Studies on Detecting Plant Leaf Disease Using KNN Classifier and Severity Measurement

Food is one of the most basic needs of living beings. It is very essential to grow a sufficient quantity of crops to cope with the growing population. With time, it is seen that plants are being affected by various kinds of diseases. Different plant diseases are a major influence on agricultural output limitations, and they are generally difficult to control. As a result, early detection of plant diseases is crucial for avoiding output losses and improving the quality of agricultural goods. This research paper proposes a method to detect and classify the disease on plant leaves with a severity measurement for the grading system. The paper describes a machine learning-based detection and classification of diseases like early blight and late blight on "potato leaf" using the KNN classifier. Our research focuses on a rigorous examination of potato plant disease segmentation approaches.

Authors

Institutions

Publication Details

Journal
Journal of Mines Metals and Fuels
Published
2024-12-20
DOI
https://doi.org/10.18311/jmmf/2023/47275
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Studies on Detecting Plant Leaf Disease Using KNN Classifier and Severity Measurement

M Madhushree, V Akshaya, S. Pravinth Raja, M. Sinthuja
Journal of Mines Metals and Fuels
Smart Agriculture and AI
article

Studies on Detecting Plant Leaf Disease Using KNN Classifier and Severity Measurement

M Madhushree, V Akshaya, S. Pravinth Raja, M. Sinthuja
article en

Abstract

Food is one of the most basic needs of living beings. It is very essential to grow a sufficient quantity of crops to cope with the growing population. With time, it is seen that plants are being affected by various kinds of diseases. Different plant diseases are a major influence on agricultural output limitations, and they are generally difficult to control. As a result, early detection of plant diseases is crucial for avoiding output losses and improving the quality of agricultural goods. This research paper proposes a method to detect and classify the disease on plant leaves with a severity measurement for the grading system. The paper describes a machine learning-based detection and classification of diseases like early blight and late blight on "potato leaf" using the KNN classifier. Our research focuses on a rigorous examination of potato plant disease segmentation approaches.

Journal of Mines Metals and Fuels
Presidency University (IN), M S Ramaiah University of Applied Sciences (IN), Sri Ramakrishna Institute of Paramedical Sciences (IN), Presidency University (BD), M S Ramaiah Memorial Hospital (IN)
Zero hunger
Openalex Percentile: Top 85%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Studies on Detecting Plant Leaf Disease Using KNN Classifier and Severity Measurement — M Madhushree, V Akshaya, et al. · Journal of Mines Metals and Fuels (2024) | TGRS Research Map | TGRS