Mechanical Intelligence Techniques for Precision Agriculture: A Case Study with Tomato Disease Detection in Morocco

This paper provides a brief review of the application of machine learning in agriculture. For this purpose, several machine-learning algorithms were considered as SVM, ANN and CNN. Furthermore, a case study for the detection of various diseases of tomato with DNN. The efficiency of the DNN algorithm for the detection of pepper diseases has been demonstrated from the results obtained. This paper can assist researchers in this area in developing an optimal and efficient machine-learning model for various agricultural applications in the future. Within this way, and with highlighting Morocco as a developing State, this study can provide effective support information to decision makers, decision makers, professionals and end-users in introducing new techniques and utilizing follow-up techniques in the agricultural sector through their adoption.