Determine the Soil Nutrients to Find the Crop Yields Using Data Mining Algorithms

Abstract

Crop cultivation used to be done by farmers who had hands-on experience. However, crop yields have begun to suffer as a result of climate change. As a result, farmers are unable to select the appropriate crop/s based on soil and environmental parameters, and the process of manually predicting the appropriate crop/s of land has frequently failed. Crop prediction accuracy leads to higher crop production. The agriculture is fully based on the soil wealth, climatic conditions, irrigation, quality of seeds, harvesting etc.  It is really important all around the world. Only a seasoned farmer can recognise the type of soil and select the appropriate crop for it. Predicting the soil type and its surrounding environment for a specific field is crucial for future crop yields. This study focuses on using a range of data mining techniques to estimate future soil conditions and boost crop production. Clustering, OneR, and J48 are among the data mining techniques used in the study. These data mining techniques are used to systematically anticipate and analyse soil bearing in order to improve crop output. This technique would be more useful to farmers in identifying the type of the soil and its riches, which, in turn, would help them choose the crop that is best suited to their soil and produces the highest yield.