Economic values for production traits (milk yield, MY, g; 12-month live weight, yLW, kg; consumable meat percentage, CM, {%}) and functional traits (mature doe live weight, DoLW, kg; mature buck live weight, LWb, kg; kidding frequency, KF; pre-weaning survival rate, PrSR, {%}; post-weaning survival rate, PoSR,{%}; doe survival rate, DoSR, {%}; and residual feed intake, RFI, kg) were estimated using profit functions for the Small East African goat. The scenario evaluated was a fixed flock size, and the resultant economic values (Kes per doe per year) were 34.46 (MY), 62.35 (yLW), 40.69 (CM), 0.15 (DoLW), 2.84 (LWb), 8.69 (KF), 17.38 (PrSR), 16.60 (PoSR), 16.69 (DoSR) and -3.00 (RFI). Similarly, the economic values decreased by -14.7 {%} (MY), -2.7 {%} (yLW), -23.9 {%} (CM), -6.6 {%} (DoLW), -98 {%} (LWb), -8.6 {%} (KF), -8.2 {%} (PrSR), -8.9 {%} (PoSR), -8.1 {%} (DoSR) and 0 {%} (RFI) when they were risk rated. The economic values for production and functional traits, except RFI, were positive, which implies that genetic improvement of these traits would have a positive effect on the profitability in the pastoral production systems. The application of an Arrow-Pratt coefficient of absolute risk aversion ($łambda$) at the level of 0.02 resulted in a decrease on the estimated economic values, implying that livestock keepers who were risk averse were willing to accept lower expected returns. The results indicate that there would be improvement in traits of economic importance, and, therefore, easy-to-manage genetic improvement programmes should be established.

This study estimated economic values (EVs) for disease resistance traits for dairy/crossbred goats in Kenya. The traits mean somatic cell count (SCC, cells/μl) and faecal worm egg count (FEC, epg) were taken as indicator traits for the most prevalent diseases in the smallholder farms i.e., mastitis and helminthiosis, respectively. Economic weights were objectively assigned to these indicator traits in a selection index such that the overall gains in the breeding objective traits were maximised. Four options for calculating EVs for SCC and FEC were considered. Option 1, response from single trait selection was set equivalent to index response for the trait. Option 2, response from single trait selection was set equivalent to maximum gains achievable. Option 3, level of FEC/SCC was set to zero; and option 4, response in FEC/SCC was set to the minimum gains achievable. In all the options, EVs with/without risk for breeding objective traits 12-month live weight (LW-kg); ADG, average post-weaning daily gain (ADG-g); DMY, average daily milk yield (DMY-kg) were used. For each production trait selected for improvement, a less positive response in the traits FEC and SCC would be desirable. Maximum negative EVs were achieved at a point where the response in SCC was set at zero (option 3) while EVs for SCC were zero when response for DMY was maximised (option 2). In addition, considerable differences in EVs for SCC were obtained when EVs with/without risk were used. Similar results were also observed for FEC when LW was the objective of improvement. However, more positive EVs for FEC were estimated relative to ADG and DMY. The results confirm that there is a scope to incorporate disease resistance traits in a breeding program with objective of reducing disease incidences and the costs of disease control.