An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions
As an essential component of the architecture of a plant, leaves are crucial to sustaining decision-making in cultivars and effectively support agricultural processes. When the leaf area is constantly monitored, a plant’s health and productive capacity can be assessed to foment proactive and reactiv...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Information Processing in Agriculture |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214317324000192 |
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| author | Gabriel S. Vieira Afonso U. Fonseca Naiane Maria de Sousa Julio C. Ferreira Juliana Paula Felix Christian Dias Cabacinha Fabrizzio Soares |
| author_facet | Gabriel S. Vieira Afonso U. Fonseca Naiane Maria de Sousa Julio C. Ferreira Juliana Paula Felix Christian Dias Cabacinha Fabrizzio Soares |
| author_sort | Gabriel S. Vieira |
| collection | DOAJ |
| description | As an essential component of the architecture of a plant, leaves are crucial to sustaining decision-making in cultivars and effectively support agricultural processes. When the leaf area is constantly monitored, a plant’s health and productive capacity can be assessed to foment proactive and reactive strategies. Because of that, one of the most critical tasks in agricultural processes is estimating foliar damage. In this sense, we present an automatic method to estimate leaf stress caused by insect herbivory, including damage in border regions. As a novelty, we present a method with well-defined processing steps suitable for numerical analysis and visual inspection of defoliation severity. We describe the proposed method and evaluate its performance concerning 12 different plant species. Experimental results show high assertiveness in estimating leaf area loss with a concordance correlation coefficient of 0.98 for grape, soybean, potato, and strawberry leaves. A classic pattern recognition approach, named template matching, is at the core of the method whose performance is compared to cutting-edge techniques. Results demonstrated that the method achieves foliar damage quantification with precision comparable to deep learning models. The code prepared by the authors is publicly available. |
| format | Article |
| id | doaj-art-10d44b504cd048f2bc50f09fb18b3d72 |
| institution | OA Journals |
| issn | 2214-3173 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Information Processing in Agriculture |
| spelling | doaj-art-10d44b504cd048f2bc50f09fb18b3d722025-08-20T02:02:02ZengElsevierInformation Processing in Agriculture2214-31732025-03-01121405310.1016/j.inpa.2024.03.001An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regionsGabriel S. Vieira0Afonso U. Fonseca1Naiane Maria de Sousa2Julio C. Ferreira3Juliana Paula Felix4Christian Dias Cabacinha5Fabrizzio Soares6Federal Institute Goiano, Computer Vision Laboratory, Urutaí GO, Brazil; Federal University of Goiás, Pixellab Laboratory, Goiânia GO, Brazil; Corresponding author at: Federal Institute Goiano, Computer Vision Laboratory, Urutaí GO, Brazil.Federal University of Goiás, Pixellab Laboratory, Goiânia GO, BrazilFederal University of Goiás, Pixellab Laboratory, Goiânia GO, BrazilFederal Institute Goiano, Computer Vision Laboratory, Urutaí GO, BrazilFederal University of Goiás, Pixellab Laboratory, Goiânia GO, BrazilFederal University of Minas Gerais/UFMG, Institute of Agrarian Science, Montes Claros MG, BrazilFederal University of Goiás, Pixellab Laboratory, Goiânia GO, BrazilAs an essential component of the architecture of a plant, leaves are crucial to sustaining decision-making in cultivars and effectively support agricultural processes. When the leaf area is constantly monitored, a plant’s health and productive capacity can be assessed to foment proactive and reactive strategies. Because of that, one of the most critical tasks in agricultural processes is estimating foliar damage. In this sense, we present an automatic method to estimate leaf stress caused by insect herbivory, including damage in border regions. As a novelty, we present a method with well-defined processing steps suitable for numerical analysis and visual inspection of defoliation severity. We describe the proposed method and evaluate its performance concerning 12 different plant species. Experimental results show high assertiveness in estimating leaf area loss with a concordance correlation coefficient of 0.98 for grape, soybean, potato, and strawberry leaves. A classic pattern recognition approach, named template matching, is at the core of the method whose performance is compared to cutting-edge techniques. Results demonstrated that the method achieves foliar damage quantification with precision comparable to deep learning models. The code prepared by the authors is publicly available.http://www.sciencedirect.com/science/article/pii/S2214317324000192Leaf area measurementDefoliationInsect predatingSmart farmingPrecision agriculture |
| spellingShingle | Gabriel S. Vieira Afonso U. Fonseca Naiane Maria de Sousa Julio C. Ferreira Juliana Paula Felix Christian Dias Cabacinha Fabrizzio Soares An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions Information Processing in Agriculture Leaf area measurement Defoliation Insect predating Smart farming Precision agriculture |
| title | An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| title_full | An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| title_fullStr | An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| title_full_unstemmed | An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| title_short | An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| title_sort | automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions |
| topic | Leaf area measurement Defoliation Insect predating Smart farming Precision agriculture |
| url | http://www.sciencedirect.com/science/article/pii/S2214317324000192 |
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