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A review of neural networks in plant disease detection using hyperspectral data


Balasundram, Siva Kumar and Golhani, Kamlesh and Vadamalai, Ganesan and Pradhan, Biswajeet (2018) A review of neural networks in plant disease detection using hyperspectral data. Information Processing in Agriculture, 5 (3). 354 - 371. ISSN 2214-3173


This paper reviews advanced Neural Network (NN) techniques available to process hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a review on NN mechanism, types, models, and classifiers that use different algorithms to process hyperspectral data. Then we highlight the current state of imaging and non-imaging hyperspectral data for early disease detection. The hybridization of NN-hyperspectral approach has emerged as a powerful tool for disease detection and diagnosis. Spectral Disease Index (SDI) is the ratio of different spectral bands of pure disease spectra. Subsequently, we introduce NN techniques for rapid development of SDI. We also highlight current challenges and future trends of hyperspectral data.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Agriculture
DOI Number: https://doi.org/10.1016/j.inpa.2018.05.002
Publisher: Elsevier
Keywords: Plant disease; Agricultural production; Neural Network (NN)
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 27 Nov 2020 20:13
Last Modified: 27 Nov 2020 20:13
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.inpa.2018.05.002
URI: http://psasir.upm.edu.my/id/eprint/72968
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