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

Summary

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. 

Sector:
Potatoes
Project code:
11120048
Date:
01 January 2019 - 31 July 2022
AHDB sector cost:
£74,400
Total project value:
£74,400
Project leader:
James Hutton Institute

About this project

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

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