About the project

This project is led by a breeding scientist Dr. Janez Jenk, Geno R&D

NrfTwin aims to improve the Norwegian Red (NR) dairy cattle breeding program by integrating a digital twin of Geno’s breeding system with advanced genomic and phenotyping technologies. Improving feed efficiency and reducing methane emissions are key priorities for sustainable dairy production. However, these traits are difficult and expensive to measure directly at large scale.

NrfTwin addresses this challenge by combining detailed phenotypic data, genomic information, and simulation models to optimize breeding strategies. The project uses a digital twin model to simulate and evaluate breeding scenarios without affecting the real population.

This enables rapid testing of alternative strategies for improving productivity, efficiency, and environmental performance, while maintaining genetic diversity and animal health. In addition, the project explores the use of milk mid-infrared (MIR) spectra as a cost-effective proxy for predicting feed efficiency and methane emissions across the national herd.

By integrating large-scale data with genomic prediction, the project aims to significantly increase the accuracy of selection and accelerate genetic progress.

Read more about the project

Project participants

NMBU participants

External participants

Project leader Dr Janez Jenko Geno R&D
Dr Arne Gjuvsland Geno R&D
Prof Gregor Gorjanc, The Roslin Institute, University of Edinburgh