A Multi-Objective Composite Model for Crop Prediction using Machine Learning Methods

Every year, numerous farmers face problems because of seasonal and viral crop diseases, and results in crop loss. The proposed model, “FARMECO”, detects the crop diseases so that the farmer may be privy to it and search for solutions. It is often likely that the diseases go undetected but are not known to the general public. So this study has considered some well-known diseases and built a proposed ML predictive model. The proposed model initially requests the farmer (client) to offer pictures of the plant wherein they may experience any abnormalities and take them as input. Then, the TeachableMachines.io is used to add numerous pattern images of that precise plant and the diseases attacking it typically and try to expect what diseases the given plant pattern is struggling with. These challenges assist us in diagnosing the disorder or trouble so that some measures can be taken accordingly.