Federico Padilla Gonzalez

Federico Padilla Gonzalez is a Researcher at Wageningen University & Research, where he contributes to Team Pesticides 2. His work focuses on advanced metabolomics and analytical chemistry applications for food safety and pesticide risk assessment, with significant contributions to Cannabis sativa and Asteraceae family research. He leverages high-resolution mass spectrometry and chemometric approaches to investigate plant specialized metabolism and identify bioactive compounds.

His research spans metabolomics, plant biochemistry, and natural products chemistry, emphasizing terpenoid biosynthesis, sesquiterpene lactone regulation, and hemp seed metabolome characterization. Key methodologies include LC-MS/MS spectral analysis and machine learning modeling for metabolite identification. Recent publications reveal a strong trend toward AI-integrated analytical techniques for food chain risk assessment and the discovery of novel molecular families in underutilized plant species.

Padilla Gonzalez leads the active project "New horizons of AI in HRMS analysis" (2025-2028) and completed "Untargeted analyses of ergot alkaloids" (2024). He created two major open datasets on chemical risks in the food chain, highlighted in FAIR Data Fund media coverage. His collaborative network spans international institutions, focusing on plant chemical diversity and its implications for food safety and human health.