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  Published Paper Details:

  Paper Title

MAGICROP: SMART CROP AND FERTILIZER RECOMMENDATION SYSTEM USING ML ALGORITHMS

  Authors

  Rahul Mahurkar,  Omkar Kudile,  Pankaj Chopade,  Santosh Sharma,  Sharad Adsure

  Keywords

Crop prediction, fertilizer recommendation, smart farming, machine learning

  Abstract


Farming is a significant supporter of the Indian economy. The standard Indian populace depends either verifiably unequivocally on agribusiness for their occupation. In this manner, it assumes an imperative part of the country. Avast larger part of the farmers has faith in relying upon their instinct to choose which harvest to plant in the specific season and what manures to utilize. This has been going on since old occasions. Thus, a solitary farmer can't be relied upon to consider every one of the countless variables that add to crop development before arriving at an agreement about which one to develop. A solitary misinformed choice by the farmer can have unfortunate implications on both himself and the country's agrarian economy. In this paper, we present an insightful framework called MagiCrop, which expects to help the farmer in settling on educated choices about the harvests to develop and the manures to use to boost the yield, depending upon natural factors and contents of the soil in that particular region.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2106456

  Paper ID - 208898

  Page Number(s) - d887-d891

  Pubished in - Volume 9 | Issue 6 | June 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Rahul Mahurkar,  Omkar Kudile,  Pankaj Chopade,  Santosh Sharma,  Sharad Adsure,   "MAGICROP: SMART CROP AND FERTILIZER RECOMMENDATION SYSTEM USING ML ALGORITHMS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 6, pp.d887-d891, June 2021, Available at :http://www.ijcrt.org/papers/IJCRT2106456.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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