CanKiwi: A Mechanistic Competition Model of Kiwifruit Bacterial Canker Disease Dynamics

• Type: Article in International Scientific Journal
• Date: 2025

Authors

Abdelkader, OH (Author) Other; Bouzebiba, H (Author) Other; Santos, MG (Author) Other; Pena, D (Author) Other; Aguiar, AP (Author) FEUP; Carvalho, SMP (Author) FCUP

Journal

Title: Agriculture (Switzerland)

Vol. 15

Final page: 1

Publisher: MDPI

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-017-Q6Y

DOI: 10.3390/agriculture15010001

Abstract (EN): This paper proposes a mathematical model based on a mechanistic approach and previous research findings for the bacterial canker disease development in kiwifruit vines. This disease is a leading cause of severe damage to kiwifruit vines, particularly in humid regions, and contributes to significant economic challenges for growers in many countries. The proposed model contains three parts. The first one is the model of the kiwifruit vine describing its light interception, its carbon acquisition, and the partitioning dynamics. The carbon resource represents the chemical energy required for maintaining the necessary respiration of the living organs and their growth processes. The second part of the model is the dynamics of the pathogenic bacterial population living within the vine's tissues and competing with them for the carbon resource required for their proliferation. The third part of the model is the carbon dynamics described by a mass conservation formula which computes the remaining amount of carbon available for competition. The model was validated by comparing simulations with experimental results obtained from growth chambers. The results show that the proposed model can simulate reasonably well the functional part of the vine in both the healthy case and the disease case without plant defense mechanisms in which the bacteria are always dominant under favorable environmental conditions. They also show that the environmental effects on the vine's growth and the infection progress are taken into account and align with the previous studies. The model can be used to simulate the infection process, predict its outcomes, test disease management techniques, and support experimental analyses.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 23