The objective of this study was to define breeding objectives and consequently determine optimum crossbreeding levels for goats in the smallholder production systems. Profits and economic values (EVs) were estimated for four genotypes namely (a) original stock or local goat breeds with 0% German Alpine blood level (OS), (b) F1 with 50% German Alpine blood level (F1), (c) first backcross with 75% German Alpine blood level (B1) and (d) second backcross with 87.5% German Alpine blood level (B2). The EVs were estimated for average daily milk yield (DMY, kg), average post-weaning daily gain (ADG, kg), number of kids weaned (NKW), mature weight (MW, kg) and 12-month live weight (LW, kg). Profitability in Kenyan Shilling (KES) without risk was optimal (KES 6038.02) for the B1 genotype. Economic values without risk for most traits were highest for the F1 genotype, i.e., KES 64.85 (ADG), 24.02 (NKW), -27.55 (MW) and 84.51 (LW). There was, however, a 23% reduction in profits in the F1 genotype. It was evident that crossbreeding would improve the profitability of the smallholder farms, but not beyond the 75% grade level. A similar trend was observed when risk was incorporated. Differences in profitability with and without risk were less than 0.005% for all the genotypes. However, differences in EVs were large, ranging from -28% to +19%; DMY had the largest differences. Therefore, incorporation of risk in estimation of EVs for traits of importance is necessary. This study has also demonstrated that crossbreeding to a higher grade level is not necessarily compensated for by a high performance in most traits. Therefore, a crossbreeding program targeting B1 (75%) crossbreds would be desirable for implementation in the smallholder production systems.

Genetic and phenotypic parameters were estimated for lamb growth traits for the Dorper sheep in semi-arid Kenya using an animal model. Data on lamb growth performance were extracted from available performance records at the Sheep and Goats Station in Naivasha, Kenya. Growth traits considered were body weights at birth (BW0, kg), at 1 month (BW1, kg), at 2 months (BW2, kg), at weaning (WW, kg), at 6 months (BW6, kg), at 9 months (BW9, kg) and at yearling (YW, kg), average daily gain from birth to 6 months (ADG0–6, gm) and from 6 months to 1 year (ADG6–12, gm). Direct heritability estimates were, correspondingly, 0.18, 0.36, 0.32, 0.28, 0.21, 0.14, 0.29, 0.12 and 0.30 for BW0, BW1, BW2, WW, BW6, BW9, YW, ADG0–6 and ADG6–12. The corresponding maternal genetic heritability estimates for body weights up to 9 months were 0.16, 0.10, 0.10, 0.19, 0.21 and 0.18. Direct-maternal genetic correlations were negative and high ranging between -0.47 to -0.94. Negative genetic correlations were observed for ADG0–6–ADG6–12, BW2–ADG6–12, WW–ADG6–12 and BW6–ADG6–12. Phenotypic correlations ranged from 0.15 to 0.96. Maternal effects are important in the growth performance of the Dorper sheep though a negative correlation exists between direct and maternal genetic effects. The current study has provided important information on the extent of additive genetic variation in the existing flocks that could now be used in determining the merit of breeding rams and ewes for sale to the commercial flocks. The estimates provided would form the basis of designing breeding schemes for the Dorper sheep in Kenya. Implications of the study to future Dorper sheep breeding programmes are also discussed.

To augment the incomes of smallholder farmers in Kenya and consequently improve their nutrition and income, many development organisations and policy makers are increasingly promoting dairy goat farming. Among the key organisations supporting the initiative is Heifer Project International–-Kenya (HPIK). However, the economic contribution and viability of dairy goats under the HPIK project have not been studied so far. The aim of the present study was to determine the contribution of dairy goats to household income and the performance of the dairy goat enterprise using gross and net margins from dairy goat farming as an indicator of economic viability. A survey covering 71 farmers was carried out in the Coast, Nyanza, and the Rift Valley provinces of Kenya using a set of pre-tested structured and semi-structured questionnaires. Results showed that, on average, the dairy goat enterprise contributed, correspondingly, about 15.2{%} and 4.8{%} to the total livestock and overall household income and was viable. Differences in gross and net margins across agroecological zones were attributed to milk prices. Despite the existence of non-viable enterprises in two of the provinces, the few present suggest the possibility of obtaining reliable incomes from the enterprise. Redoubling of effort or re-orientation of production to match the local and external requirements would, however, be necessary. Costs and revenues were similar across the agroecological zones. Farmers with positive gross margins had better milk and stock sales and vice versa. The success of a dairy goat enterprise is attributed to location and good management. Besides, farmers’ awareness of the market demands within and outside the community is important in establishing production goals and may be crucial to achieving a positive gross margin.

A deterministic approach was used to compare breeding strategies utilizing local and imported semen for improvement of dairy cattle in Kenya. The local selection programs considered were a closed progeny testing scheme (CPT) and a young bull system progeny of local bulls (PLB). The continuous semen importation (CSI) and young bull system progeny of imported bulls (PIB) were the strategies based on imports. The breeding strategies were compared on the basis of selection response. The effect of genetic correlation (rg) and initial differences in genetic merit between the two populations was also examined. The CSI and PIB strategies ranked above CPT by, correspondingly, 35.1{%} and 25.0{%} when the rg between Kenya and the USA was assumed to be one. At a rg of 0.58, imports from countries which are 1.50 standard deviation (SD) above the local population were superior to CPT but equal to PLB. This means that if CSI is to be used at a rg of 0.58, then only semen from countries which are >1.50SD should be imported. At a rg of 0.70 and with an initial genetic difference of 1.25SD, the economic responses in CSI and PLB were equal. This indicates that semen importation is only justified when genotype–environment interaction is >0.70. It is concluded that wholesale importation of semen as a means of achieving sustainable genetic progress in Kenya is a less optimal solution and there is the need for an effective local selection program.

Data consisting of 8922 weight records from 2642 Dorper sheep from 20 to 380 days of age spanning 1981–1996 were used to model the growth trajectory using random regression (RR) and estimate genetic parameters. The independent variables were orthogonal (Legendre) polynomials of age at weighing and orders of fit up to 3 were considered. Analyses were carried out fitting sets of RR coefficients due to direct and maternal additive genetic and environmental effects, and heterogeneous error variances. Direct additive genetic variance increased steadily along the trajectory from 0.9 at 20 days of age to 2.44 at 380 days of age. Maternal additive genetic variance increased steadily along the trajectory from 0.13 to 2.92. Direct permanent environmental effect variances increased steadily from a value of 0.66 at 20 days to 2.13 at 380 days of age. Maternal permanent environmental variances declined from 0.87 at 20 days of age to 0.01 at 200 days of age followed by an increase to 0.87 at 380 days. Direct genetic heritability estimates declined sharply from 0.13 at 20 days to 0.07 at 80 days of age then fluctuated thereafter. Maternal genetic heritability estimates increased along the trajectory up to 320 days of age after which it declined slightly. The genetic and phenotypic correlations decreased with increasing lag in time between the weights. The Dorper sheep growth was adequately modeled using RR models despite the limited data. This study has demonstrated the possibility of application of RR models for routine genetic evaluation of Dorper sheep in Kenya.