Machine-Cast: A scalable machine learning framework for forecasting risk of crop pests and pathogens

Lead Participant: CLIMATE EDGE LIMITED

Abstract

In this project we are building a novel pest/disease forecasting service that uses machine learning 'ensemble' techniques to imbue highly localised predictive power and wide pest-crop-geography application potential.

This broad-spectrum approach to forecasting is highly innovative and has the potential to drive synergistic improvements in the usage of inputs across all of the UK's most important crops. This innovation will drive a reduction in agro-chem usage, increase in crop yields and reduce the carbon footprint of UK agriculture.

Lead Participant

Project Cost

Grant Offer

CLIMATE EDGE LIMITED £160,997 £ 112,698
 

Participant

INNOVATE UK
JAMES HUTTON LIMITED £23,213 £ 11,606
ALO MUNDUS LIMITED
THE JAMES HUTTON INSTITUTE £59,031 £ 59,031

Publications

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