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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.

Follow this link to listen to the full podcast episode