Genetic parameters of calving ease in dairy cattle using threshold and linear models

A combination of better management and genetic selection for good health and fertility would provide a more effective long term solution for economic loss due to diseases and poor fertility. This would also help to address public concerns about the use of medical treatment in milk production. A balance in the genetic improvement of health and fertility together with milk production could be achieved through their inclusion in national genetic selection indices, for which genetic parameters are needed. One of the main objectives of this study was to estimate genetic parameters for various disease and fertility traits in the UK dairy cattle population, using records from a national recording scheme run by Livestock Services UK Ltd. Genetic analysis of traits recorded as present or absent (binary traits; e.g. diseases) requires the use of non-linear threshold models, because linear models require normality assumptions (e.g., Gianola 1982). The other objective of this study was to estimate genetic parameters for binary disease and fertility traits based on threshold animal models and to compare results with those from linear animal models.

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Genetic parameters for calving difficulty using complex genetic models in five beef breeds in Australia

Animal Production Science ◽

10.1071/an14571 ◽

2016 ◽

Vol 56 (5) ◽

pp. 927 ◽

Cited By ~ 5

Author(s):

M. G. Jeyaruban ◽

D. J. Johnston ◽

B. Tier ◽

H.-U. Graser

Keyword(s):

Genetic Parameters ◽

Linear Models ◽

Random Effect ◽

Genetic Correlations ◽

Genetic Effect ◽

Genetic Effects ◽

Gestation Length ◽

Calving Ease ◽

Direct Genetic Effect ◽

Calving Difficulty

Data on Angus (ANG), Charolais (CHA), Hereford (HER), Limousin (LIM) and Simmental (SIM) cattle were used to estimate genetic parameters for calving difficulty (CD), birthweight (BWT) and gestation length (GL) using threshold-linear models and to examine the effect of inclusion of random effect of sire × herd interaction (SxH) in the models. For models without SxH, estimated heritabilities for direct genetic effect of CD were 0.24 (±0.02), 0.22 (±0.04), 0.31 (±0.02), 0.22 (±0.04) and 0.17 (±0.01) for ANG, CHA, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.13 to 0.20. Estimated heritabilities for direct genetic effect of BWT were 0.38 (±0.01), 0.37 (±0.03), 0.46 (±0.01), 0.35 (±0.02) and 0.36 (±0.01) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.08 to 0.11. Estimated heritabilities for direct genetic effect of GL were 0.59 (±0.02), 0.42 (±0.04), 0.50 (±0.03), 0.45 (±0.04) and 0.42 (±0.03) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.03 to 0.09. Genetic correlations between direct genetic effects of CD with BWT were highly positive and with GL were moderately positive for all five breeds. Estimated genetic correlations between direct genetic effects and maternal genetic effects (rdm) ranged across the five breeds from –0.40 (±0.05) to –0.16 (±0.02), –0.41 (±0.03) to –0.27 (±0.08) and –0.47 (±0.10) to –0.06 (±0.12) for BWT, GL and CD, respectively. Fitting SxH interaction as additional random effect significantly increased the log-likelihood for analyses of BWT, GL and CD of all breeds, except for GL of CHA. The estimated heritabilities were less than or equal to the estimates obtained with models omitting SxH. The rdm increased (i.e. became less negative) for BWT, GL and CD of all five breeds. However, the increase for GL was not substantially high in comparison to the increase observed for BWT and CD. Genetic parameters obtained for BWT, GL and CD, by fitting SxH as an additional random effect, are more appropriate to use in the genetic evaluation of calving ease in BREEDPLAN.

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A Comparison of Linear Models for Estimating Co-Variance Components and Genetic Parameters in Holstein Dairy Cattle

Journal of Animal Poultry & Fish Production ◽

10.21608/japfp.2015.7424 ◽

2015 ◽

Vol 4 (1) ◽

pp. 7-15 ◽

Cited By ~ 1

Author(s):

Shalaby A. ◽

S. Moawed ◽

K. El-Bayomi

Keyword(s):

Dairy Cattle ◽

Variance Components ◽

Genetic Parameters ◽

Linear Models

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Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models

Journal of Animal Breeding and Genetics ◽

10.1111/jbg.12105 ◽

2014 ◽

Vol 131 (6) ◽

pp. 513-521 ◽

Cited By ~ 10

Author(s):

S. Vanderick ◽

T. Troch ◽

A. Gillon ◽

G. Glorieux ◽

N. Gengler

Keyword(s):

Dairy Cattle ◽

Genetic Parameters ◽

Threshold Models ◽

Calving Ease

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Genetic evaluation of productive life in Iranian Holstein using survival analysis

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200010425 ◽

2005 ◽

Vol 2005 ◽

pp. 131-131 ◽

Cited By ~ 2

Author(s):

M. Dadpasand Taromsari ◽

S. R. Miraei-Ashtiani ◽

M. Moradi Shahrebabak ◽

R. Vaez Torshizi

Keyword(s):

Survival Analysis ◽

Dairy Cattle ◽

Genetic Parameters ◽

Linear Models ◽

Failure Time ◽

Genetic Evaluation ◽

Time Analysis ◽

Productive Life ◽

Analysis Methodology ◽

Time Dependent Covariates

Improvement of herd life increases profitability due to lower replacement costs of heifers, higher proportion of mature cows that produce at their maximum potential and increased opportunity for voluntary culling. Functional productive life (PL) after adjustment for production is the ability of a cow to remain healthy and delay involuntary culling (Ducrocq et al 1988). Survival or failure time analysis has replaced linear model approaches for routine genetic evaluation of dairy cattle in several countries (Sewalem et. al. 2003). It allows proper treatment of censored data, inclusion of time-dependent covariates and skewed or non normal distribution of data. Approximate estimates of the heritability of longevity traits typically range from 0.05 to 0.10 and 0.15 to 0.20 using linear models and survival analysis, respectively (Vollema et al. 2000 and Caraviello et. al. 2004). The objective of this study was to apply survival analysis methodology for assessing the most important factor influencing PL, estimation of genetic parameters of productive life and genetic evaluation in Iranian Holstein dairy cattle.

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Estimation of genetic parameters using a random regression monthly test-day model in an Ethiopian dairy cattle population

Agriculture and Natural Resources ◽

10.1016/j.anres.2015.06.002 ◽

2016 ◽

Vol 50 (1) ◽

pp. 64-70 ◽

Cited By ~ 2

Author(s):

Gebregziabher Gebreyohannes ◽

Skorn Koonawootrittriron ◽

Mauricio A. Elzo ◽

Thanathip Suwanasopee

Keyword(s):

Dairy Cattle ◽

Genetic Parameters ◽

Random Regression ◽

Cattle Population ◽

Estimation Of Genetic Parameters

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Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

Archives Animal Breeding ◽

10.5194/aab-59-243-2016 ◽

2016 ◽

Vol 59 (2) ◽

pp. 243-248 ◽

Cited By ~ 3

Author(s):

Hafedh Ben Zaabza ◽

Abderrahmen Ben Gara ◽

Hedi Hammami ◽

Mohamed Amine Ferchichi ◽

Boulbaba Rekik

Keyword(s):

Dairy Cattle ◽

Bayesian Methods ◽

Milk Fat ◽

Variance Components ◽

Genetic Parameters ◽

Genetic Correlations ◽

Bayesian Procedure ◽

Milk Traits ◽

Residual Variances ◽

Estimation Of Variance

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

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