Genetic parameters for milk production and persistency in the Iranian Holstein population by the multitrait random regression model

Khabat Kheirabadi,Sadegh Alijani

doi:10.7482/0003-9438-57-012

Abstract

Abstract. For genetic dissection of milk, fat, and protein production traits in the Iranian primiparous Holstein dairy cattle, records of these traits were analysed using a multitrait random regression test-day model. Data set included 763 505 test-day records from 88 204 cows calving since 1993. The (co)variance components were estimated by Bayesian method. The obtained results indicated that as in case of genetic correlations within traits, genetic correlations between traits decrease as days in milk (DIM) got further apart. The strength of the correlations decreased with increasing DIM, especially between milk and fat. Heritability estimates for 305-d milk, fat, and protein yields were 0.31, 0.29, and 0.29, respectively. Heritabilities of test-day milk, fat, and protein yields for selected DIM were higher in the end than at the beginning or the middle of lactation. Heritabilities for persistency ranged from 0.02 to 0.24 and were generally highest for protein yield (0.05 to 0.24) and lowest for fat yield (0.02 to 0.17), with milk yield having intermediate values (0.06 to 0.22). Genetic correlations between persistency measures and 305-d production were higher for protein and milk yield than for fat yield. The genetic correlation of the same persistency measures between milk and fat yields averaged 0.76, and between milk and protein yields averaged 0.82.

Highlights

Dairy cows produce a lot of milk, but a more important goal of those who milk cows is to make a profit
Persistency should not be achieved at the expense of total lactation milk, as persistency is highly affected by lactation milk (Togashi & Lin 2004)
Swalve & Gengler (1999) sorted the persistency measures into 4 categories: 1) measures derived from the parameters of the lactation curve 2) those based on rations between total, partial and daily yields 3) those based on variation of test-day (TD) yields and 4) those derived from the random regression test-day model (RRM)

Summary

Introduction

Dairy cows produce a lot of milk, but a more important goal of those who milk cows is to make a profit. Swalve & Gengler (1999) sorted the persistency measures into 4 categories: 1) measures derived from the parameters of the lactation curve 2) those based on rations between total, partial and daily yields 3) those based on variation of test-day (TD) yields and 4) those derived from the RRM. Jamrozik et al (1997) compared three measures of persistency derived from parameters of lactation curves using a TD model and found that genetic correlations with lactation milk yield were all >0.1. Jakobsen et al (2002) studied five different persistency measures using RRM and showed that the estimated genetic correlations with 305-d lactation yield ranged from 0.00 to 0.47 for milk, −0.30 to 0.10 for fat, and −0.20 to 0.53 for protein. The objectives of this research were as follows: a) to estimate the genetic parameters for milk production traits by a multitrait RRM; and b) to estimate the genetic and environmental parameters of different persistency measures and comparison of them

Objectives

Methods

Results