Artificial Insemination in Smallholder Farming: An Exploration of Farmer Perspectives and Determinants in Beitbridge, Zimbabwe
Keywords:
Artificial insemination technology, Smallholder farming systems, Cattle Farmers perceptions, Adoption determinants, Beitbridge, ZimbabweAbstract
This study investigated the perceptions of communal farmers in Beitbridge, Zimbabwe, regarding the adoption of artificial insemination (AI) technology in cattle breeding. A semi-structured questionnaire was administered to 80 cattle farmers who had participated in the Zimbabwe Resilient Building Fund Government Communal Cattle Insemination program between 2017 and 2021. The results revealed that 99% of the farmers did not regularly utilize AI services due to the absence of locally based AI service providers (97.5%), discontinuation of service between government programs, and insufficient knowledge of AI technology (72%). Uncontrolled breeding systems and poor seasonal nutrition were identified as major challenges by 100% and 80% of the farmers, respectively. The majority of farmers (77.5%) preferred using both AI and natural mating if available. The perceived low adoption of AI in communal areas was attributed to a shortage of locally based inseminators, inadequate farmer awareness of assisted reproductive technologies (ARTs), and the absence of structured communal breeding programs. The study recommends collaboration among cattle stakeholders to address the challenges in optimizing cattle productivity through ART implementation and adoption in rural areas, including enhancing the capacity of government workers and lead farmers, decentralizing service providers, and institutionalizing community-led sustainability frameworks. Alternative methods of technology dissemination are also needed to improve farmers' awareness of fundamental aspects of AI and synchronization protocols.
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Copyright (c) 2025 Bruce Tavirimirwa, Grace Tembo, Tendai Dominic Matekenya, Givious Sisito, Andrew Chamisa, Irene Chakoma, Sikhulile Siziba, Soul Washaya, Xavier Zhakata, Never Assan

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.