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| Registros recuperados : 85 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas; Embrapa Trigo. |
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Data corrente: |
28/01/2020 |
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Data da última atualização: |
17/09/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
LINS, E. A.; RODRIGUEZ, J. P. M.; SCOLOSKI, S. I.; PIVATO, J.; LIMA, M. B.; FERNANDES, J. M. C.; PEREIRA, P. R. V. da S.; LAU, D.; RIEDER, R. |
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Afiliação: |
ELISON ALFEU LINS, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1; JOÃO PEDRO MAZUCO RODRIGUEZ, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil; SANDY ISMAEL SCOLOSKI, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1; JULIANA PIVATO, The Brazilian Agricultural Research Corporation (Embrapa Wheat), Passo Fundo, Rio Grande do Sul, Brazil2; MARÍLIA BALOTIN LIMA, The Brazilian Agricultural Research Corporation (Embrapa Wheat), Passo Fundo, Rio Grande do Sul, Brazil2; JOSE MAURICIO CUNHA FERNANDES, CNPT; PAULO ROBERTO VALLE DA S PEREIRA, CNPF; DOUGLAS LAU, CNPT; RAFAEL RIEDER, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1. |
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Título: |
A method for counting and classifying aphids using computer vision. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Computers and Electronics in Agriculture, n. 169, 2020. |
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DOI: |
https://doi.org/10.1016/j.compag.2019.105200 |
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Idioma: |
Inglês |
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Conteúdo: |
Aphids are insects that attack crops and cause damage directly, by consuming the sap of plants, and indirectly,by vectoring microorganisms that can cause diseases. Cereal crops are hosts for many aphid species, includingRhopalosiphumpadi(an economically important aphid species). Recording and classifying aphids are necessaryfor evaluating and predicting crop damage. Thus, serving as a basis for decision making on the utilization ofcontrolmeasures.Itcanalsobeusefultoevaluateplantresistancetoaphids.Traditionally,therecordingprocessis manual and depends on magnification and well-trained staff. The manual counting is also a time-consumingprocess and susceptible to errors. With this in mind, this paper presents a method and software to automate thecounting and classification ofRhopalosiphum padiusing image processing, computer vision, and machinelearningmethods.Thetextalsopresentsacomparisonofmanuallycountsfromexpertsandvaluesobtainedwiththe software, considering 40 samples. The results showed strong positive correlation in counting and classifi-cation(rs=0.92579)and measurement (r=0.9799).Concluding, thesoftware provedtobe reliableandusefulto aphid population monitoring studies. |
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Palavras-Chave: |
Aphids; Counting. |
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Thesaurus NAL: |
Classification; Computer vision; Measurement. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/209811/1/1-s2.0-S0168169919306039-main.pdf
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Marc: |
LEADER 02015naa a2200289 a 4500
001 2119503
005 2020-09-17
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.compag.2019.105200$2DOI
100 1 $aLINS, E. A.
245 $aA method for counting and classifying aphids using computer vision.$h[electronic resource]
260 $c2020
520 $aAphids are insects that attack crops and cause damage directly, by consuming the sap of plants, and indirectly,by vectoring microorganisms that can cause diseases. Cereal crops are hosts for many aphid species, includingRhopalosiphumpadi(an economically important aphid species). Recording and classifying aphids are necessaryfor evaluating and predicting crop damage. Thus, serving as a basis for decision making on the utilization ofcontrolmeasures.Itcanalsobeusefultoevaluateplantresistancetoaphids.Traditionally,therecordingprocessis manual and depends on magnification and well-trained staff. The manual counting is also a time-consumingprocess and susceptible to errors. With this in mind, this paper presents a method and software to automate thecounting and classification ofRhopalosiphum padiusing image processing, computer vision, and machinelearningmethods.Thetextalsopresentsacomparisonofmanuallycountsfromexpertsandvaluesobtainedwiththe software, considering 40 samples. The results showed strong positive correlation in counting and classifi-cation(rs=0.92579)and measurement (r=0.9799).Concluding, thesoftware provedtobe reliableandusefulto aphid population monitoring studies.
650 $aClassification
650 $aComputer vision
650 $aMeasurement
653 $aAphids
653 $aCounting
700 1 $aRODRIGUEZ, J. P. M.
700 1 $aSCOLOSKI, S. I.
700 1 $aPIVATO, J.
700 1 $aLIMA, M. B.
700 1 $aFERNANDES, J. M. C.
700 1 $aPEREIRA, P. R. V. da S.
700 1 $aLAU, D.
700 1 $aRIEDER, R.
773 $tComputers and Electronics in Agriculture$gn. 169, 2020.
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Registro original: |
Embrapa Trigo (CNPT) |
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