Evaluation of smart Dairy system for enhancing Reproductive herd health management in smallholder farms in Bishoftu town,
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Date
2025
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Addis Abeba University
Abstract
The integration of smart dairy farming technologies, encompassing sensors, mobile applications, and data analytics, presents a transformative opportunity for enhancing the productivity, profitability, and sustainability of smallholder dairy farms, particularly in regions like Ethiopia. To evaluate the practical application and impact of a smart dairy system, this study enrolled 30 smallholder farmers managing 519 animals into a virtual “Fertility Control Camp”. Their daily operations were augmented through the experimentation of data acquisition, digital recording via ODK-Collect, data analytics, generation of actionable insights, and a mobile alerting system. From this cohort, 40 cows whose estrus was characterized by CowsVille, dairy farm management software, were randomly selected for monitoring. Estrus detection tools and chemical pregnancy tests provided data that is processed by CowsVille, delivering mobile alerts to farmers. Mean Number Service Conception (NSC), days the last artificial insemination (DALAI), and days last conception (DALC) were 3.12±0.39, 68.23±10.37 days, and 249.07±35.4 days, respectively. The fertility window was identified in all cases (100%), averaging 14.82±0.4 hours, resulting in a FSC rate of 65.8%, significantly higher than the national average. CowsVille integrated with a mobile alert system has proven to be a valuable resource for guiding farmers in making AI-related decisions. Further analysis of 62 cows (38 normal-cycling, 24 repeat-breeding) from the CowsVille database explored estrus detection using physicochemical profiles and Vaginal Electrical Resistance (VER). Conception rates were significantly different (P < 0.05) between normal-cycling (70.6%)
and repeat-breeding cows (41.7%). Body weight, insemination time, and VER significantly affected conception rates (P < 0.05), with optimal results at 7-12 hours poststanding estrus (71.43%), and VER of 181-220 Ω (84.21%). Sperm penetration, spinnbarkeit, VER, and crystallization patterns of cervical fluid proved useful in predicting optimal insemination time. The CowsVille system, combining digital recordkeeping, with analytical capabilities and direct farmer feedback, effectively mitigated the limitations in traditional smallholder management, enabling evidence-based decisions.
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Keywords
CowsVille, Dairy, Estrus, Fertility Control Camp, Mobile alert