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Published December 19, 2019 | Version Version 1.0
Technical note Open

K-PIE: using K-means algorithm for Percentage Infection symptoms Estimation

Description

The K-means algorithm is one of the most effective clustering methods that has been widely used in plant disease detection. Herein, we developed a script termed K-PIE (K-means algorithm for Percentage Infection symptoms Estimation) that utilises the k-means algorithm to analyse images of both yellow and stem rust infected wheat leaves to estimate the percentage of disease symptoms based on colour analysis.

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Additional details

Funding

DeMMYR – Decoding the molecular mechanisms driving host adaptation of yellow rust on cereal crops and grasses 715638
European Commission
CEREALPATH – CEREALPATH - Training in innovative and integrated control of cereal diseases 674964
European Commission
The Norwich Research Park Biosciences Doctoral Training Partnership BB/M011216/1
UK Research and Innovation