Crop And Fertilizer Recommendation to Improve Crop Yield using Deep Learning

To fulfill the rising global food demand, agricultural production must be improved. Using fertilizers as efficiently as possible based on the needs of the various crops is one approach to this. To assist farmers to increase agricultural yields, deep learning algorithms may be used to produce suggestions for crops and fertilizers. A deep learning model is created using methods like CNNs, RNNs, or LSTM networks, and suggestions for crops and fertilizers are then made depending on the input data. The procedure entails gathering data on crop yields, soil properties, and fertilizer consumption. The model’s accuracy may then be tested to get better outcomes over time. The development of crop and fertilizer recommendations using deep learning can assist farmers in increasing crop yields, enhancing agricultural sustainability, and meeting the global demand for food.