Response to hormonal treatment and conception rates of Sahiwal cows subjected to fixed time artificial insemination in pastoral dairy systems.

This study aimed at determining factors influencing response of Sahiwal cows/heifers to fixed time artificial insemination protocol in pastoral systems in Kenya. Available cows/heifers were inspected for conformity to Sahiwal breed characteristics, parity, body condition score, and subsequently rectal palpation to determine pregnancy status, ovarian structures, and estimated ovarian diameter. Consequently, these animals were injected with 100 µg of gonadotrophin-releasing hormone. On days 7 and 9, only responsive cows/heifers were injected with 500 µg of cloprostenol and 100 µg of gonadorelin Acetate, respectively. On day 10, animals were inseminated and separated from bulls for 45 days and pregnancy diagnosis done after 90 days. Analysis of variance was performed to determine the effects of production system, parity, and ovarian structures on ovary diameters pre- and post-hormonal treatment. Logistic regression was used fitting a logit function to account for the binomial distribution of conception. Overall, 56.2%, 23.1%, and 20.7% of the animals had follicles (F), corpus luteum (CL), and corpus albicans (CA), respectively, at day 0, and 16.6%, 68.6%, and 14.8%, respectively, at day 7. Human and environmental factors had no influence on conception. Among the animal factors, only the ovarian structures at day 7 had a significant effect on conception. Ovaries with CL at this time were about 6 times significantly more likely to conceive than those with F. For higher conception rates, animals with ovaries with CL should be recruited into the FTAI program as they are significantly more likely to conceive than those with other ovarian structures.

Genetic parameters for test-day milk yield, lactation persistency, and fertility in low-, medium-, and high-production systems in Kenya.

Genetic parameters for test-day milk yield, lactation persistency, and age at first calving (as a fertility trait) were estimated for the first 4 lactations in multiple-breed dairy cows in low-, medium-, and high-production systems in Kenya. Data included 223,285 test-day milk yield records from 11,450 cows calving from 1990 to 2015 in 148 herds. A multivariate random regression model was used to estimate variance and covariance components. The fixed effects in the model included herd, year, and test month, and age as a covariate. The lactation profile over days in milk (DIM) was fitted as a cubic smoothing spline. Random effects included herd, year, and test month interaction effects, genetic group effects, and additive genetic and permanent environmental effects modeled with a cubic Legendre polynomial function. The residual variance was heterogeneous with 11 classes. Consequently, the variance components were varied over the lactation and with the production system. The estimated heritability for milk yield was lower in the low-production system (0.04-0.48) than in the medium- (0.22-0.59) and high-production (0.21-0 60) systems. The genetic correlations estimated between different DIM within lactations decreased as the time interval increased, becoming negative between the ends of the lactations in the low- and medium-production systems. Low (0.05) to medium (0.60) genetic correlations were estimated among first lactation test-day milk yields across the 3 production systems. Genetic correlations between the first lactation test-day milk yield and age at first calving ranged from 0.27 to 0.49, 0 to 0.81, and -0.08 to 0.27 in the low-, medium-, and high-production systems, respectively. Medium to high heritabilities (0.17-0.44) were estimated for persistency, with moderate to high (0.30-0.87) genetic correlations between 305-d milk yield and persistency. This indicates that genetic improvement in persistency would lead to increased milk yield. The low to medium genetic correlations between test-day milk yield between production systems indicate that sires may be re-ranked between production systems. Therefore, we conclude that sires should be selected based on a genetic evaluation within the target production system.