  Farmers face several challenges when growing crops like uncertain irrigation,
poor soil quality, etc. Especially in India, a major fraction of farmers do not
have the knowledge to select appropriate crops and fertilizers. Moreover, crop
failure due to disease causes a significant loss to the farmers, as well as the
consumers. While there have been recent developments in the automated detection
of these diseases using Machine Learning techniques, the utilization of Deep
Learning has not been fully explored. Additionally, such models are not easy to
use because of the high-quality data used in their training, lack of
computational power, and poor generalizability of the models. To this end, we
create an open-source easy-to-use web application to address some of these
issues which may help improve crop production. In particular, we support crop
recommendation, fertilizer recommendation, plant disease prediction, and an
interactive news-feed. In addition, we also use interpretability techniques in
an attempt to explain the prediction made by our disease detection model.
