Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems

Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems

Abstract Background Charcoal rot is a fungal disease that thrives in warm dry conditions and affects the yield of soybeans and other important agronomic crops worldwide. There is a need for robust, automatic and consistent early detection and quantification of disease symptoms which are important in...

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Bibliographic Details
Main Authors: Koushik Nagasubramanian, Sarah Jones, Soumik Sarkar, Asheesh K. Singh, Arti Singh, Baskar Ganapathysubramanian
Format: Article
Language:English
Published: BMC 2018-10-01
Series:Plant Methods
Subjects:
Charcoal rot
Soybean disease
Precision agriculture
Band selection
Genetic algorithm
Support vector machines
Online Access:http://link.springer.com/article/10.1186/s13007-018-0349-9

Internet

http://link.springer.com/article/10.1186/s13007-018-0349-9

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