Cassava vascular bacteriosis detection using spectral measurement of color leaf

Résumé

Plant diseases early detection is primordial to determine an appropriate treatment. However, the traditional identification methods are time consuming and sometimes diseases spot appear before to identify the pathology relying to naked eye observation. So many method based on color space measurement were developed to simplify disease detection for plant diseases. In this work, we developed developed a neural network model based on CIELAB color space for early detection of cassava vascular bacteriosis. The results obtained show a perfect detection with regard to the Rsquare coefficient = 0.98 and RMSE = 0.05.