Project
Developing sustainable breeding strategies for dairy cattle in China with emphasis on improved resilience
PhD project by Rui Shi. China’s desire to increase its self-sufficiency for milk production would inevitably result in a dramatic impact on the environment when the current breeding goal will not be adapted. The objective of this research is developing sustainable and environmentally friendly breeding strategies for dairy cattle in China with a minimum impact on the environment and cows better prepared to future climatic conditions.
The demand for animal products such as meat and milk products are increasing in China, while China is not self-sufficient for these products. Increasing production and efficiency of dairy cattle production is therefore needed. At the same time, the environmental impact of dairy production should be decreased.From a breeding point of view, balanced breeding is the best way to simultaneously improve production efficiency and health and resilience. The objective of this research is to develop sustainable breeding strategies increasing efficiency and resilience and reducing environmental impact of dairy production.
Four aspects will be the cornerstones to make the dairy cattle industry in China more sustainable: (1) formulation of a selection index with functional traits, (2) quantifying the environmental impacts indicators of dairy cows and including them in the breeding procedures, (3) inclusion of novel traits to improve sustainability of current breeding goals (4) designing a breeding strategy to optimally achieve genetic improvement in the balanced breeding goal.
The approach for the first objective is to expand the current breeding goal through inclusion of functional traits. Genetic parameters and economic values of corresponding traits will be calculated to obtain maximal genetic improvement and long-term farm profit in China. The approach for the second objective is to extend the existing bio-economic model to evaluate the environmental consequences of genetic improvement in terms of nutrients losses, greenhouse gas emissions, and the food-feed competition. The approach for the third objective includes: (1) applying genetic analysis for feed efficiency and resilience, with the assessment of genotype by environment interactions. (2) performing genome wide association study and genomic selection for these novel traits. The approach for the fourth objective is to assess the future genetic gains of these updated indices after inclusion of the new traits developed in previous objectives, through simulation studies to select optimal indices for the dairy industry of China.