0393 Analysis of genetic residual feed intake in Danish Holstein cows by covariance functions using random regression models

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 190-191
Author(s):  
C. Pfeiffer ◽  
B. Li ◽  
P. Lovendahl ◽  
J. Lassen
Keyword(s):  
Feed Intake ◽  
Regression Models ◽  
Residual Feed Intake ◽  
Random Regression ◽  
Holstein Cows ◽  
Covariance Functions

scholarly journals Simultaneous Bayesian estimation of genetic parameters for curves of weight, feed intake and residual feed intake in beef cattle

2021 ◽  
Author(s):  
Hadi Esfandyari ◽  
Just Jensen
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Parameters ◽  
Residual Feed Intake ◽  
Test Period ◽  
Random Regression ◽  
Farm Animals ◽  
Joint Analysis ◽  
Breeding Values ◽  
Covariance Functions

Abstract Rate of gain and feed efficiency are important traits in most breeding programs for growing farm animals. Rate of gain (GAIN) is usually expressed over a certain age period and feed efficiency is often expressed as residual feed intake (RFI), defined as observed feed intake (FI) minus expected feed intake based on live weight (WGT) and GAIN. However, the basic traits recorded are always WGT and FI and other traits are derived from these basic records. The aim of this study was to develop a procedure for simultaneous analysis of the basic records and then derive linear traits related to feed efficiency without retorting to any approximations. A bivariate longitudinal random regression model was employed on 13,791 individual longitudinal records of WGT and FI from 2,827 bulls of six different beef breeds tested for own performance in the period from 7 to 13 months of age. Genetic and permanent environmental covariance functions for curves of WGT and FI were estimated using Gibbs sampling. Genetic and permanent covariance functions for curves of GAIN were estimated from the first derivative of the function for WGT and finally the covariance functions were extended to curves for RFI, based on the conditional distribution of FI given WGT and GAIN. Furthermore, the covariance functions were extended to include GAIN and RFI defined over different periods of the performance test. These periods included the whole test period as normally used when predicting breeding values for GAIN and RFI for beef bulls. Based on the presented method, breeding values and genetic parameters for derived traits such as GAIN and RFI defined longitudinally or integrated over (parts of) of the test period can be obtained from a joint analysis of the basic records. The resulting covariance functions for WGT, FI, GAIN and RFI are usually singular but the method presented here do not suffer from the estimation problems associated with defining these traits individually before the genetic analysis. All results are thus estimated simultaneously, and the set of parameters are consistent.

scholarly journals Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models

animal ◽  
2009 ◽  
Vol 3 (2) ◽  
pp. 181-188 ◽  
Author(s):  
H. Hüttmann ◽  
E. Stamer ◽  
W. Junge ◽  
G. Thaller ◽  
E. Kalm
Keyword(s):  
Energy Balance ◽  
Feed Intake ◽  
Regression Models ◽  
Random Regression ◽  
Holstein Cows

Is it useful to define residual feed intake as a trait in animal breeding programs?

2004 ◽  
Vol 44 (5) ◽  
pp. 405 ◽  
Author(s):  
J. H. J. van der Werf
Keyword(s):  
Feed Intake ◽  
Production Efficiency ◽  
Residual Feed Intake ◽  
Selection Response ◽  
Random Regression ◽  
Biological Efficiency ◽  
Multiple Trait ◽  
Selection Indices ◽  
Feed Utilisation ◽  
Definition Of

Residual feed intake is a linear function of feed intake, production and maintenance of liveweight, and as such is an attractive characteristic to use to represent production efficiency. The phenotypic and genetic parameters of residual feed intake can be written as a function of its constituent traits. Moreover, selection indices containing the constituent traits are equivalent with an index that includes residual feed intake. Therefore, definition of the term residual feed intake may be useful to interpret variation in production efficiency, but it does not help in obtaining a better selection response than selection on constituent traits alone. In fact, multiple trait genetic evaluation of constituent traits rather than residual feed intake is likely to be more accurate as this more appropriately accommodates different models for the constituent traits and missing data. For residual feed intake to reflect true biological efficiency in growing animals, it is important that feed intake and liveweight are accurately measured. Accounting for growth and body composition would significantly help in revealing between-animal variation in feed utilisation. Random regression models can be helpful in indicating variation in feed efficiency over the growth trajectory.

scholarly journals Covariance functions and random regression models for cow weight in beef cattle1

2004 ◽  
Vol 82 (1) ◽  
pp. 54-67 ◽  
Author(s):  
J. A. Arango ◽  
L. V. Cundiff ◽  
L. D. Van Vleck
Keyword(s):  
Regression Models ◽  
Random Regression ◽  
Covariance Functions

scholarly journals Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

animal ◽  
2007 ◽  
Vol 1 (3) ◽  
pp. 325-334 ◽  
Author(s):  
C.M.R. de Melo ◽  
I.U. Packer ◽  
C.N. Costa ◽  
P.F. Machado
Keyword(s):  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Holstein Cows

scholarly journals Prediction of residual feed intake for first-lactation dairy cows using orthogonal polynomial random regression

2013 ◽  
Vol 96 (12) ◽  
pp. 7991-8001 ◽  
Author(s):  
G. Manafiazar ◽  
T. McFadden ◽  
L. Goonewardene ◽  
E. Okine ◽  
J. Basarab ◽  
...  
Keyword(s):  
Orthogonal Polynomial ◽  
Dairy Cows ◽  
Feed Intake ◽  
Residual Feed Intake ◽  
Random Regression

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

2009 ◽  
Vol 123 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Annaiza Braga Bignardi ◽  
Lenira El Faro ◽  
Vera Lucia Cardoso ◽  
Paulo Fernando Machado ◽  
Lucia Galvão de Albuquerque
Keyword(s):  
Milk Yield ◽  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Holstein Cows ◽  
Southeastern Brazil

Estimates of covariance functions for growth of Kordi sheep in Iran using random regression models

2018 ◽  
Vol 162 ◽  
pp. 69-76 ◽  
Author(s):  
Davoud Ali Saghi ◽  
Ali Reza Shahdadi ◽  
Fatemeh Kazemi Borzelabad ◽  
Kourosh Mohammadi
Keyword(s):  
Regression Models ◽  
Random Regression ◽  
Covariance Functions
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