Crop Intelligent: Weather based Crop Selection using Machine Learning

Agriculture is essential in all places, accounting for 18% of India’s overall Gross Domestic Product. Most crops in India are weather, soil, and planting dependent. For weather prediction, machine learning techniques such as recurrent neural networks are utilized, and to choose appropriate crops, a classification of random forests approach is utilized, which helps to boost yield and also indicates the appropriate planting time for the suitable crops. Machine learning algorithms for weather prediction such as, RNN and ANN are utilized, and the random forest is used to identify the suitable crop, while the ANN displays the highest performance data for each specified weather parameter. Weather-based crop selection has challenges due to a lack of understanding of crop sensitivity to weather, the complexity of climate change, the availability of sufficient seed types, and access to financial resources. Because of these challenges, forecasting which crops would perform best in a given place can be difficult, restricting farmers’ ability to adopt weather-based crop selection tactics.