Titles |
English :
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Response to selection for milk yield traits in Egyptian buffalo
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Arabic :
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استجابة الانتخاب لصفات انتاج اللبن في الجاموس المصرى
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Abstract |
The aim for the present study was to estimate the genetic response to improve milk yield traits (milk, fat and protein) in Egyptian buffalo. Seven selection indices were constructed from data of 699 lactations of 478 buffalo daughter of 82 sires and 383 dams. The first index (I1) which included all milk yield traits was assumed to be the base of comparison while the rest indices are defined as reduced ones. Genetic parameters were estimated by a multiple-trait repeatability animal model using restricted maximum likelihood (REML) procedure. The model included herd year season of calving and age nested within lactation for the first three lactations as fixed effects and additive genetic and permanent environment as random effects. Results indicated that selection to improve milk yield traits might be achieved through multiple-trait selection. Therefore, a selection index including MY (Il, I2, I3 or I5) was recommended as the best criterion from both the economic and the practical points of view to improve milk yield traits of Egyptian buffaloes. Using I5 which includes only milk yield, as a criterion of selection results in an increase of the expected genetic response for MY, FY and PY. For local breeders, I5 could be considered as the best criterion from the practical point of view and easy to apply.
Keywords: Genetic parameters, multiple-trait repeatability animal model, multiple-trait selection
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Publication year |
2010
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Pages |
85-92
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Availability location |
معهد بحوث الانتاج الحيوانى- شارع نادى الصيد- الدقى - الجيزة
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Availability number |
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Organization Name |
Animal Production Research Institute (APRI)
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serial title |
Egyptian Journal of Animal Production
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ISSN |
0302-4520
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Author(s) from ARC |
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Agris Categories |
Animal husbandry
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AGROVOC TERMS |
Genetic parameters.
Milk yield.
Selection.
Water buffaloes.
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Proposed Agrovoc |
multiple-trait;repeatability animal model;multiple-trait selection;
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Publication Type |
Journal
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