87 Academic-industry collaborations in animal breeding: Advancing breeding through strategic partnerships.

Abstract Academic-industry partnerships have been fundamental to advancing animal breeding and genetics, providing mutual benefits through complementary expertise and resources. Industry partners contribute extensive technological infrastructure, cutting-edge phenotypic and genotypic datasets, and practical breeding program experience, while academic institutions provide fundamental research capabilities, advanced analytical methodologies, computational expertise, and dedicated graduate researchers. The most significant outcomes of these collaborations have been software developments that form the foundation of modern animal evaluation systems. Notable examples include BLUPF90 from the University of Georgia and MiXBLUP from Wageningen University, both widely adopted across the industry. These software packages, combined with robust data capture systems and databases, enable the routine genetic evaluations essential to breeding programs. The nature of academic-industry relationships has evolved considerably over time. Previously, academics directly assisted smaller breeding operations with testing program establishment, genetic evaluation implementation, and results interpretation. Today, large companies possess internal capabilities for most breeding activities yet remain dependent on externally-developed software. As companies have developed internal expertise and industry consolidation has occurred, data sharing and collaborative willingness have diminished. Many organizations now maintain dedicated internal research and development teams to reduce external dependence and protect competitive advantages. Multi-species companies increasingly operate centralized R&D divisions, though they continue to rely heavily on academic literature for theoretical foundations and software innovations. Contemporary collaborations focus on emerging areas such as multi-omics research, where academia contributes methodological expertise and software development while industry provides animal access, datasets, and infrastructure. Precision livestock farming represents another active collaboration area, with joint efforts to validate high-throughput phenotyping technologies. A notable trend is academia’s decreased generation of proprietary data through selection experiments, coupled with increased reliance on industry datasets, while companies show reduced interest in funding external research in favor of internal capacity building. Future successful collaborations will require adaptation to this evolving landscape, potentially necessitating enhanced support from government agencies and professional organizations to maintain productive academic-industry partnerships that benefit both sectors and advance the field.