Genomics of Resilience in Dairy Cattle of Austria and East Africa
SUPERVISOR: Johann SÖLKNER
PROJECT ASSIGNED TO: Mabel AGYIRI
Livestock are subject to a wide range of disturbances both from their internal and external environments throughout their lifespan. It is essential that they can effectively cope with these challenges and recover promptly. Heat stress is one of the conditions that threaten livestock farming, mostly driven by climate change. It is characterised by increased temperature conditions that exceed the thermoregulatory potential of animals. Reduction in reproductive performance, milk production, growth, and increase in disease occurrence are some of the numerous effects of heat stress on dairy cattle. Beyond heat stress, livestock in arid regions face significant fluctuations in the availability and quality of feed and water throughout the year due to climate change. Energy is thus channelled away from production towards the survival of the animal, posing a threat to food security. In Austria, open-sided roofed housing is typical of cattle farms. During winter periods, this can also potentially cause cold stress to cows. Breeding for resilience is one of the approaches that is increasingly being sought to manage the situation. Resilience refers to the ability of an animal to be minimally impacted or swiftly recover in terms of its physiological, behavioural, cognitive, health, and productive state prior to a disturbance. Recent studies have shown that variation in the daily milk yield of cattle captures the disturbances in milk yield patterns, and this can provide indicators of resilience that can be used in breeding more resilient cows. With the development of precision livestock farming technology like the automated milking system, such data can be collected on cattle. This study will explore the patterns of fluctuation of daily milk yields in Austrian dairy cattle. Indicators of resilience will be defined using the daily milk yields of cows and correlated with diseases such as mastitis and fertility-related conditions to determine their potential use for selection. Genetic parameters will also be derived for the resilience indicators. The results from this study will be compared with those from East Africa to provide data on breed and geographic differences. The general workflow of this PhD is as follows: