Optimization of Crop Yield Using Machine Learning

The economic growth and food security of an agriculture-based nation are significantly influenced by agricultural planning. The choice of crop(s) is a crucial issue for agricultural planning. It is based on a variety of factors, including market and production growth rates as well as governmental regulations. For agricultural planning utilizing information approaches or system learning methodologies, several studies explored crop yield price forecast, weather prediction, soil category and crop type. The choosing of crop becomes challenging if there are several options for planting a crop at once with limited land resources. In order to overcome crop selection challenges and maximize net crop yield charges over the course of a season, K-mean algorithm is applied on the dataset to find the results as the accuracy comes out to be as 97%.