Tesfaye A., Alemayehu L., Tefera Y., Endris A.
Samara University, College of Veterinary Medicine, P.O.Box 132, Samara, Ethiopia
Tesfaye, A., Samara University, College of Veterinary Medicine, P.O.Box 132, Samara, Ethiopia; Alemayehu, L., Samara University, College of Veterinary Medicine, P.O.Box 132, Samara, Ethiopia; Tefera, Y., Samara University, College of Veterinary Medicine, P.O.Box 132, Samara, Ethiopia; Endris, A., Samara University, College of Veterinary Medicine, P.O.Box 132, Samara, Ethiopia
The objective of this study was to investigate the effect of some factors on the reproductive performance of smallholder dairy cows under artificial insemination (AI) in two regions of Ethiopia. A cross-sectional study and retrospective data analysis were conducted on 428 farm characteristics and management, 644 cow reproductive histories and 613 inseminations by examining records and a questionnaire survey. Mean days for calving to first service interval (CFSI) and calving to conception interval (CCI) were 222 (n=320) and 257(n=234) days, respectively. Service per conception (SPC) was 1.54 and first service conception rate (FSCR) was 41.8%. The relationship between reproductive performance and risk factors was described by using proportion of submitted cows to first service by day 201 after calving (SUB201), pregnant cows by day 228 after calving (PREG228) and non pregnant cows by day 305 after calving (NPREG305). The proportions for SUB201, PREG228 and NPREG305 were 35%, 28% and 52%, respectively. Site, body condition score (BCS) and management systems were associated to SUB201, PREG228 and NPREG305. The odds for BCS <3 to that of BCS>3 were 0.379, 0.297 and 2.03 for SUB201, PREG228 and NPREG305, respectively. Farms with intensive management system had odds of 1.99, 1.77 and 0.533 for SUB201, PREG228 and NPREG305, respectively to that of extensively managed farms. The performance of the AI service in the area had association to SUB201 and NPREG305. BCS, age of the cow, management system and AI service performance were factors to affect the reproductive performance of the smallholder dairy farms. Thus, increasing reproductive performance should overcome the challenge of nutritional and AI management. © iForest – Biogeosciences and Forestry.