The majority of the Kenyan population resides in the rural areas and is characterised by low income and food insecurity leading to high levels of poverty. Poultry production and in particular indigenous chicken (IC) production play a significant role in the economic and social life of these resource-poor households, contributing to cheap source of animal proteins and cash income. Indigenous chickens are present whenever there are human settlements and their economic strength lies in their low cost of production which is a characteristic of the resource-poor rural households. They are highly adapted to the harsh scavenging conditions, poor nutrition and disease and/or parasite challenges. Their low productivity has hindered their exploitation. This paper highlights the current IC production circumstances with a view to identifying the major challenges which need to be addressed in order to improve the IC productivity and thereby improve the livelihood of the rural households who are the custodian of these genetic resources. It is concluded that the IC in Kenya posses high genetic diversity and are popular among the consumers. There is potential to improve IC productivity in Kenya and therefore individual and national efforts are required that takes into account the whole IC production value chain.

Indigenous chicken (IC) and their production systems were characterized to understand how the whole system operates for purposes of identifying threats and opportunities for holistic improvement. A survey involving 594 households was conducted in six counties with the highest population of IC in Kenya using structured questionnaires. Data on IC farmers' management practices were collected and analysed and inbreeding levels calculated based on the effective population size. Indigenous chicken were ranked highest as a source of livestock income by households in medium- to high-potential agricultural areas, but trailed goats in arid and semi-arid areas. The production system practised was mainly low-input and small-scale free range, with mean flock size of 22.40 chickens per household. The mean effective population size was 16.02, translating to high levels of inbreeding (3.12%). Provision for food and cash income were the main reasons for raising IC, whilst high mortality due to diseases, poor nutrition, housing and marketing channels were the major constraints faced by farmers. Management strategies targeting improved healthcare, nutrition and housing require urgent mitigation measures, whilst rural access road network needs to be developed for ease of market accessibility. Sustainable genetic improvement programmes that account for farmers' multiple objectives, market requirements and the production circumstances should be developed for a full realization of IC productivity.

Rwanda has about 4.5 million of indigenous chicken (IC) that are very low in productivity. To initiate any genetic improvement programme, IC needs to be accurately characterized. The key purpose of this study was to ascertain the genetic diversity of IC in Rwanda using microsatellite markers. Blood samples of IC sampled from 5 agro-ecological zones were collected from which DNA was extracted, amplified by PCR and genotyped using 28 microsatellite markers. A total of 325 (313 indigenous and 12 exotic) chickens were genotyped and revealed a total number of 305 alleles varying between 2 and 22 with a mean of 10.89 per locus. One hundred eighty-six (186) distinct alleles and 60 private alleles were also observed. The frequency of private alleles was highest in samples from the Eastern region, whereas those from the North West had the lowest. The influx of genes was lower in the Eastern agro-ecological zone than the North West. The mean observed heterozygosity was 0.6155, whereas the average expected heterozygosity was 0.688. The overall inbreeding coefficient among the population was 0.040. Divergence from the Hardy-Weinberg equilibrium was significant (p<0.05) in 90% of loci in all the populations. The analysis of molecular variance revealed that about 92% of the total variation originated from variation within populations. Additionally, the study demonstrated that IC in Rwanda could be clustered into four gene groups. In conclusion, there was considerable genetic diversity in IC in Rwanda, which represents a crucial genetic resource that can be conserved or optimized through genetic improvement.