Phaeosphaeria leaf spot (PLS), a disease caused by a fungus, is one of the major diseases that threaten the stability of maize production in tropical and subtropical Africa. Small pale green to yellow spots develop on affected maize leaf blades, which progess to cover the entire leaf in severe cases.
The study aimed to investigate if remotely sensed data can be used to detect the early stage of PLS in tropical maize. The researchers were able to differentiate between healthy and early stage PLS affected plants. The results show a potential for remote sensing datasets and techniques in detecting early stage infestation in tropical maize. This information will help farmers to apply fungicides to control PLS infestation at the right place and avoid continuous monitoring to detect the disease.
This work was carried out by the Geo-Information Unit. It is partly funded by the UK Department for International Development, a core donor of the International Centre of Insect Physiology and Ecology.
Adam E., Deng H., Odindi J., Abdel-Rahman E.M. and Mutanga O. (2017) Detecting the early stage of phaeosphaeria leaf spot infestations in maize crop using in situ hyperspectral data and guided regularized random forest algorithm. Journal of Spectroscopy 2017, doi.org:6961310.6961155/6962017/6961387.
Detecting the early stage of phaeosphaeria leaf spot infestations in maize crop using in situ hyperspectral data and guided regularized random forest algorithm