Mins.
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