Machine learning is the next-generation solution to identifying patterns in large datasets and involves using computer science and statistics to analyse very large datasets. These datasets are too complex to uncover with traditional human-led analysis. This project will use large volumes of data (plot images, environmental, soil, crop yield, grain quality, single-nucleotide polymorphism data, weather and lidar) with the aim of providing a predictive tool or computational model to assist breeders increase genetic gain in a range of crops by finding the gene and environmental factors that maximise yield.