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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/02/2006 |
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Data da última atualização: |
17/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CAMARGO NETO, J.; MEYER, G. E.; JONES, D. D.; SAMAL, A. K. |
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Afiliação: |
JOAO CAMARGO NETO, CNPTIA; GEORGE E. MEYER, University of Nebraska; DAVID D. JONES, University of Nebraska; ASHOK K. SAMAL, University of Nebraska. |
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Título: |
Plant species identification using Eliptic Fourier leaf shape analysis. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
Computers and Electronics in Agriculture, v. 50, n. 2, p. 121-134, 2006. |
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DOI: |
https://doi.org/10.1016/j.compag.2005.09.004 |
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Idioma: |
Inglês |
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Conteúdo: |
Elliptic Fourier (EF) and discriminant analyses were used to identify young soybean (Glycine max (L.) merrill), sunflower (Helianthus pumilus), redroot pigweed (Amaranthus retroflexus) and velvetleaf (Abutilon theophrasti Medicus) plants, based on leaf shape. Chain encoded, Elliptic Fourier harmonic functions were generated based on leaf boundary. A complexity index of the leaf shape was computed using the variation between consecutive EF functions. Principle component analysis was used to select the Fourier coefficients with the best discriminatory power. Canonical discriminant analysis was used to develop species identification models based on leaf shapes extracted from plant color images during the second and third weeks after germination. The classification results showed that plant species during the third week were successfully identified with an average of correct classification rate of 89.4%. The discriminant model correctly classified on average: 77.9% of redroot pigweed, 93.8% of sunflower, 89.4% of velvetleaf and 96.5% of soybean. Using all of the leaves extracted from the second and the third weeks, the overall classification accuracy was 89.2%. The discriminant model correctly classified 76.4% of redroot pigweed, 93.6% of sunflower, 81.6% of velvetleaf, 91.5% of soybean leaf extracted from trifoliolate and 90.9% of soybean unifoliolate leaves. The Elliptic Fourier shape feature analysis could be an important and accurate tool for weed species identification and mapping. MenosElliptic Fourier (EF) and discriminant analyses were used to identify young soybean (Glycine max (L.) merrill), sunflower (Helianthus pumilus), redroot pigweed (Amaranthus retroflexus) and velvetleaf (Abutilon theophrasti Medicus) plants, based on leaf shape. Chain encoded, Elliptic Fourier harmonic functions were generated based on leaf boundary. A complexity index of the leaf shape was computed using the variation between consecutive EF functions. Principle component analysis was used to select the Fourier coefficients with the best discriminatory power. Canonical discriminant analysis was used to develop species identification models based on leaf shapes extracted from plant color images during the second and third weeks after germination. The classification results showed that plant species during the third week were successfully identified with an average of correct classification rate of 89.4%. The discriminant model correctly classified on average: 77.9% of redroot pigweed, 93.8% of sunflower, 89.4% of velvetleaf and 96.5% of soybean. Using all of the leaves extracted from the second and the third weeks, the overall classification accuracy was 89.2%. The discriminant model correctly classified 76.4% of redroot pigweed, 93.6% of sunflower, 81.6% of velvetleaf, 91.5% of soybean leaf extracted from trifoliolate and 90.9% of soybean unifoliolate leaves. The Elliptic Fourier shape feature analysis could be an important and accurate tool for weed species identification and ... Mostrar Tudo |
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Palavras-Chave: |
Análise de forma de folha; Elliptic Fourier; Espécies de planta; Machine vision; Reconhecimento padrão; Shape features. |
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Thesaurus Nal: |
Computer vision; discriminant analysis; Leaves. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02359naa a2200277 a 4500
001 1009265
005 2020-01-17
008 2006 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.compag.2005.09.004$2DOI
100 1 $aCAMARGO NETO, J.
245 $aPlant species identification using Eliptic Fourier leaf shape analysis.$h[electronic resource]
260 $c2006
520 $aElliptic Fourier (EF) and discriminant analyses were used to identify young soybean (Glycine max (L.) merrill), sunflower (Helianthus pumilus), redroot pigweed (Amaranthus retroflexus) and velvetleaf (Abutilon theophrasti Medicus) plants, based on leaf shape. Chain encoded, Elliptic Fourier harmonic functions were generated based on leaf boundary. A complexity index of the leaf shape was computed using the variation between consecutive EF functions. Principle component analysis was used to select the Fourier coefficients with the best discriminatory power. Canonical discriminant analysis was used to develop species identification models based on leaf shapes extracted from plant color images during the second and third weeks after germination. The classification results showed that plant species during the third week were successfully identified with an average of correct classification rate of 89.4%. The discriminant model correctly classified on average: 77.9% of redroot pigweed, 93.8% of sunflower, 89.4% of velvetleaf and 96.5% of soybean. Using all of the leaves extracted from the second and the third weeks, the overall classification accuracy was 89.2%. The discriminant model correctly classified 76.4% of redroot pigweed, 93.6% of sunflower, 81.6% of velvetleaf, 91.5% of soybean leaf extracted from trifoliolate and 90.9% of soybean unifoliolate leaves. The Elliptic Fourier shape feature analysis could be an important and accurate tool for weed species identification and mapping.
