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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Prediction of suitable crop using machine learning
Authors Name: Mannem Ganesh Reddy , Goli Vineeth , Chapala Rithik Reddy , Dr. P. Indira Priyadarsini
Unique Id: IJSDR2005099
Published In: Volume 5 Issue 5, May-2020
Abstract: 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.
Keywords: Suitable crop, K-Nearest Neighbors Classifier, crop productivity, soil requirements.
Cite Article: "Prediction of suitable crop using machine learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 5, page no.607 - 611, May-2020, Available :http://www.ijsdr.org/papers/IJSDR2005099.pdf
Downloads: 000336257
Publication Details: Published Paper ID: IJSDR2005099
Registration ID:191872
Published In: Volume 5 Issue 5, May-2020
DOI (Digital Object Identifier):
Page No: 607 - 611
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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