JOURNAL ARTICLE
Study of a crop-pest-natural enemy model with Z-type control — An approach to pest management.
Published In: International Journal of Biomathematics, 2023, v. 16, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mandal, Dibyendu Sekhar; Samanta, Sudip; Parshad, Rana D.; Chekroun, Abdennasser; Helal, Mohamed; Chattopadhyay, Joydev 3 of 3
Abstract
In this study, the Z-type control method is applied to an intraguild crop-pest-natural enemy model, assuming that the natural enemy can predate on both crop and pest populations. For this purpose, the indirect Z-type controller is considered in the natural enemy population. After providing the design function for the crop-pest-natural enemy model with Z-control, we find the analytical expression of the update parameter. The findings indicate that the uncontrolled system can produce chaos through period-doubling bifurcation due to crop over-consumption by the pest population. We draw a Poincaré map to confirm the occurrence of chaos and compute the maximum Lyapunov exponent. As the observations further indicate that the pest population can be controlled by using an indirect Z-control mechanism in the natural enemy population, we postulate that, if natural enemy abundance can be governed by the update parameter, any desired pest population abundance can be achieved through the proposed Z-type controller, thus controlling the pest. To verify these assertions, extensive numerical simulations are performed to explore the potential for practical application of the proposed Z-type controller. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Biomathematics. 2023/05, Vol. 16, Issue 4, p1
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2023
- ISSN:1793-5245
- DOI:10.1142/S1793524522500991
- Accession Number:161030929
- Copyright Statement:Copyright of International Journal of Biomathematics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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