Literature DB >> 18024769

Genetic modification of the lactation curve by bending the eigenvectors of the additive genetic random regression coefficient matrix.

K Togashi1, C Y Lin.   

Abstract

The eigenvectors of the additive genetic random regression covariance (K) matrix contribute differentially to different parts of the lactation curve in response to genetic selection. It is, therefore, important to examine the genetic response patterns from the individual eigenvectors of the matrix K for the modification of the shape of the lactation curve. This study demonstrated a general methodology for imposing differential restrictions on different eigenvectors according to their effects on the shape of the lactation curve. A numerical example is given to illustrate the derivation and implementation of this procedure. Theoretically and experimentally, manipulating individual eigenvectors based on their individual effects on the shape of the lactation curve is more important than manipulating the joint effect of all the eigenvectors of K on the lactation curve. This described procedure provides a useful tool for simultaneous improvement of milk production and lactation persistency by modifying the shape of the lactation curve.

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Year:  2007        PMID: 18024769     DOI: 10.3168/jds.2007-0363

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  1 in total

1.  Random regression models to account for the effect of genotype by environment interaction due to heat stress on the milk yield of Holstein cows under tropical conditions.

Authors:  Mário L Santana; Annaiza Braga Bignardi; Rodrigo Junqueira Pereira; Alberto Menéndez-Buxadera; Lenira El Faro
Journal:  J Appl Genet       Date:  2015-07-09       Impact factor: 3.240

  1 in total

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