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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM53301

AgroMate: Smart insights for better Farming- Integrating Crop Recommendation, Disease Detection, Market Price Analysis, Digital Logbook

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM53301

Volume:

9 |

10 |

Oct 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM53301

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

NG

Namrata Gentyal1

SJ

Sneha Jadhav2

VS

Vaibhavi Samangave3

KP

Kalyani Padalkar4

PASS

Prof A. S. Shinde5

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Abstract

AgroMate is an intelligent agriculture platform integrating data analytics and artificial intelligence to assist farmers. It combines four key modules—Crop Recommendation, Disease Detection, Market Price Analysis, and a Digital Logbook. Crop Recommendation uses real-time weather and soil data to suggest optimal crops. Disease Detection identifies plant diseases through leaf image analysis. Market Price Analysis provides insights into commodity pricing trends, while the Digital Logbook organizes farm management details like pesticide and irrigation schedules. Pilot tests show AgroMate improves crop selection accuracy, disease management, and economic planning, supporting sustainable and efficient farming. ·

KEYWORDS

Smart Agriculture Crop Recommendation Plant Disease Detection Market Price Analysis Digital Logbook Artificial Intelligence (AI) Deep learning (DL) Machine Learning (ML) Data Analytics Precision Farming Weather API Integration Sustainable Farming practices

Cite This Article

Namrata Gentyal1, Sneha Jadhav2, Vaibhavi Samangave3, Kalyani Padalkar4, Prof A. S. Shinde5, "AgroMate: Smart insights for better Farming- Integrating Crop Recommendation, Disease Detection, Market Price Analysis, Digital Logbook," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 10, Oct 2025. https://doi.org/10.55041/IJSREM53301

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Publication Date

10/30/2025

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Double-Blind Peer Review

Review Rounds: 2

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0

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5

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5

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The authors declare no conflict of interest related to this research work.

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