Open AccessA Review : Improving the Village wise Soil Parameter and Predict the Crop Suggestion
Author(s) -
Kamlesh A. Waghmare,
Sheetal A. Jhare
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2062171
Subject(s) - revenue , edaphic , agriculture , computer science , soil quality , machine learning , agricultural engineering , business , geography , environmental science , soil science , engineering , soil water , accounting , archaeology
India economy majorly depend on agriculture that play important role in the survival of the people. It's remain the major provider for farmers and source of revenue of our country. The main focus of this survey is on how to improve the soil quality and predict the Crop selection. We are going to study the Edaphic factor, Classification problem and prediction of village wise soil parameters. That is done by collecting number of soil testing samples for finding soil fertility indices and pH values which represent a detail overview on application of machine learning in agriculture base . Mostly above problem are solved using two advance classifier Xgboost and Logistical regression which also achieve better accuracy in these area. By applying machine learning in real time data which enabled program to present high testimonial and deep perceptivity for experts and farmers to make correct decision and take proper action