The Crop Recommendation is a machine learning-based application that provides recommendations for suitable crops based on various environmental and soil conditions. It aims to assist farmers and agricultural professionals in making informed decisions about crop selection, optimizing yields, and maximizing profitability.
The system takes into account several factors such as soil nutrients, climate, rainfall, temperature, humidity, and pH levels to determine the most suitable crops for a given region. By analyzing historical data and using predictive models, the system provides personalized recommendations tailored to the specific conditions of a farm or agricultural area.
Context
Precision agriculture is in trend nowadays. It helps the farmers to get informed decision about the farming strategy. Here is a dataset which would allow the users to build a predictive model to recommend the most suitable crops to grow in a particular farm based on various parameters.
This dataset was build by augmenting datasets of rainfall, climate and fertilizer data available for India.
Data fields
- N - ratio of Nitrogen content in soil
- P - ratio of Phosphorous content in soil
- K - ratio of Potassium content in soil
- temperature - temperature in degree Celsius
- humidity - relative humidity in % -ph - ph value of the soil
- rainfall - rainfall in mm