1Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM University, Visakhapatnam-530 045, Andhra Pradesh, India
Vishwakarma Institute of Information Technology, Pune-411 048, Maharashtra, India
*Corresponding Author: Ratnmala Nivrutti Bhimanpallewar, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM University, Visakhapatnam-530 045, Andhra Pradesh, India, Email: ratnmalab@gmail.com
Online Published on 09 May, 2022.
The key source of income in India is agriculture, so farming is called as backbone of Indian economy. To satisfy the need of increasing population increase in the crop yield is very important. India country programming framework stated that, the annual soil loss in India is about 5.3 billion tonnes.
Majority farmers are small or marginal scale and are dependent on natural resources like soil-quality, rainfall and environmental condition etc. for their yield. Based on experience farmers decide which crop to be adopted. Government is arranging trainings and exhibitions to enhance the skillset of farmers.
A land which gives poor yield for one crop may produce adequate yield for some other crop/crops. To know the possible suitable crop/crops proposed machine learning model focuses current and potential suitability evaluation for available scenario.
Classification, Decision tree, Fragmented land, Soil nutrients, Soil suitability
