PADDY AND RAGI CROP YEILD PREDICTION AND RICE BLAST DISEASE DETECTION USING ML

Computer Science and Engineering

There are numerous issues facing the agricultural industry today, including how to enhance crop production, maintain correct agricultural parameters, maintain proper fertilizer, decrease the incidence of farmer suicides, and raise farmer profitability, among others. Since humans cannot survive without food, it is possible that food is the most significant part of life. Crop risk management and transportation decisions are guided by crop yield predictions, which also aid in managing crop storage. As a result, food storage becomes absolutely necessary for all nations, especially emerging ones. Storing enough food for the long term is a crucial goal for the governments of these nations, especially in the event of a catastrophic calamity. Consequently, estimating food is exceedingly difficult. The world's population demonstrates the need for increased production... Productivity can be increased by protecting the crops and preventing them from diseases and pests. Identification of diseases plays a major role in prevention or protection of crops. Here, Oryza Sativa (Rice or Paddy Crop) is considered. A very common disease which attacks this crop is the Rice Blast. The identification of this disease can be done using Deep learning CNN. It is very important to detect this disease in paddy crops as rice is one of the main food items which is required by everyone in the world.

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