Fred van Eeuwijk

Prof. Fred van Eeuwijk is a Full Professor in the Department of Mathematical and Statistical Methods - Biometris at Wageningen University & Research. His research focuses on integrating statistical genetics, computational biology, and agricultural science to address challenges in plant breeding and genotype-environment interaction (GxE). He specializes in quantitative trait locus (QTL) mapping, genomic prediction, and high-throughput phenotyping (HTP) data analysis. Recent work includes developing Bayesian models for methane production in dairy cows, epistasis analysis in Arabidopsis, and reaction norm models for GxE prediction.

Key projects involve creating chromosome substitution mapping panels, analyzing organellar genome effects in plants, and advancing methodologies for multi-omic data integration. He leads collaborative initiatives across Europe and Australia to characterize crop adaptation under environmental stress, leveraging satellite imagery and computational tools like the statgenHTP R package. His work bridges statistical innovation with practical applications in sustainable agriculture.

Supervised PhD candidates include Jasper Solin (predictive plant breeding), Koen Melsen (AI for plant phenotypes), and Yong Shao (longitudinal plant analysis). He advises on multi-environment genomic prediction strategies and has contributed to datasets such as maize yield response studies and sorghum phosphorus efficiency mapping.

Research outputs emphasize open-access methodologies, with over 293 publications including influential work on GxE modeling and reciprocal cybrid analysis. His lab's interdisciplinary approach addresses global agricultural challenges through data-driven innovation.