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Prediction of genetic gains for breeding objective traits and designing selection schemes for Washera and Gumuz indigenous sheep
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In Ethiopia,there are 32.85 millions of sheep,more than 99 % of which are indigenous.However,the productivity of local sheep under traditional production system is low with high mortality of sheep.There are two ways of improving performance of sheep and goats,namely improving the enviroment of animals and/or improving there genetic potential.The aim of this study was to predict genetic gains of breedingobjective traits and select the best sheep selection scheme for Gumuz andWashera sheep. Body size(six month weight and yearling weight) and litter size were breeding objective traits identified by own flock animal ranking experiment and personal interview. Deterministic approach of ZPLAN computor program is used for modeling input parametres of Gumuz and Washera sheep and simulating breeding plans using gene flow method and selection index procedures. One-tier cooperative sheep breeding scheme were proposed whereby ram exchange between and within villages is the main means of genetic dissimination. Genetic gains predicted for six month weight of Gumuz and Washera sheep were 0.43 and 0.55 kg,respectively. Genetic gains predicted for yearling weight of Gumuz and Washera sheep were 0.55 and 0.60 kg,respectively. Genetic gains predicted for litter size of Gumuz and Washera sheep were 0.08 and 0.09 lambs,respectively. The lower rate of inbreeding, the higher monetary genetic gain for aggregate genotype,higher return to investmnet and higher profit/ewe/year were quality measures of breeding program considered to prefer scheme 4 for both Gumuz and Washera sheep.Hence,for both Gumuz and Washera sheep populations a sheep selection scheme designed with 15 % selection proportion and one year ram use for breeding was recommended. Special emphasis need to be given to yearling weight with higher predicted genetic response and higher percentage return to investment.
Animal Husbandry, Agriculture Faculty, Gorontalo State University
Title: Prediction of genetic gains for breeding objective traits and designing selection schemes for Washera and Gumuz indigenous sheep
Description:
In Ethiopia,there are 32.
85 millions of sheep,more than 99 % of which are indigenous.
However,the productivity of local sheep under traditional production system is low with high mortality of sheep.
There are two ways of improving performance of sheep and goats,namely improving the enviroment of animals and/or improving there genetic potential.
The aim of this study was to predict genetic gains of breedingobjective traits and select the best sheep selection scheme for Gumuz andWashera sheep.
Body size(six month weight and yearling weight) and litter size were breeding objective traits identified by own flock animal ranking experiment and personal interview.
Deterministic approach of ZPLAN computor program is used for modeling input parametres of Gumuz and Washera sheep and simulating breeding plans using gene flow method and selection index procedures.
One-tier cooperative sheep breeding scheme were proposed whereby ram exchange between and within villages is the main means of genetic dissimination.
Genetic gains predicted for six month weight of Gumuz and Washera sheep were 0.
43 and 0.
55 kg,respectively.
Genetic gains predicted for yearling weight of Gumuz and Washera sheep were 0.
55 and 0.
60 kg,respectively.
Genetic gains predicted for litter size of Gumuz and Washera sheep were 0.
08 and 0.
09 lambs,respectively.
The lower rate of inbreeding, the higher monetary genetic gain for aggregate genotype,higher return to investmnet and higher profit/ewe/year were quality measures of breeding program considered to prefer scheme 4 for both Gumuz and Washera sheep.
Hence,for both Gumuz and Washera sheep populations a sheep selection scheme designed with 15 % selection proportion and one year ram use for breeding was recommended.
Special emphasis need to be given to yearling weight with higher predicted genetic response and higher percentage return to investment.
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