650 $aComputer vision
650 $adiscriminant analysis
650 $aLeaves
653 $aAnálise de forma de folha
653 $aElliptic Fourier
653 $aEspécies de planta
653 $aMachine vision
653 $aReconhecimento padrão
653 $aShape features
700 1 $aMEYER, G. E.
700 1 $aJONES, D. D.
700 1 $aSAMAL, A. K.
773 $tComputers and Electronics in Agriculture$gv. 50, n. 2, p. 121-134, 2006.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
22/12/2008 |
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Data da última atualização: |
23/11/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - A |
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Autoria: |
PARAIBA, L. C.; KATAGUIRI, K. |
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Afiliação: |
LOURIVAL COSTA PARAIBA, CNPMA; Karen Kataguiri, Faculdade de Engenharia Ambiental-UNESP Sorocaba. |
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Título: |
Model approach for estimating potato pesticide bioconcentration factor. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
Chemosphere, v. 73, p.1247-1252, 2008. |
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Idioma: |
Inglês |
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Conteúdo: |
e presented a model that estimates the bioconcentration factor (BCF) of pesticides in potatoes supposing that the pesticide in the soil solution is absorbed by the potato by passive diffusion, following Fick?s second law. The pesticides in the model are nonionic organic substances, traditionally used in potato crops that degrade in the soil according to a first-order kinetic equation. This presents an expression that relates BCF with the pesticide elimination rate by the potato, with the pesticide accumulation rate within the potato, with the rate of growth of the potato and with the pesticide degradation rate in the soil. BCF was estimated supposing steady state equilibrium of the quotient between the pesticide concentration in the potato and the pesticide concentration in the soil solution. It is suggested that a negative correlation exists between the pesticide BCF and the soil sorption partition coefficient. The model was built based on the work of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103? 3108], in which an expression to calculate the diffusivity of persistent organic substances in potatoes is presented. The model consists in adding to the expression of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103?3108] the hypothesis that the pesticide degrades in the soil. The value of BCF suggests which pesticides should be monitored in potatoes. Menose presented a model that estimates the bioconcentration factor (BCF) of pesticides in potatoes supposing that the pesticide in the soil solution is absorbed by the potato by passive diffusion, following Fick?s second law. The pesticides in the model are nonionic organic substances, traditionally used in potato crops that degrade in the soil according to a first-order kinetic equation. This presents an expression that relates BCF with the pesticide elimination rate by the potato, with the pesticide accumulation rate within the potato, with the rate of growth of the potato and with the pesticide degradation rate in the soil. BCF was estimated supposing steady state equilibrium of the quotient between the pesticide concentration in the potato and the pesticide concentration in the soil solution. It is suggested that a negative correlation exists between the pesticide BCF and the soil sorption partition coefficient. The model was built based on the work of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103? 3108], in which an expression to calculate the diffusivity of persistent organic substances in potatoes is presented. The model consists in adding to the expression of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato mo... Mostrar Tudo |
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Palavras-Chave: |
Modelagem matemática. |
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Thesagro: |
Agrotóxico. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/150408/1/2008AP-13.pdf
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Marc: |
LEADER 02130naa a2200157 a 4500
001 1015596
005 2016-11-23
008 2008 bl uuuu u00u1 u #d
100 1 $aPARAIBA, L. C.
245 $aModel approach for estimating potato pesticide bioconcentration factor.$h[electronic resource]
260 $c2008
520 $ae presented a model that estimates the bioconcentration factor (BCF) of pesticides in potatoes supposing that the pesticide in the soil solution is absorbed by the potato by passive diffusion, following Fick?s second law. The pesticides in the model are nonionic organic substances, traditionally used in potato crops that degrade in the soil according to a first-order kinetic equation. This presents an expression that relates BCF with the pesticide elimination rate by the potato, with the pesticide accumulation rate within the potato, with the rate of growth of the potato and with the pesticide degradation rate in the soil. BCF was estimated supposing steady state equilibrium of the quotient between the pesticide concentration in the potato and the pesticide concentration in the soil solution. It is suggested that a negative correlation exists between the pesticide BCF and the soil sorption partition coefficient. The model was built based on the work of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103? 3108], in which an expression to calculate the diffusivity of persistent organic substances in potatoes is presented. The model consists in adding to the expression of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103?3108] the hypothesis that the pesticide degrades in the soil. The value of BCF suggests which pesticides should be monitored in potatoes.
650 $aAgrotóxico
653 $aModelagem matemática
700 1 $aKATAGUIRI, K.
773 $tChemosphere$gv. 73, p.1247-1252, 2008.
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Embrapa Meio Ambiente (CNPMA) |
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