Plant genomic selection models to be created by Artificial Intelligence

This is the first time a highly efficient genomic selection method based on machine learning has been proposed for polyploid plants – in which cells have more than two complete sets of chromosomes. The methodology, published in Scientific Reports, improved the predictive power of machine learning by more than 50%. This means that this model is much more accurate than traditional breeding techniques. Machine learning is a branch of AI that involves computer statistics and optimisation with countless applications. Its main goal is to create algorithms that automatically extract patterns from datasets.