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Machine learning saves gardeners' plants from pests

Copyright: GrowVeg.co.uk

A service which predicts the arrival of insect pests is helping gardeners to protect their produce and reduce chemical pesticide use.

Data breakout

86% Average prediction accuracy of aphid movements by the predictive model
£200k Value of investment from BBSRC and Innovate UK
33-43% Anticipated increase in revenue for Growing Interactive

Dr Daniel Kudenko from the University of York and Dr Paul Holloway, now at University College Cork, used geographical and temporal data from the Rothamsted Insect Survey (RIS) and large-scale citizen science project The Big Bug Hunt to develop a predictive model of insect migrations. Using this model, the pest prediction service alerts users of predicted outbreaks, enabling them to implement biological control measures in advance.

Gardening app developer Growing Interactive will incorporate the service into their existing Garden Planner app and anticipate a 33-43% increase in revenue.

Key impacts

  • The pest prediction service will help gardeners protect their crops before bugs arrive, without using chemical pesticides.
  • Gardening app developer Growing Interactive anticipate a 33-43% increase in revenue through increased subscriptions.
  • “We have been delighted with the enthusiastic response from gardeners around the world, and the partnership with the University of York through BBSRC and Innovate UK has enabled us to make the most of this extensive data.” – Jeremy Dore, founder, Growing Interactive.

Read the full impact evidence report:

Machine learning saves gardeners' plants from pests (PDF 1.63MB)

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