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.

Modelling of lactation curves of dairy cows based on monthly test day milk yield records under inconsistent milk recording scenarios.

The objective of this study was to describe the lactation curve of dairy cattle in Kenya using a suitable lactation function in order to facilitate inclusion of partial lactations in national dairy cattle evaluation and to assess the effect of data characteristics on lactation curve parameters. Six functions were fitted to test day (TD) milk yield records from six parities of Ayrshire, Guernsey, Holstein Friesian, Jersey and Sahiwal cattle. Five datasets: DS-1 (12-TD dataset with randomly missing records), DS-2 (10-TD dataset without missing records), DS-3 (10-TD dataset with randomly missing records), DS-4 (7-TD dataset, with only TD 4 to 10 records) and DS-5 (7-TD dataset, with TD 1 to 4, 6, 8 and 10 records) depicting various recording circumstances were derived to assess the effects of data characteristics on lactation curves and to assess the feasibility of reducing the number of TD samples per lactation. The fit of the functions was evaluated using adjusted R(2) and their predictive abilities were compared using mean square prediction error, percentage of squared bias and the correlation between the predicted and actual milk yield. These criteria plus the changes in the parameters of curve functions and their associated standard errors were used in determining the effects of data characteristics on lactation curves. The mechanistic functions of Dijkstra (DIJ) and Pollott (APOL), and the incomplete gamma function of Wood (WD) had the highest adjusted R(2) > 0.75. The APOL function was eliminated due to convergence failures when analysis of individual lactations within breeds was carried out. Both DIJ and WD had good predictive ability, although DIJ performed slightly better. Convergence difficulties were noted in some DIJ analysis where data were limiting. Missing records, especially at the beginning of a lactation, greatly influenced parameters a and b of the functions. It also resulted in estimates with large standard errors. Missing records in later lactation hardly affected the parameter estimates. The WD and DIJ functions showed superior fit to the data. The WD function demonstrated higher adaptability to various data characteristics than DIJ and could be used in situations where animal recording is not consistently practised and where recording of animal performance is routinely practised. DIJ function had high data requirements, which restricts it to dairy systems with consistent recording, despite easy physiological interpretation of its parameters. The number of TD per lactation could be reduced by minimising sampling frequency in the later lactation while maintaining the monthly sampling frequency in early lactation.

Direct and maternal (co)variance components and genetic parameters for growth and reproductive traits in the Boran cattle in Kenya.

Direct and maternal (co)variance components and genetic parameters were estimated for growth and reproductive traits in the Kenya Boran cattle fitting univariate animal models. Data consisted of records on 4502 animals from 81 sires and 1010 dams collected between 1989 and 2004. The average number of progeny per sire was 56. Direct heritability estimates for growth traits were 0.34, 0.12, 0.19, 0.08 and 0.14 for birth weight (BW), weaning weight (WW), 12-month weight (12W), 18-month weight (18W) and 24-month weight (24W), respectively. Maternal heritability increased from 0.14 at weaning to 0.34 at 12 months of age but reduced to 0.11 at 24 months of age. The maternal permanent environmental effect contributed 16%, 4% and 10% of the total phenotypic variance for WW, 12W and 18W, respectively. Direct-maternal genetic correlations were negative ranging from -0.14 to -0.58. The heritability estimates for reproductive traits were 0.04, 0.00, 0.15, 0.00 and 0.00 for age at first calving (AFC), calving interval in the first, second, and third parity, and pooled calving interval. Selection for growth traits should be practiced with caution since this may lead to a reduction in reproduction efficiency, and direct selection for reproductive traits may be hampered by their low heritability.

Genetic evaluation of growth of Kenya Boran cattle using random regression models.

Data consisting of 18 884 weight records collected from 1273 Boran cattle from birth to 24 months of age were used to estimate covariance functions and genetic parameters for growth of Boran cattle using random regression (RR) models under a situation of small herd size and inconsistent recording. The RR model fitted quadratic Legendre polynomials of age at recording for additive genetic and permanent environmental effects. Genetic variance increased from birth, reaching an asymptotic value at 455 days and was maximum at 525 days of age after which it gradually dropped. Permanent environmental variance increased throughout the trajectory. Estimates of temporary environmental variance were heterogeneous across ages. Direct heritability and permanent environmental variance as a proportion of phenotypic variance fluctuated greatly during the early ages but later stabilized at intermediate to later ages; the estimates ranged from 0.11 to 0.33 and from 0.18 to 0.83, respectively. Genetic correlation estimates were positive, ranging from 0.10 to unity. The estimates declined with increasing in lag between the age points. Phenotypic correlation pattern was erratic between early ages, negatively low (-0.02) between the extreme data points and moderate to highly positive (>0.50) between intermediate and later points, with prominent spikes along the diagonal. It is concluded that RR models have potential for modelling growth of Boran cattle, notwithstanding conditions of small herd sizes and inconsistent recording.