An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions

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dc.creatorGabriel da Silva Vieira
dc.creatorAfonso Ueslei da Fonseca
dc.creatorNaiane Maria de Sousa
dc.creatorJulio Cesar Ferreira
dc.creatorJuliana Paula Felix
dc.creatorChristian Dias Cabacinha
dc.creatorFabrizzio Soares
dc.date.accessioned2025-07-18T15:00:37Z
dc.date.accessioned2025-09-09T01:32:10Z
dc.date.available2025-07-18T15:00:37Z
dc.date.issued2024
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.doihttps://doi.org/10.1016/j.inpa.2024.03.001
dc.identifier.issn2214-3173
dc.identifier.urihttps://hdl.handle.net/1843/83652
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofInformation Processing in Agriculture
dc.rightsAcesso Aberto
dc.subjectDesfolhamento
dc.subjectInsetos
dc.subjectInteligência artificial
dc.subjectAgricultura de precisão
dc.subjectParasitóides
dc.subject.otherDesfolhamento
dc.subject.otherInsetos
dc.subject.otherInteligência artificial
dc.subject.otherAgricultura de precisão
dc.subject.otherParasitóides
dc.titleAn automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions
dc.typeArtigo de periódico
local.citation.epage53
local.citation.issue1
local.citation.spage40
local.citation.volume12
local.description.resumoAs 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.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S2214317324000192

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