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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM57486

Intelligence Blight Damage Estimator for Yield Prediction

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM57486

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM57486

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

DB

Dinesh B

D

Dr.S.Mohana

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Abstract

Crop diseases are one of the major factors that reduce agricultural productivity worldwide. Among these diseases, blight significantly affects plant health and leads to considerable yield loss. Early detection and accurate estimation of blight damage are essential for farmers to take timely preventive measures and improve crop productivity. This paper proposes an intelligent system for estimating blight disease damage and predicting crop yield using machine learning and image analysis techniques. The system analyses images of plant leaves to detect blight symptoms and estimate the severity of damage. By combining disease detection with predictive analytics, the proposed framework provides insights into potential crop yield reduction. The system aims to assist farmers in making informed decisions regarding crop management, pesticide usage, and disease prevention.

KEYWORDS

Blight Disease Crop Yield Prediction Machine Learning Image Processing Smart Agriculture.

Cite This Article

Dinesh B, Dr.S.Mohana, "Intelligence Blight Damage Estimator for Yield Prediction," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026. https://doi.org/10.55041/IJSREM57486

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Publication Date

12/2/2026

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Double-Blind Peer Review

Review Rounds: 2

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

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