Evidence map›Paper›PMID 40745516›Full record

ArticleTropical animal health and production2025

Adoption and intensity of artificial insemination technology for dairy cattle in Ethiopia.

Amenu Leta Duguma, Tesfaye Solomon, Xiuguang Bai

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Article in Tropical animal health and production, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Amenu Leta DugumaCollege of Economics and Management, Northwest A&F University, Yangling, 712100, China.
Tesfaye SolomonDepartment of Agricultural Economics, Mattu University, P.O. Box 318, Mattu, Ethiopia.
Xiuguang BaiCollege of Economics and Management, Northwest A&F University, Yangling, 712100, China. baixg960@nwafu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of artificial insemination (AI) has become a transformative technology to improve the reproductive efficiency of cattle. Nonetheless, the adoption and intensity of AI utilization among dairy farmers remain minimal. This study aimed to identify the key factors influencing the adoption and intensity of artificial insemination (AI) technology in dairy cattle production in the Bedele district of Ethiopia. We measured the intensity of AI adoption by the number of calves born through AI. Data from 162 household heads were analyzed using the Double Hurdle model. The probit regression analysis indicated that education level, non-farm income, landholding size, and experience with AI all affect the use of AI technology. Moreover, access to credit and consistent engagement with extension services substantially enhanced the probability of adopting AI in dairy cattle. While gender, age, proximity to the AI center, and dependency ratio adversely and significantly influence the adoption decision. The truncated regression results showed that the amount of AI use is positively related to the education level of household heads, the size of the landholding, experience with AI, the availability of credit, and extension contact. The extent of AI technology utilization in dairy cattle is adversely and significantly influenced by factors such as age and proximity to the AI center. The government is encouraged to improve education, support effective use of artificial insemination (AI), promote non-farm income activities, strengthen extension services, upgrade infrastructure, empower female-headed households, and enhance access to affordable credit within the study area.

Indexed as

Animal HusbandryDairyingInsemination, ArtificialAnimalsCattleEthiopiaFemaleMaleRegression AnalysisAdoptionArtificial insemination technologyDairy cattleEthiopiaIntensity

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.