Farming Assistance for Soil Fertility Improvement and Crop Prediction using XGBoost

Department of Computer Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India

^* email: man.des.rt18@rait.ac.in
^** email: ami.jai.rt18@rait.ac.in
^*** email: omk.jos.rt18@rait.ac.in
^**** email: rajashree.shedge@rait.ac.in

Abstract

In India most vital and widely practiced occupation is Agriculture and it plays a vital role in the development of our country. Soil properties, rainfall, temperature, humidity and soil pH are the factors on which agriculture is depended. In agriculture, the selection of the wrong crop may reduce crop production. Farmers should know which crops can be grown in their area. Machine Learning-based solutions are widely used in the agriculture sector. This proposed work is a recommendation system in which Machine Learning techniques are used to recommend best three crops based on soil and weather parameters. The top three crops are recommended because farmers may not have access to a particular crop if only one crop is recommended. Previous studies in this field have been done by using different Machine Learning algorithms such as Random Forest, KNN, Naïve Bayes, etc. In this proposed system XGBoost Machine Learning algorithm is used which gives better results than other algorithms. In addition, the system provides information about how to improve the soil for growing the desired crop and gives the weather forecast for next five days. As a result, this system will help farmers minimize their financial losses while also increasing crop productivity.