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Issue: November 2022

Volume 7 | Issue 11

Impact factor: 8.15

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Paper Title: Agricultural Crop Recommendation Based on Productivity and Season
Authors Name: Khandode Priyanka , Ugale Sakshi , Nagare Sakshi , Khairnar Vrushali , Prof. Rahul Dhokane
Unique Id: IJSDR2211145
Published In: Volume 7 Issue 11, November-2022
Abstract: As we know the fact that, India is the second largest population country in the world and majority of people in India have agriculture as their occupation. Farmers are growing same crops repeatedly without trying new verity of crops and they are applying fertilizers in random quantity without knowing the deficient content and quantity. So, this is directly affecting on crop yield and also causes the soil acidification and damages the top layer. So, we have designed the system using machine learning algorithms for betterment of farmers. Our system will suggest the best suitable crop for particular land based on content and weather parameters. And also, the system provides information about the required content and quantity of fertilizers, required seeds for cultivation. Hence by utilizing our system farmers can cultivate a new variety of crop, may increase in profit margin and can avoid soil pollution
Keywords: Precision Agriculture, Machine learning, Crop prediction, Naive Bayes, Supervised Learning, Effective farming
Cite Article: "Agricultural Crop Recommendation Based on Productivity and Season", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.990 - 992, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211145.pdf
Downloads: 000150695
Publication Details: Published Paper ID: IJSDR2211145
Registration ID:202764
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 990 - 992
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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