Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium
Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (co)variance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three sin...
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Presses Agronomiques de Gembloux
1997-01-01
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Online Access: | http://www.pressesagro.be/base/text/v1n1/26.pdf |
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doaj-0973346acb664ba6b0ea2803baf4f3ee2020-11-24T21:40:28ZengPresses Agronomiques de GemblouxBiotechnologie, Agronomie, Société et Environnement1370-62331780-45071997-01-01112633Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in BelgiumPierre CoenraetsNicolas GenglerComparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (co)variance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires) estimated with the single-trait and multiple-trait models were over .98 (.99) in fat yield and over .99 (.99) in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1%) in milk yield, 6% (3%) in fat yield, and .4% (.2%) in protein yield for cows (for sires). Relative genetic gains were 3% (1%), 6% (2%) and .5% (.2%) respectively in milk, fat and protein yields for cows (for sires). The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.http://www.pressesagro.be/base/text/v1n1/26.pdfDairy cattlemilk production traitsgenetic evaluationmultiple-traitcomputation time |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pierre Coenraets Nicolas Gengler |
spellingShingle |
Pierre Coenraets Nicolas Gengler Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium Biotechnologie, Agronomie, Société et Environnement Dairy cattle milk production traits genetic evaluation multiple-trait computation time |
author_facet |
Pierre Coenraets Nicolas Gengler |
author_sort |
Pierre Coenraets |
title |
Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium |
title_short |
Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium |
title_full |
Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium |
title_fullStr |
Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium |
title_full_unstemmed |
Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium |
title_sort |
use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in belgium |
publisher |
Presses Agronomiques de Gembloux |
series |
Biotechnologie, Agronomie, Société et Environnement |
issn |
1370-6233 1780-4507 |
publishDate |
1997-01-01 |
description |
Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (co)variance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires) estimated with the single-trait and multiple-trait models were over .98 (.99) in fat yield and over .99 (.99) in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1%) in milk yield, 6% (3%) in fat yield, and .4% (.2%) in protein yield for cows (for sires). Relative genetic gains were 3% (1%), 6% (2%) and .5% (.2%) respectively in milk, fat and protein yields for cows (for sires). The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods. |
topic |
Dairy cattle milk production traits genetic evaluation multiple-trait computation time |
url |
http://www.pressesagro.be/base/text/v1n1/26.pdf |
work_keys_str_mv |
AT pierrecoenraets useofmultipletraitanimalmodelsforgeneticevaluationofmilkfatandproteinlactationyieldsofdairycattleinbelgium AT nicolasgengler useofmultipletraitanimalmodelsforgeneticevaluationofmilkfatandproteinlactationyieldsofdairycattleinbelgium |
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