Application of machine learning to improve the prediction of blackleg (Pectobacterium atrosepticum) disease risk in potatoes

To date, a machine learning framework has been developed and refined to achieve a better understanding of blackleg risk. Preliminary findings are that the relative importance of different risk factors varies according to the seed grade and the spatial scale studied. 

To produce a precision disease management tool for predicting the risk of blackleg development in any potato growing area of Scotland