Multi-trait and multi-source selection indices for milk production and reproductive traits in a herd of Holstein cattle in Egypt

Eslam Faid-Allah

doi:10.14334/jitv.v20i3.1182

Abstract

The main aim of this study was explore possibility to improve milk production and reproductive traits of Holstein cattle via selection index method which include general, reduced, sub and Multi-source of information indices (Own-Performance, Full-Sibs and Half-Sibs). D ata was obtained from a commercial farm (Safi Masr for Developing the Animal Resources), located in the Nile Delta, Dakahlia, Egypt. Data included 4791 records of 1797 cows, 794 dams and 67 sires that represented the period from 2002 to 2012. Estimates of genetic and phenotypic parameters for studied traits were computed and used to construct 18 selection indices to improve milk production and reproductive traits. F ull index incorporating milk yield at 305d (305-dMY), lactation period (LP), days open (DO) and age at first calving (AFC) had the highest correlation with aggregate breeding value (R ih = 0.518; RE=100%). The correlation fell to 0.455 when 305-dMY was omitted from the index. The general index has the maximum expected genetic gain in 305-dMY (132.6 kg) per generation were accompanied by decrease of LP (-4.679 day), DO (-3.449 day) and AFC (-1.41 month) when all four traits were included in the index (I 1 ). The expected genetic gain for 305-dMY decreased to 26.84 kg/generation when 305-dMY was excluded in index 5 (I 5 ). In addition, Using multi-source of information will enhance correlation with aggregate breeding value (R ih = 0.740; RE=142.91%) and raised the expected genetic gain per generation for 305-dMY (209 kg) and decreasing the expected genetic gain for LP (-6.37 day), DO (-4.244 day) and AFC (1.843 month) when all four traits were included in the index (I 16 ). It could be suggested using the higher indexes of Rih (I 1 (RE=100) ) to improve milk production and reproductive traits in Holstein cattle under own-performance strategy and using (I 16 (RE= 142.91 ) ) under multi-source strategy to get high accuracy and higher expected genetic changes per generation compare to general index.

Highlights

Breeding programs are basically designed to identify superior genotypes for different traits of economic interest, based on performance information of animals and their relatives, in order to disseminate their genes in the population
Using multi-source of information will enhance correlation with aggregate breeding value (Rih= 0.740; RE=142.91%) and raised the expected genetic gain per generation for 305-day milk yield (305-dMY) (209 kg) and decreasing the expected genetic gain for lactation period (LP) (-6.37 day), days open (DO) (-4.244 day) and at first calving (AFC) (1.843 month) when all four traits were included in the index (I16). It could be suggested using the higher indexes of Rih (I1 (RE=100)) to improve milk production and reproductive traits in Holstein cattle under own-performance strategy and using (I16 (RE=142.91)) under multi-source strategy to get high accuracy and higher expected genetic changes per generation compare to general index
Increasing use of selection indices and greater scope in number of traits has been observed in dairy cattle populations in the past two decades included main components related to production, durability, health and reproduction in each selection index (Miglior et al 2005)

Summary

Introduction

Breeding programs are basically designed to identify superior genotypes for different traits of economic interest, based on performance information of animals and their relatives, in order to disseminate their genes in the population. Increasing use of selection indices and greater scope in number of traits has been observed in dairy cattle populations in the past two decades included main components related to production, durability, health and reproduction in each selection index (Miglior et al 2005). Age at first calving and calving interval are important because they determine the days a cow is in milk and the number of calves in the productive lifetime for replacement or sale (Wahinya et al 2015). As information on other traits related to health, fertility and longevity started being recorded and genetic evaluations for these traits were performed, they were gradually included as breeding goals of dairy cattle (Norman et al 2010)

Objectives

Methods

Results