Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques.
Journal:
Journal of the science of food and agriculture
PMID:
35657067
Abstract
BACKGROUND: Diseases such as Alternaria and pests such as leafminer threaten tomato as one of the most widely used agricultural products. These pests and diseases first damage the leaves of tomatoes, then the flowers, and finally the fruit. Therefore, the damage to the tomato tree must be controlled in its early stages. It is difficult for farmers to distinguish Alternaria disease from leafminer pest at the early and middle stages of their outbreak on tomato leaves. In the present study, 272 tomato leaf images were prepared from the farm of the Vali-e-Asr University of Rafsanjan, including 100 healthy leaves and 172 infected leaves with both Alternaria and leafminer at the initial stages. The image processing technique, texture, neural networks and adaptive network-based fuzzy inference system (ANFIS) classifiers were used to diagnose Alternaria disease and leafminer pest on this dataset.