Abstract
The long-term impact of pests and diseases on plant growth and production remains a key issue for forecasting agricultural yields. To address this challenge, this thesis adopts a modeling approach that integrates pest dynamics, plant growth, and their interactions.The work proposes a model coupling framework that enables the representation of these interactions with minimal structural changes to the original models. The main objective is to assess the production of robusta coffee in Uganda, a crop particularly affected by several pests, including the Coffee Berry Borer (CBB), the Black Coffee Twig Borer (BCTB), and the Red Blister Disease (RBD).The methodology formalizes interactions between plants and pests using a cohort-based approach, which helps to manage the complexity of model integration. A modular model was developed to describe the dynamics of scolytid-type pests, incorporating their life cycle and responses to both biotic and abiotic factors. In parallel, a plant growth model based on the GreenLab formalism simulates the structure and functioning of the coffee plant while accounting for the effects of pest attacks on its development. Regulation mechanisms at various levels of the plant allow the representation of a wide range of biological responses.Model outputs are presented, based on parameterization using data from the literature and specifically designed experimental protocols. Simulations were conducted to evaluate the impact of pests on coffee production and to compare model predictions with available observations. Finally, an analysis discusses the results, their biological implications, and the modeling choices made