This project aims to optimise the Norwegian Red (NR) dairy cattle breeding program through the integration of NrfTwin, a digital twin of NR breeding program. NrfTwin enables simulations of various changes in the breeding program to achieve significant and sustainable advancements in the genetic gain without jeopardising the national herd's genetics. The primary focus is on improving the overall sustainability of NR by enhancing efficiency and reducing the environmental footprint. The first key objective is genetic improvement of feed efficiency and methane emission through the application of milk infra-red spectra that is available for every cow in Norway. To date, we have collected approximately 40,000 MIR spectra data points from over 500 cows on farms where phenotypes for feed intake and methane emissions are recorded and have executed the initial phenotypic predictions of enteric methane emission. The second major aim is to optimize reproductive and genomic technologies in the current breeding program. We have developed simulation code to compare different embryo production strategies and various scenarios for the application of sexed semen within the NR breeding program. The third objective analyses the potential to enhance the current breeding program through the efficient fusion of purebreds and crossbreds, supported by the development of simulation code for two future breeding programs designed for genetic information exchange. These outcomes will lead to increased resource efficiency, a smaller environmental footprint, improved farm profitability, and a higher return on investment in the NR breeding program, strengthening Geno’s position in the dairy cattle breeding industry.
The project aims to improve the Norwegian Red Dairy Cattle (NR) breeding program through the integration of digital twin of Geno's breeding program (NrfTwin) and advanced breeding techniques. By utilizing NrfTwin simulations and data-driven approaches, the project seeks to optimize the breeding program for increased genetic progress in feed efficiency, methane emission reduction, fertility rates, and overall sustainability. The implementation of NrfTwin will enable rapid evaluation of different breeding scenarios and selection criteria without risking the genetics of the national herd. Through multidisciplinary collaboration and advanced data management systems, the project aims to foster innovation, collaboration, and continuous learning within the organization. The innovation addresses the need to improve the environmental impact of dairy cattle breeding by prioritizing traits that promote productivity, efficiency, and sustainability. By incorporating advanced breeding techniques and leveraging genetic advancements, the project aims to enhance the competitiveness of NR genetics in national and international markets. The research also focuses on optimizing the phenotyping, genotyping, and genetic evaluation methodology to maximize selection accuracy and genetic gain. The use of milk infra-red spectra and advanced prediction machinery will further contribute to the optimization of the breeding program. The project has significant positive impacts on society, including increased resource efficiency, reduction of environmental footprint, improved profitability for farmers, self-sufficiency in food production, and dissemination of knowledge. Overall, the project's outcomes will enhance the return on investment in the NR breeding program, positioning Geno as a more efficient and competitive organization in the dairy cattle breeding industry.
