Genotype by environment interaction for fertility traits in New Zealand dairy cows

Abstract

The majority of New Zealand dairy farms operate a seasonal production system. This requires that a cow calve every 365 days, which means the cow must recover from calving and present for mating 12 weeks from the calving event. The seasonal system aligns calving and the subsequent increase in milk production with the increase of seasonal pasture production. This a key element to the economic success of NZ dairy systems. Negative correlations exist between fertility and milk production traits. Prior to 2001, when fertility was first included in the National Breeding Objective, there was a major focus on selection for production performance. During this time the fertility performance of the national dairy herd deteriorated. Since inclusion in 2001 the downward trend of fertility performance has been halted and small improvements made. Current six week in-calf rates are 66 percent and an industry target of 78 percent has been set, so there is considerable progress to be made. This thesis presents an investigation into the effect of genotype by environment interaction for fertility traits by completing parameter estimation of fertility traits with discrete environmental descriptors for divergent herd fertility (high and low fertility herd). A further investigation was completed that aimed to quantify the effect of sire estimated genetic merit of fertility on cow fertility phenotypes. Data were obtained from DairyNZ and contained records of approximately 22 million animals, with data fields for animal identification, birth year, farm location identifier, lactation number, transfer data, pedigree records and records related to mating and calving events. Cows born between 1997 and 2009 were retained to ensure animals used in the analysis were representative of a modern genotype and no animals had censored mating records. Heritabilities and genetic standard deviations were 1.2 – 3.6 times greater, across all fertility traits, for cows in low fertility herds compared to those in high fertility herds. This indicates that sires selected for greater fertility performance can have a greater impact in low fertility herds compared to high fertility herds. Genetic correlations were estimated but were inconsistent across multiple analyses and in all cases had large standard errors. Therefore, it was not possible to dissect any GxE in terms of sire re-ranking. A pedigree index fertility breeding value was calculated for each animal and used to understand the regression relationship between sire estimated genetic merit and the subsequent cow fertility phenotype across varying fertility environments. Results indicate that sire fertility EBV has twice the impact in the most unfavouarble 30% of herds for fertility performance. Furthermore, when this effect was investigated with quadratic terms included in the model, an increasing phenotypic response, as a function of increasing genetic merit, was observed, where high fertility exhibited a diminishing response. Results from this thesis can be used to improve the rate of gain for fertility traits, by providing guidance to farmers, who operate herds with unfavourable fertility performance, to target sires with higher genetic merit for fertility. Whilst farmers operating high fertility herds just have to avoid low fertility sires, and therefore can focus selection pressure on other traits.