Factors Affecting Technology Adoption in Small Community Farmers in Relation to Reproductive Events in Tropical Cattle Raised under Dual Purpose Systems

Abstract

The impact of technology adoption among farmers in developing countries has been an issue difficult to measure and interpret. Hence, research to improve production has been centered in technology that possible is not adequate for this region. The present review aims to utilize subjects such as Genetics, Reproduction, Nutrition, Management and Animal Health as examples of research endeavors illustrating the scarcely bond existing between research and adoption of technology. A final section is an attempt to illustrate the possible reasons why the transfer of technology is failing to be of any consequence at least under the conditions of developing countries.

Artificial Insemination in Nyagatare District: Level of Adoption and the Factors determining its Adoption

“…Most of the farmers with 6 to 7 family members showed a significant preference to AI whereas those with small families (up to 3 members) and those with very large families (with over 7 members) preferred to use natural service for breeding (p < 0.05). Our results are consistent with those of some workers (Howley et al, 2012;Dehinenet et al, 2014;Galina et al, 2016) who reported a positive relationship between family size and AI adoption. The results, however, contradict with other reports (Teferal, 2013) who reported that family size was negatively correlated with AI adoption.…”

“…This could be possibly because of the costs involved in the movement of personnel and equipment for the AI procedure. Similar observations were also reported by other scholars (Teferal, 2013;Tebug et al, 2014;Galina et al, 2016;Rathod et al, 2017). Distance was related to increase in costs, which is essentially a hindrance for farmers to use AI.…”

“…In Rwanda, the smallholder dairy sector provides a unique development strategy as a source of livelihood through providing income, home consumption, manure and as a reserve for cash for investment (Lukuyu et al, 2009). It is well known that AI is the quickest reliable way of disseminating advances in genetic resources undertaken in different parts of the world for the benefit of mankind (Howley et al, 2012;Mugisha et al, 2014;Galina et al, 2016). Advantages of AI include genetic improvement of milk production, control of venereal and other diseases, reduction in lethal genes, simplicity and low cost (Howley et al, 2012).…”

“…Simply stated there are farm and farmer factors influencing the adoption of AI (Howley et al, 2012). Factors affecting AI adoption may also be separated into fixed and modifiable factors (Galina et al, 2016). AI adoption is influenced by education level of the farmer, age of farmer, gender of the famer, ethnicity, family size, experience with farming, contact with extension personnel, membership of dairy cooperatives, access to credit, on-farm and off farm income, availability of labour, availability of feed and water and distance to veterinary institution (Mugisha et al, 2014;Martinez-Garcia et al, 2015;Galina et al, 2016;Rathod et al, 2017).…”

“…Factors affecting AI adoption may also be separated into fixed and modifiable factors (Galina et al, 2016). AI adoption is influenced by education level of the farmer, age of farmer, gender of the famer, ethnicity, family size, experience with farming, contact with extension personnel, membership of dairy cooperatives, access to credit, on-farm and off farm income, availability of labour, availability of feed and water and distance to veterinary institution (Mugisha et al, 2014;Martinez-Garcia et al, 2015;Galina et al, 2016;Rathod et al, 2017). In order to support and accelerate increased productivity within the smallholder dairy sector, the Rwandan government established AI centres in sectors within districts run by state veterinarians and AI-trained Animal Health Workers (Paul et al, 2017).…”