Ina Hulsegge

Ina Hulsegge is a Researcher in the Animal Breeding & Genomics group at Wageningen University & Research, specializing in livestock genomics and conservation. Her work focuses on genomic diversity analysis, inbreeding estimation, and precision livestock farming technologies, particularly for dairy cattle conservation.

Her research spans

• Genomic profiling of livestock diversity
• Development of real-time animal identification systems using computer vision
• Conservation genomics for Dutch cattle breeds
• Deep learning applications in genotype data analysis

with strong emphasis on practical implementation in breeding programs and gene banks.

Recent publications highlight trends in

• Automated phenotyping through ear-tag recognition (2024)
• SNP array-based genomic diversity assessment (2024)
• Aneuploidy detection via deep learning (2023)
• Sub-population analysis in red-pied cattle (2023)

demonstrating her dual focus on computational innovation and conservation applications.

Scientific contributions include:

• Management systems for genomic information in gene banks (2024)
• EUGENA database updates for multi-species conservation (2024)
• Analysis of genetic changes in Dutch black-and-white cattle (2022)

She actively engages in knowledge transfer through professional presentations at precision livestock farming conferences and collaborates with institutions like CGN (Centre for Genetic Resources, the Netherlands) on conservation initiatives. Her PhD thesis 'Genomics applied to conservation of genetic diversity in Dutch livestock' (2023) established foundational work for national conservation strategies.