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

By Amy Lowe, N. Harrison, Andrew P. French. Plant Methods, 2017

566 citations recorded by the source corpus.

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.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/53e4d11df1dbefa59d5ffdf5e11cc53e7dba9d90

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Fulya Baysal-Gurel
2. Biswajeet Pradhan
3. Samuel C. Hassler
4. Siva K. Balasundram
5. G. Vadamalai
6. K. Golhani

In Ecology

1. Fulya Baysal-Gurel
2. Biswajeet Pradhan
3. Samuel C. Hassler

In Plant Science

1. Fulya Baysal-Gurel
2. Samuel C. Hassler
3. Siva K. Balasundram

Citations in the corpus

• A review of neural networks in plant disease detection using hyperspectral data (2018, background): “Deep learning models learn features of input data through a hierarchically organized network of neurons [88].”
• Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture (2020, methodology): “[218] Focused on hyperspectral imaging and reviewed some of its applications in detecting and classifying crop disease and stress.”
• Unmanned Aircraft System (UAS) Technology and Applications in Agriculture (2019, methodology): “This method of imaging can be useful if very specific wavelengths of light need to be measured independently—often detecting light emitted from particular biomolecules such as chlorophyll [16,27]; xanthophyll [83]; mesophyll [82]; and carotenoids [16].”