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

Lowe, Amy; Harrison, Nicola; French, Andrew P.

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.

Citation

Lowe, A., Harrison, N., & French, A. P. (2017). Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant Methods, 13, Article 80. https://doi.org/10.1186/s13007-017-0233-z

• Journal Article Type: Article
• Acceptance Date: Oct 3, 2017
• Publication Date: Oct 10, 2017
• Deposit Date: Oct 17, 2017
• Publicly Available Date: Oct 17, 2017
• Journal: Plant Methods
• Electronic ISSN: 1746-4811
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Article Number: 80
• DOI: https://doi.org/10.1186/s13007-017-0233-z
• Keywords: Hyperspectral imaging; Image analysis techniques; Vegetation Indices; Plant disease and stress; Early; detection of stress; Hyperspectral image analysis
• Public URL: https://nottingham-repository.worktribe.com/output/887442
• Publisher URL: https://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0233-z
• Contract Date: Oct 17, 2017