Automated Classification of Target Spot (Corynespora cassiicola) in Soybean Crops Using Hu Moments and Machine Learning

This paper presents a Computer Vision approach for the automatic identification of Target Spot disease in soybeans. By utilizing Hu Invariant Moments for feature extraction and Machine Learning models, the system successfully distinguished between healthy and diseased leaves. The Decision Tree model (ExtraTrees Classifier) achieved a peak accuracy of 99.4%, proving to be an effective tool for decision support in the agribusiness sector

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-09
DOI
https://doi.org/10.5281/zenodo.18193292
Primary Topic
Smart Agriculture and AI
Type
article
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article

Automated Classification of Target Spot (Corynespora cassiicola) in Soybean Crops Using Hu Moments and Machine Learning

Juliano Aragão
Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Automated Classification of Target Spot (Corynespora cassiicola) in Soybean Crops Using Hu Moments and Machine Learning

Juliano Aragão
article en

Abstract

This paper presents a Computer Vision approach for the automatic identification of Target Spot disease in soybeans. By utilizing Hu Invariant Moments for feature extraction and Machine Learning models, the system successfully distinguished between healthy and diseased leaves. The Decision Tree model (ExtraTrees Classifier) achieved a peak accuracy of 99.4%, proving to be an effective tool for decision support in the agribusiness sector

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 92%
Smart Agriculture and AI
DOIOpen Access PDFOpenAlex
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Automated Classification of Target Spot (Corynespora cassiicola) in Soybean Crops Using Hu Moments and Machine Learning — Juliano Aragão · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS