In this episode, Patrizia Ricca from Computomics gives us comprehensive insights into xSeedScore – a breeders’ tool to develop new crop varieties adjusted to future climates. Learn about how to work with xSeedScore, about the benefits of using machine learning, and how it differs from conventional methods. What data is needed to apply xSeedScore? What role does the interaction between genetics and temperature play for future varieties?
Patrizia Ricca joined Computomics four years ago as Bioinformatics Analyst. She studied Plant Molecular Biology and Bioinformatics at the University of Tübingen, graduating at the Center for Plant Molecular Biology and the Max Planck Institute for Developmental Biology, Tübingen. Patrizia has worked in industry and academia in multiple fields. She has comprehensive and unique knowledge in plant biology, genomics, metagenomics, transcriptomics, and machine learning. Since the beginning of 2022, Patrizia is the Scientific Product Manager for xSeedScore – Computomics’ predictive plant breeding technology.