Multi-country investigation of factors influencing breeding decisions by smallholder dairy farmers in sub-Saharan Africa

Abstract

Artificial insemination (AI) and selective bull mating are considered as robust methods for dairy cattle breeding. Globally, these methods have been used to enhance productivity and realize rapid genetic gains. However, these technologies have had low adoption rates in sub-Saharan Africa (SSA). Even though available evidence suggests that this is due to various infrastructural and technical challenges. There is limited information about what drives this low uptake of AI from a farmer's perspective. Therefore, the main objective of this study was to determine and characterize factors that influence the choice by smallholder farmers between bull service and AI for dairy cow breeding. Further, the relationships between the breeding choices and the bio-physical elements of dairy farming, mainly, farmer characteristics, household income levels, farm management practices, and institutional support structures, were investigated. Data were collected through face-to-face interviews from a total of 16,308 small-scale dairy farmers in Ethiopia (n = 4679), Kenya (n = 5278), Tanzania (n = 3500), and Uganda (n = 2851). The questionnaire was coded in an electronic form using Open Data Kit (ODK) platform to allow for real-time data entry and management. Descriptive statistics, chi-square test, and a t-test were used to evaluate the independent and dependent variables, while logistic regression and factor analysis were used to identify factors that influenced farmers' breeding decisions. Results showed that there was a significant difference in animal husbandry practices between farmers who used artificial insemination (AI) and those who practiced bull mating. The majority of farmers who used AI kept records, purchased more animal feeds, had more labor by hiring workers whose average wages were higher than those of bull service farmers. However, farmers who used AI pay more for services such as water access and breeding while their service providers had to cover long distances compared to farmers who used bulls. This indicates limited access to services and service providers for AI farmers. The ratio of AI to bull service users was even for Ethiopia and Kenya, while in Uganda and Tanzania, more farmers preferred bull service to AI. It was established that the factors that influence farmers' breeding decision were not the same across the region. Factors such as farmer's experience in dairy farming, influence of the neighbor, farmer's ability to keep records, and management practices such as water provision and availability of feeds had a significant association (p < 0.001) with AI adoption among dairy farmers. In contrast, large herd and large land size negatively influenced AI adoption. Institutional settings including cost of AI service and the distance covered by the service provider negatively affected (p < 0.001) the choice of AI as a breeding option. There was a high probability of continued use of a specific breeding method when there was a previous conception success with that same method. Based on the results obtained, we...

Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda

“…The study additionally reveals the dominance of farms characterized as small-scale, subsistence, extensive, and low productive. This is in line with previous studies that also reported that most farmers in sub-Sahara African countries are small-scale and subsistence in nature [46,84,85]. Though some studies have found small-scale farms to be more productive and efficient [86,87], others have challenged this finding, reporting that small farms are characterized by low efficiency, low productivity, and weak integration into the market [88][89][90].…”

Characterization of dairy innovations in selected milksheds in Kenya using a categorical principal component analysis

“…Most (65.0%) farmers of NKCC Sotik (state-owned processor) were in cluster 1 which was characterized by not housing cows at night, use of bull as main method of reproduction, weekly spraying of cows, and low proportion of farmers selling milk through groups. The reason for use of bull in reproduction could be as a result of farmers having large pieces of land to rear bulls (Mwanga et al 2019 ), farmers getting discouraged to use AI due to its high cost and cases of repeated inseminations that further increase costs (Mburu et al 2016 ). The finding of low use of AI services in the study area was congruent with the findings of Kenduiwa et al ( 2016 ) who studied the influence of smallholder dairy farmers’ participation in microfinance on breed improvement in dairy farming in Bomet County.…”

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Analysis in making decision of farmer to select bull frozen semen in Indonesia

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