Evidence map›Paper›PMID 35450199›Full record

ArticleAdvances in continuous and discrete models2022

A delayed plant disease model with Caputo fractional derivatives.

Pushpendra Kumar, Dumitru Baleanu, Vedat Suat Erturk, Mustafa Inc, V Govindaraj

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Article in Advances in continuous and discrete models, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Pushpendra KumarDepartment of Mathematics, National Institute of Technology Puducherry, Karaikal, 609609 India.ORCID 0000-0002-7755-2837
Dumitru BaleanuDepartment of Mathematics, Cankaya University, Ankara, Turkey.
Vedat Suat ErturkDepartment of Mathematics, Ondokuz Mayis University, Atakum, 55200 Samsun Turkey.
Mustafa IncDepartment of Computer Engineering, Biruni Universiity, Istanbul, Turkey.
V GovindarajDepartment of Mathematics, National Institute of Technology Puducherry, Karaikal, 609609 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington-DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams-Bashforth-Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study.

Indexed as

Caputo fractional derivativeCrowding effectDisease resistanceFractional mathematical modelIncubation periodPredictor–corrector algorithmTime-delay

Identifiers

PMID35450199
PMCPMC8799979

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