Genetic evaluation of daily gains of dual-purpose bulls using a random regression model

Krejcová, H; Přibyl, J.; Přibylová, J.; Štípková, M.; Mielenz, N.

doi:10.17221/360-cjas

Cited by 11 publications

(14 citation statements)

References 17 publications

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“…All the functions had 5 parameters. A detailed description of the methodology is in Přibyl et al (2007Přibyl et al ( , 2008 and Krejčová et al (2008).…”

Section: Methodsmentioning

confidence: 99%

“…For traits from RR analysis (G1m, G2m, G3m, W1m and W1mD) the variance components for traits were derived from the covariance matrix of random regression coefficients Krejčová et al, 2008). Estimates of genetic (G) and permanent environmental (PE) components for each day during the test period were obtained by…”

Section: Methodsmentioning

confidence: 99%

“…A high degree of similarity of results between both methodologies was found. Krejčová et al (2008) reported the culmination of daily gain at 250 days of age for performancetested young bulls of Czech Fleckvieh cattle kept under standardized conditions. Heritability of daily gains was very low due to the high random fluctuations of daily gains and random errors of production records in short intervals.…”

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confidence: 99%

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Comparison of different traits to evaluate the growth of bulls

Přibyl¹,

Přibylová²,

Krejcová³

et al. 2008

CZECH J ANIM SCI

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ABSTRACT:The live weights of 8 243 performance-tested bulls from 100 to 400 days of age were analysed using random regression (RR) and single-trait animal models. Evaluations were done for live weight at 400 days of age and gains from 100 to 400 days of age at various monthly intervals. Estimates of variance components differed depending on the trait definition and model of analysis. Systematic environmental effects explained a higher proportion of variability in the RR for gains than for other definitions of growth. The expected average reliability of estimated breeding values was similar for all methods from 0.42 to 46, but the rankings of animals differed. Determinations (r 2 ) of breeding values between methods ranged from 0.64 to 0.94. Correlations of the breeding values of progeny at performance-test stations with parents were highest for the evaluation of gains in consecutive intervals evaluated by RR. Correlations of the breeding values of sires from their growth at performance-test stations with the breeding values of groups of progeny at progeny-test stations were from 0.26 to 0.38. Correlations were the highest for RR evaluations of gain using consecutive short intervals. Evaluation of the growth of animals according to daily gains in short consecutive intervals was preferred because more animals and more observations per animal were included in the evaluations, and the growth curve was separated into genetic and non-genetic parts. Simple evaluation of growth according to the final weight or daily gain in a long interval is not entirely correct, since environmental compensatory growth can occur.

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“…All the functions had 5 parameters. A detailed description of the methodology is in Přibyl et al (2007Přibyl et al ( , 2008 and Krejčová et al (2008).…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Comparison of different traits to evaluate the growth of bulls

Přibyl¹,

Přibylová²,

Krejcová³

et al. 2008

CZECH J ANIM SCI

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“…Several authors (Tong et al, 1986;de Rose et al, 1988) also estimated a mean negative environmental correlation (-0.41 to -0.09) between pre-weaning growth and growth in a station test. Using the testday model with random regression, Krejčová et al (2008) also estimated negative values of r pe in bulls from Czech Fleckvieh cattle at performance test stations and documented growth compensation in those bulls influenced by the environment. Schenkel et al (2004) reported that due to the influence of the aforementioned growth compensation, the problem of correct evaluation and subsequent selection of bulls for breeding may arise.…”

Section: Direct Permanent Environmentmentioning

confidence: 99%

Genetic evaluation of the growth of beef bulls at a performance test station

Vostrý¹,

Veselá²,

Krupa³

2014

J. Anim. Feed Sci.

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“…The advantages of the SSP are more pronounced for traits with lower heritabilities (Chen et al, 2011) and can be used in multiple trait (MT) analysis for the prediction of the GEBV of several traits . An SSP approach is based on typical methods using linear mixed models in large populations at a national level (Zavadilová et al, 2005(Zavadilová et al, , 2009Krejčová et al, 2008;Vostrý et al, 2008;Komprej et al, 2009), and it immediately follows all processed and programmed national-scale procedures for the genetic evaluation of farm animals (Plemdat, 2011).…”

mentioning

confidence: 99%

Single-step prediction of genomic breeding value in a small dairy cattle population with strong import of foreign genes

Přibyl¹,

Haman²,

Kott³

et al. 2012

CZECH J ANIM SCI

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The main goal of the inclusion of molecular genetic information (MG) in the evaluation of breeding animals is to evaluate young animals without performance records.The inclusion of MG was first carried out based on the relationship between several genetic markers with QTLs (Přibyl, 1995). This information was combined with the polygenic breeding value (EBV) determined by a BLUP Animal Model. A large number of genetic markers can be determined due to the development of laboratory techniques that influence the methods of EBV prediction. A large number of partial regressions are estimated for a given trait based on many SNP genetic markers. These partial regressions are summed into one total criterion used for the animal's selection for breeding. This criterion predicts the direct genetic value (DGV) and in combination with the Single-step prediction of genomic breeding value in a small dairy cattle population with strong import of foreign genes The older data set included 526 genotyped bulls, in which the daughters' milk performance was known for 210 individuals. All of the genotyped animals were included in the newer data set. Of the young genotyped bulls from the older set, 279 had more than 50 daughters with performance records in the newer set. Genomic relationship matrices (G) were constructed from the allele frequencies of the current genotyped population or by assuming a constant value of 0.5 for all loci. Using current allele frequencies, the correlation of G with the pedigree relationship (A) was 0.74, while it was 0.77 when the constant value was used. G was blended with A with weights of 80 or 99%. The average EBV of the genotyped bulls exceeded the mean EBV of the entire population by 3 SD. Although the number of reference bulls was small, genotyping resulted in an increase of approximately 0.05 in the correlation of the GEBV of young bulls with their results after progeny testing. Only small differences in correlations were found in dependency on the methods used for the determination of G and in dependency on the weight used in blending G with A. Both EBV and GEBV in the older set showed higher correlations with the GEBV of the newer set than the EBV of the newer set.

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Genetic evaluation of daily gains of dual-purpose bulls using a random regression model

Cited by 11 publications

References 17 publications

Comparison of different traits to evaluate the growth of bulls

Comparison of different traits to evaluate the growth of bulls

Genetic evaluation of the growth of beef bulls at a performance test station

Single-step prediction of genomic breeding value in a small dairy cattle population with strong import of foreign genes

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