Breeding objectives for indigenous chicken: model development and application to different production systems.

A bio-economic model was developed to evaluate the utilisation of indigenous chickens (IC) under different production systems accounting for the risk attitude of the farmers. The model classified the production systems into three categories based on the level of management: free-range system (FRS), where chickens were left to scavenge for feed resources with no supplementation and healthcare; intensive system (IS), where the chickens were permanently confined and supplied with rationed feed and healthcare; and semi-intensive system (SIS), a hybrid of FRS and IS, where the chickens were partially confined, supplemented with rationed feeds, provided with healthcare and allowed to scavenge within the homestead or in runs. The model allows prediction of the live weights and feed intake at different stages in the life cycle of the IC and can compute the profitability of each production system using both traditional and risk-rated profit models. The input parameters used in the model represent a typical IC production system in developing countries but are flexible and therefore can be modified to suit specific situations and simulate profitability and costs of other poultry species production systems. The model has the capability to derive the economic values as changes in the genetic merit of the biological parameter results in marginal changes in profitability and costs of the production systems. The results suggested that utilisation of IC in their current genetic merit and production environment is more profitable under FRS and SIS but not economically viable under IS.

Application of risk-rated profit model functions in estimation of economic values for indigenous chicken breeding.

The economic values for productive (egg number, average daily gain, live weight, and mature weight) and functional (fertility, hatchability, broodiness, survival rate, feed intake, and egg weight) traits were derived for three production systems utilizing indigenous chicken in Kenya. The production systems considered were free-range, semi-intensive, and intensive system and were evaluated based on fixed flock size and fixed feed resource production circumstances. A bio-economic model that combined potential performances, feeding strategies, optimum culling strategies, farmer's preferences and accounted for imperfect knowledge concerning risk attitude of farmers and economic dynamics was employed to derive risk-rated economic values. The economic values for all the traits were highest in free-range system under the two production circumstances and decreased with level of intensification. The economic values for egg number, average daily gain, live weight, fertility, hatchability, and survival rate were positive while those for mature weight, broodiness, egg weight, and feed intake were negative. Generally, the economic values estimated under fixed feed resource production circumstances were higher than those derived under fixed flock size. The difference between economic values estimated using simple (traditional) and risk-rated profit model functions ranged from -47.26% to +67.11% indicating that inclusion of risks in estimation of economic values is important. The results of this study suggest that improvement targeting egg number, average daily gain, live weight, fertility, hatchability, and survival rate would have a positive impact on profitability of indigenous chicken production in Kenya.

Factors that influence the efficiency of beef and dairy cattle recording system in Kenya: A SWOT-AHP analysis.

Animal recording in Kenya is characterised by erratic producer participation and high drop-out rates from the national recording scheme. This study evaluates factors influencing efficiency of beef and dairy cattle recording system. Factors influencing efficiency of animal identification and registration, pedigree and performance recording, and genetic evaluation and information utilisation were generated using qualitative and participatory methods. Pairwise comparison of factors was done by strengths, weaknesses, opportunities and threats-analytical hierarchical process analysis and priority scores to determine their relative importance to the system calculated using Eigenvalue method. For identification and registration, and evaluation and information utilisation, external factors had high priority scores. For pedigree and performance recording, threats and weaknesses had the highest priority scores. Strengths factors could not sustain the required efficiency of the system. Weaknesses of the system predisposed it to threats. Available opportunities could be explored as interventions to restore efficiency in the system. Defensive strategies such as reorienting the system to offer utility benefits to recording, forming symbiotic and binding collaboration between recording organisations and NARS, and development of institutions to support recording were feasible.

Influence of major genes for crested-head, frizzle-feather and naked-neck on body weights and growth patterns of indigenous chickens reared intensively in Kenya.

The influence of major genes for crested-head (Cr), frizzle-feather (Fr) and naked-neck (Na) on body weights and growth patterns of indigenous chickens reared intensively was investigated and compared with normal-feather (na) gene. Birds were individually weighed at hatch and every two weeks up to 30 weeks of age. Growth patterns were modelled using the Gompertz-Laird function. The genes influenced body weights and growth patterns at various ages. The Cr gene had significant (P < 0.05) negative effects on body weights (between 52.2 g and 112.3 g) from 18 weeks onwards and low absolute growth rate from 10 to 22 weeks than na, but higher initial specific growth and maturation rates than the Na gene. The Fr gene had significant negative effects on body weights (between 28.2 g and 75.1 g) from 8 to 16 weeks than na, but a higher relative growth rate than Cr from 12 to 16 weeks. The Na gene had significant negative effects on body weights (between 24.7 g and 134.6 g) from 8 weeks onwards than na. It was concluded that Frfr and Nana genotypes are not ideal for cool environments in Kenya and indigenous chicken genotypes have varied growth potentials and patterns that can be improved to increase production.