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

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.

2012 ◽  
Vol 57 (No. 3) ◽  
pp. 108-114 ◽  
Author(s):  
V. Zink ◽  
J. Lassen ◽  
M. Štípková

The aim of this study was to estimate genetic parameters for female fertility and production traits in first-parity Czech Holstein cows and to quantify the effect of using this information on the accuracy of a selection index in seven different scenarios. In order to estimate genetic (co)variance components, the DMU software running an AI-REML algorithm was used. The analyses were made using a series of bivariate animal models. The pedigree included 164 125 animals and it was set up using a pruned animal model design. The present study included the following female fertility traits for the first lactations: calving to the first insemination (CF), days open (DO), calving from the first to the last insemination (FL), and milk production traits: milk production (MLK), kg of fat (FAT), and kg of protein (PROT). The heritability for all the investigated fertility traits was low and close to 0. Moderate heritabilities for production traits ranging from 0.20 (MLK) to 0.23 (PROT) were estimated. The strongest unfavourable correlation was found between PROT and DO (0.49). Other estimated correlations between fertility traits and production traits were moderate, ranging from 0.26 to 0.41. The results of this study evidence that cows with the poorest genetic potential for reproductive performance are those having high genetic potential for milk production and milk components. The results also show that the number of days from calving to new pregnancy depends on the production level. Seven investigated scenarios using selection index theory show a clear trend for increasing accuracy when more fertility traits were added as well as when higher numbers of daughters with information on reproduction traits per sire were available.  


2017 ◽  
Vol 100 (7) ◽  
pp. 5578-5591 ◽  
Author(s):  
P.B. Kandel ◽  
M.-L. Vanrobays ◽  
A. Vanlierde ◽  
F. Dehareng ◽  
E. Froidmont ◽  
...  

2014 ◽  
Vol 97 (4) ◽  
pp. 2462-2473 ◽  
Author(s):  
V.J. Castañeda-Bustos ◽  
H.H. Montaldo ◽  
G. Torres-Hernández ◽  
S. Pérez-Elizalde ◽  
M. Valencia-Posadas ◽  
...  

2020 ◽  
Vol 103 (3) ◽  
pp. 2460-2476
Author(s):  
E.K. Cheruiyot ◽  
T.T.T. Nguyen ◽  
M. Haile-Mariam ◽  
B.G. Cocks ◽  
M. Abdelsayed ◽  
...  

2007 ◽  
Vol 2007 ◽  
pp. 69-69
Author(s):  
E.D. Ilatsia ◽  
T. K. Muasya ◽  
W. B. Muhuyi ◽  
A. K. Kahi

The primary emphasis of the long-term Sahiwal cattle breeding programme is to increase milk yield by selecting cows based on their performance in first three lactations. It is therefore important to have knowledge on the extend of additive genetic variance and genetic parameters for these traits. Genetic and phenotypic parameter estimates normally apply directly to the specific population and environment from which the data were collected. In the Sahiwal cattle in Kenya, very little is known about the genetic variation of milk production traits and their genetic relationships. Furthermore, genetic and phenotypic parameter estimates for the Sahiwal cattle based on multivariate animal model are scarce. This paper presents estimates of variance components and genetic parameters for milk production traits using trivariate animal model.


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