Decision support system for Western Flower Thrips management in roses production

The objective of this study is to develop an innovative system assess the risk pests using a fuzzy logic approach. designed provide farmers with index representing estimate presence Western Flower Thrips (WFT), Frankliniella occidentalis in roses greenhouse. For purpose, modular knowledge-based decision support has been designed. major findings our research are summarized four points. First all, model based on variables measured automatically via sensors and do not require human activity (damaged area leaf, sex ratio). Secondly, as only oriented toward experimentation centers but also farmers, phenomenon manual counting could be replaced by predicted value. In addition, novelty associated that it supplies daily rather than weekly WFT level. so doing, stay aware influence weather conditions its evolution. Finally, beneficial help reduce utilization pesticides decrease percentage production loss, due continuous monitoring level Because development F. highly sensitive climate change, order enhance assessment pest risk, approach, which combines data related type rose, duration sunlight meteorological conditions, was followed. Simulation results displayed at end validate