scholarly journals Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

2015 ◽  
Vol 29 (5) ◽  
pp. 607-614 ◽  
Author(s):  
C. I. Cho ◽  
M. Alam ◽  
T. J. Choi ◽  
Y. H. Choy ◽  
J. G. Choi ◽  
...  
Keyword(s):  
Milk Production ◽  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Holstein Cattle ◽  
Production Traits ◽  
Milk Production Traits

Use of productive data to predict length of productive life in Iranian Holstein cattle

2005 ◽  
Vol 2005 ◽  
pp. 126-126
Author(s):  
A. Abdolmohammadi ◽  
M. Moradi Shahrebabak ◽  
S. R. M. Ashtiani
Keyword(s):  
Milk Production ◽  
Genetic Parameters ◽  
Selection Index ◽  
Direct Selection ◽  
Holstein Cattle ◽  
Production Traits ◽  
Milk Production Traits ◽  
Direct Evaluation ◽  
Productive Life ◽  
Selection Of

Improvement of longevity by direct selection of sires based on theirs daughters’ longevity measures is impractical because of a low heritability and generation intervals prolonged by waiting until all cows complete their productive life. As an alternative to direct evaluation of sires for longevity is indirect prediction from genetically correlated production traits measures in the first lactation. The objectives this study were 1) to estimate genetic parameters of longevity and production traits 2) to examine relationships between longevity and first lactation milk production traits and 3) to determine selection index for sires’ longevity based on production traits.

scholarly journals Comparison of different polynomial functions in Random Regression Model for milk production traits of Iranian Holstein dairy cattle

2014 ◽  
Vol 14 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Ali Mohammadi ◽  
Sadegh Alijani ◽  
Hossein Daghighkia
Keyword(s):  
Dairy Cattle ◽  
Regression Model ◽  
Milk Production ◽  
Genetic Parameters ◽  
Random Regression ◽  
Polynomial Functions ◽  
Early Lactation ◽  
Production Traits ◽  
Milk Production Traits ◽  
Random Regression Model

Abstract The aim of this research was to compare different polynomial functions including Legendre polynomials (LP), Wilmink (WRR) and Ali-Schaeffer (ARR) functions, in random regression model (RRM) for estimation of genetic parameters for milk production traits of Iranian Holstein dairy cattle. For this purpose the performance records obtained from test-day (TD) regarding milk yield, fat and protein contents of the cows calving for the first time were used. The numbers of records for the above mentioned traits were 701212, 657004, and 560775, respectively. These records were collected from the years 2006 to 2010 by the National Breeding Center of Iran. The genetic parameters were estimated using Restricted Maximum Likelihood (REML) method by applying RRM. Residual variances were considered homogeneous over the lactation period. To compare the model, different criteria (-2Logl, AIC, BIC and RV) were used for considered traits. Based on the results obtained, for all traits, RRM with LP function (2,5) were chosen as the best model. Considering residual variance (RV), LP (2,2) was proved to be a model which has the lowest performance, while using -2Logl, AIC, BIC criteria, RRM with ARR function was the worst model. According to the results, it is recommended to use LP with low orders for the additive genetic effects and with more orders for the permanent environment effects in the RRM for Iranian Holstein cattle. Permanent environment variance was higher in early lactation than during lactation and additive genetic variance in the early lactation was lower than at the end of lactation. Heritability range of milk yield, fat and protein contents was estimated to be from 0.08 to 0.23, 0.05 to 0.20 and 0.08 to 0.14, respectively. Phenotypic variance of the considered traits during lactation was not constant and it was higher at the beginning and the end of lactation. The additive genetic correlation between adjacent test days was higher than between distant test days.

scholarly journals Comparison of random regression models, traditional animal model and with the inclusion of molecular markers in the estimation of genetic parameters in Colombian Holstein cattle

2021 ◽  
Vol 42 (3) ◽  
pp. 1303-1322
Author(s):  
Daniel Cardona-Cifuentes ◽  
◽  
Albeiro López-Herrera ◽  
Luis Gabriel González-Herrera ◽  
Mario Fernando Cerón-Muñoz ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Somatic Cell ◽  
Milk Production ◽  
Regression Models ◽  
Genetic Parameters ◽  
Evaluation Model ◽  
Random Regression ◽  
Holstein Cattle ◽  
Protein Percentage ◽  
Estimation Of Genetic Parameters

The use of molecular markers to identify desirable genes in animal production is known as marker-assisted selection. The traditional genetic evaluation model uses the BLUP methodology; when genetic markers are included in the evaluation model, the methodology is known as M-BLUP. In contrast, random regression models (RRM), unlike the models based on production at 305 days, consider factors that change for each animal from one test to another. The objective of this study was to compare variance components, genetic parameters and breeding values for milk production, protein percentage and somatic cell score in Colombian Holstein cattle using BLUP, M-BLUP and RRM. For the estimation of genetic parameters and values, 2003 lactations corresponding to 1417 cows in 55 herds were used, and effects of the order of delivery, herd, and contemporary group were included. The three traits presented greater heritability under the MBLUP model: 0.44 for protein percentage, 0.27 for milk production and 0.28 for somatic cell score. This was because the genetic variance was greater when M-BLUP was used, which allowed a greater accuracy of the breeding value estimation in the three traits. Therefore, the model that includes information on molecular markers is more suitable for genetic evaluation in Colombian Holstein cattle.

scholarly journals Genetic parameters of mid-infrared methane predictions and their relationships with milk production traits in Holstein cattle

2017 ◽  
Vol 100 (7) ◽  
pp. 5578-5591 ◽  
Author(s):  
P.B. Kandel ◽  
M.-L. Vanrobays ◽  
A. Vanlierde ◽  
F. Dehareng ◽  
E. Froidmont ◽  
...  
Keyword(s):  
Milk Production ◽  
Genetic Parameters ◽  
Holstein Cattle ◽  
Production Traits ◽  
Milk Production Traits ◽  
Mid Infrared

scholarly journals Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

2013 ◽  
Vol 12 (1) ◽  
pp. 143-153 ◽  
Author(s):  
D.J.A. Santos ◽  
M.G.C.D. Peixoto ◽  
R.R. Aspilcueta Borquis ◽  
R.S. Verneque ◽  
J.C.C. Panetto ◽  
...  
Keyword(s):  
Milk Production ◽  
Regression Models ◽  
Genetic Parameters ◽  
Bos Indicus ◽  
Random Regression

scholarly journals Genotype-by-environment (temperature-humidity) interaction of milk production traits in Australian Holstein cattle

2020 ◽  
Vol 103 (3) ◽  
pp. 2460-2476
Author(s):  
E.K. Cheruiyot ◽  
T.T.T. Nguyen ◽  
M. Haile-Mariam ◽  
B.G. Cocks ◽  
M. Abdelsayed ◽  
...  
Keyword(s):  
Milk Production ◽  
Holstein Cattle ◽  
Production Traits ◽  
Milk Production Traits ◽  
Genotype By Environment ◽  
Environment Temperature
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