Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress

Lowe, Amy and Harrison, Nicola and French, Andrew P. (2017) Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant Methods, 13 . 80/1-80/12. ISSN 1746-4811

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Abstract

This review explores how imaging techniques are being developed with a focus on deployment for crop monitoring methods. Imaging applications are discussed in relation to both field and glasshouse-based plants, and techniques are sectioned into ‘healthy and diseased plant classification’ with an emphasis on classification accuracy, early detection of stress, and disease severity. A central focus of the review is the use of hyperspectral imaging and how this is being utilised to find additional information about plant health, and the ability to predict onset of disease. A summary of techniques used to detect biotic and abiotic stress in plants is presented, including the level of accuracy associated with each method.

Item Type: Article
Keywords: Hyperspectral imaging; Image analysis techniques; Vegetation Indices; Plant disease and stress; Early detection of stress; Hyperspectral image analysis
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Biosciences
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: 10.1186/s13007-017-0233-z
Depositing User: Eprints, Support
Date Deposited: 17 Oct 2017 12:34
Last Modified: 18 Oct 2017 17:43
URI: http://eprints.nottingham.ac.uk/id/eprint/47309

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