Genetic evaluation of breeding program for body weight of indigenous chicken in Kenya
Joel Onyango Khobondo
Abstract
Open-access reader
Joel Onyango Khobondo
Abstract
Open-access reader
The demand for poultry meat, particularly from indigenous chicken, is ever increasing. This need efficient production potential from the chicken. This paper simulated different scenarios of breeding program for indigenous chicken and compared the selection response with realized genetic gain after one generation of selection. A one stage discrete generation deterministic simulation approach using SelAction program was used. Two genetic parameters were employed. The phenotypic variances and heritability used were 25,000g and 0.25, 3040 and 0.51, respectively. For each case, 300 hens and 50 cocks were selected to produce the next generation. Each cock was mated to 6 hens and each hen produced 6 offspring. The best 50% and 20% of females and males, respectively, were selected for mating. The expected selection response was simulated as follows; a) own performance b) own performance, full sibs and half sibs and c) own performance with full sibs, half sibs and BLUP information sources. A sire model of BLUP was used for realized selection response. The predicted genetic gain for all simulated programs were much lower than realized response. This realized genetic gain could only be achieved by higher selection intensity on cocks, however this would increase the inbreeding rate above recommended level. The breeding program has shown potential for improvement and success in body weight at 12 weeks of age.
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The demand for poultry meat, particularly from indigenous chicken, is ever increasing. This need efficient production potential from the chicken. This paper simulated different scenarios of breeding program for indigenous chicken and compared the selection response with realized genetic gain after one generation of selection. A one stage discrete generation deterministic simulation approach using SelAction program was used. Two genetic parameters were employed. The phenotypic variances and heritability used were 25,000g and 0.25, 3040 and 0.51, respectively. For each case, 300 hens and 50 cocks were selected to produce the next generation. Each cock was mated to 6 hens and each hen produced 6 offspring. The best 50% and 20% of females and males, respectively, were selected for mating. The expected selection response was simulated as follows; a) own performance b) own performance, full sibs and half sibs and c) own performance with full sibs, half sibs and BLUP information sources. A sire model of BLUP was used for realized selection response. The predicted genetic gain for all simulated programs were much lower than realized response. This realized genetic gain could only be achieved by higher selection intensity on cocks, however this would increase the inbreeding rate above recommended level. The breeding program has shown potential for improvement and success in body weight at 12 weeks of age.
Key concepts: Genetic gain, Heritability, Best linear unbiased prediction, Sire, Inbreeding, Selection (genetic algorithm), Breeding program, Biology