DVTXAI: a novel deep vision transformer with an explainable AI-based framework and its application in agriculture: DVTXAI: a novel deep vision transformer...: S. Kamal et al.

Agriculture is one of the fundamental components of human civilization, contributing not only to food production but also to economic growth. Early identification of diseases in plants presents a significant challenge, as timely identification is crucial to increasing agricultural production. Incorporating the latest technology, such as artificial intelligence (AI) techniques, in fields can reduce major losses for farmers and also improve productivity. In this paper, we have proposed a Deep Vision transformer and an Explainable AI (XAI)-based technique to address various diseases in plants. Here, we have used the dataset “Plant Village" as a case study that focuses on two majorly grown crops like: potatoes and tomatoes. In addition, we have analysed nine diseases that affect these crops around the world, with tomatoes showing six different conditions and potatoes affected by three bacterial diseases. The proposed DVTXAI framework incorporates the Deep vision transforms to identify plant diseases at an early stage. In the experiments, the proposed model achieves an accuracy of 93.56% for tomatoes and 99.95% for potatoes. Additionally, to make model ‘Trustworthy’, we make model Explainable, which reveals the transparency mechanism that helps the farmer to make the right decision at an early stage of the crop. [ABSTRACT FROM AUTHOR]