Analysis and optimal control measures of diseases in cassava population

Onah, I. S., Aniaku, S. E. and Ezugorie, O. M. (2022) Analysis and optimal control measures of diseases in cassava population. Optimal Control Applications and Methods, (doi: 10.1002/oca.2901) (Early Online Publication)

[img] Text
269619.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.



Cassava amongst other crops is ranked currently as the third most essential source of carbohydrate in the tropics and a major food source in Africa. In spite of these gains, cassava production is highly threatened by pathogen-causing diseases. In this study, a deterministic compartmental model is developed to investigate the effect of these diseases on cassava production. The local and global stabilities of the disease free and endemic equilibrium states of the model without control are analyzed. The model is extended to incorporate control techniques necessary in eradicating cassava diseases. Optimal control theory is applied on the control model to explore the impact of the introduction of resistant cassava plant, the use of all other traditional practices and the application of pesticides in the prevention and eradication of diseases in cassava production. Numerical simulation of the models are carried out and results obtained indicates that introduction of control measures should be done largely at the onset of cassava planting by introducing resistant cassava stems to reduce the spread of the disease and also maintain minimum cost for production and thereby maximize profit from its yield. The cost effectiveness analysis agreed with our earlier analysis and shows that the best and effective control is the use of resistant cassava stem together with the IPM approach.

Item Type:Articles
Status:Early Online Publication
Glasgow Author(s) Enlighten ID:Onah, Mr Ifeanyi Sunday
Authors: Onah, I. S., Aniaku, S. E., and Ezugorie, O. M.
College/School:College of Science and Engineering > School of Mathematics and Statistics
Journal Name:Optimal Control Applications and Methods
ISSN (Online):1099-1514
Published Online:09 May 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Optimal Control Applications and Methods 2022
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record