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Modelling induced resistance to plant diseases.

Nurul S Abdul Latif1, Graeme C Wake2, Tony Reglinski3

  • 1Faculty of Agro Based Industry, Universiti Malaysia Kelantan, Jeli, Kelantan, Malaysia; Institute of Natural and Mathematical Sciences, Massey University, Auckland, New Zealand.

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This study introduces a mathematical model for induced resistance (IR) in plants, crucial for sustainable disease control. The model quantifies how elicitors enhance plant defenses, improving crop protection strategies.

Keywords:
Diplodia pineaDynamical systemElicitorInduced resistanceMethyl jasmonate

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Area of Science:

  • Plant Pathology
  • Mathematical Biology
  • Agricultural Science

Background:

  • Traditional plant disease control relies on agrochemicals with environmental risks.
  • Induced resistance (IR) offers an alternative but shows variable field efficacy.
  • Mathematical modeling can elucidate IR dynamics for improved disease management.

Purpose of the Study:

  • To propose and analyze a mathematical model for IR triggered by chemical elicitors.
  • To understand the temporal dynamics of plant resistance and susceptibility.
  • To quantitatively estimate the effectiveness of elicitors in plant disease control.

Main Methods:

  • Developed a prototype mathematical model based on epidemiological principles.
  • Modeled IR using reversible processes to describe transitions between Susceptible (S), Resistant (R), and Diseased (D) plant compartments.
  • Used computer-based algorithms to match model parameters with experimental data.

Main Results:

  • The model predicts the proportion of plants in S, R, and D compartments over time.
  • Effectiveness of chemical elicitors in enhancing plant defense is quantitatively estimated.
  • The model provides a generic framework applicable to various plant-pathogen-elicitor systems.

Conclusions:

  • Mathematical modeling is a valuable tool for understanding and optimizing induced resistance in crops.
  • The proposed model can guide the development of more effective and sustainable plant disease management strategies.
  • This approach aids in predicting disease dynamics and assessing the impact of elicitors.