Prediction of suitable crop using machine learning

Mannem Ganesh Reddy , Goli Vineeth , Chapala Rithik Reddy , Dr. P. Indira Priyadarsini

Suitable crop, K-Nearest Neighbors Classifier, crop productivity, soil requirements.

Agriculture in India plays a key role in economy and employment. The main drawback of farmers are they do not select the acceptable crop for their soil requirements. As a result, farmers face a critical setback in productivity. These issues faced by the farmers are addressed during this study. This study uses research data of rainfall, temperature, and season of major crops and suggests the farmer with suitable crop supported their site-specific parameters. It helps famers to settle on the proper crop and improve the crop productivity. The classification K-Nearest Neighbors algorithm is employed to classify the information during this proposed system. This technique recommends the crop based on the details like type of soil, temperature, rainfall and season which are provided by the user. Farmers can gain the advantages of using a more accurate approach to direct crops with additional information. User can view data blogs which provides detailed information about fertilizers for crops, crops which are suitable for the season based on the water availability for the user.

Published Paper   E-Certificate

"Prediction of suitable crop using machine learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 5, page no.607 - 611, May-2020, Available :https://ijsdr.org/papers/IJSDR2005099.pdf

Volume 5 Issue 5, May-2020

Pages : 607 - 611

Paper Reg. ID: IJSDR_191872

Published Paper Id: IJSDR2005099

Downloads: 000347309

Research Area: Engineering

Country: hyderabad, Telangana, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2005099

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2005099

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition