Applying machine learning models to real world agricultural applications
In this episode Prof. Dr. Dominik Grimm from TUM Campus Straubing and Weihenstephan-Triesdorf University of Applied Sciences gives us insights into CropML, a BMBF funded project. The project evaluates new machine learning techniques for more accurate plant breeding by integrating heterogeneous external factors. Different phenotype prediction models, including basic genomic selection methods to more advanced deep learning-based techniques have been compared. Learn why advanced models are the future and where the challenges are.
Dominik is heading the Bioinformatics department at TUM Campus Straubing. He received his PhD from Max-Planck-Institute for Intelligent Systems & Max-Planck-Institute for Developmental Biology Tübingen in 2015. Dominik did his PostDoc at ETH Zürich. From there he moved on to TUM where is now Head of Bioinformatics. He receved a prize for Excellence in Teaching two years in a row.
Publication: https://www.frontiersin.org/articles/10.3389/fpls.2022.932512/full
git: https://github.com/grimmlab/easyPheno
Overview
