| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Instrumentação. Para informações adicionais entre em contato com cnpdia.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Instrumentação. |
|
Data corrente: |
16/11/2021 |
|
Data da última atualização: |
09/06/2022 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
FURUYA, D. E. G.; MA, L.; PINHEIRO, M. M. F.; GOMES, F. D. G.; GONÇALVEZ, W. N.; MARCATO JUNIOR, J.; RODRIGUES, D. de C.; BLASSIOLI- MORAES, M. C.; MICHEREFF, M. F. F.; BORGES, M.; ALAUMANN, R. A.; FERREIRA, E. J.; OSCO, L. P.; RAMOS, A. P. M.; LI, J.; JORGE, L. A. de C. |
|
Afiliação: |
MARIA CAROLINA BLASSIOLI MORAES, Cenargen; MIGUEL BORGES, Cenargen; EDNALDO JOSE FERREIRA, CNPDIA; LUCIO ANDRE DE CASTRO JORGE, CNPDIA. |
|
Título: |
Prediction of insect-herbivory-damage and insect-type attack in maize plants using hyperspectral data. |
|
Ano de publicação: |
2021 |
|
Fonte/Imprenta: |
International Journal of Applied Earth Observation and Geoinformation, v. 105, 102608, 2021. |
|
Páginas: |
1 - 10 |
|
ISSN: |
0303-2434 |
|
DOI: |
https://doi.org/10.1016/j.jag.2021.102608 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Accurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consists of an original contribution to early differentiate the undamaged plant from the damaged one due to insect-attack, highlighting the most contributive wavelengths to map this occurrence. MenosAccurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consis... Mostrar Tudo |
|
Palavras-Chave: |
Proximal hyperspectral sensing; Random forest. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 02800naa a2200361 a 4500
001 2136152
005 2022-06-09
008 2021 bl uuuu u00u1 u #d
022 $a0303-2434
024 7 $ahttps://doi.org/10.1016/j.jag.2021.102608$2DOI
100 1 $aFURUYA, D. E. G.
245 $aPrediction of insect-herbivory-damage and insect-type attack in maize plants using hyperspectral data.$h[electronic resource]
260 $c2021
300 $a1 - 10
520 $aAccurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consists of an original contribution to early differentiate the undamaged plant from the damaged one due to insect-attack, highlighting the most contributive wavelengths to map this occurrence.
653 $aProximal hyperspectral sensing
653 $aRandom forest
700 1 $aMA, L.
700 1 $aPINHEIRO, M. M. F.
700 1 $aGOMES, F. D. G.
700 1 $aGONÇALVEZ, W. N.
700 1 $aMARCATO JUNIOR, J.
700 1 $aRODRIGUES, D. de C.
700 1 $aBLASSIOLI- MORAES, M. C.
700 1 $aMICHEREFF, M. F. F.
700 1 $aBORGES, M.
700 1 $aALAUMANN, R. A.
700 1 $aFERREIRA, E. J.
700 1 $aOSCO, L. P.
700 1 $aRAMOS, A. P. M.
700 1 $aLI, J.
700 1 $aJORGE, L. A. de C.
773 $tInternational Journal of Applied Earth Observation and Geoinformation$gv. 105, 102608, 2021.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Instrumentação (CNPDIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 5 | |
| 1. |  | ROSSI, T. C.; CAMARGO, L. S. de A.; FERNANDES, C. A. C.; VARAGO, F. C.; MIYAUCHI, T. M.; ROSSI, J. R.; GIOSO, M. M. Bovine oocyte transportation in environment with or without control gas atmosphere. Animal Reproduction, v. 10, n. 3, p. 547, Jul./Sept. 2013. Suplemento. Edição dos abstracts do 27º Annual Meeting of the Brazilian Embryo Technology Society, 2013, Praia do Forte, BA.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
|    |
| 2. | | VIANA, J. H. M.; MIYAUCHI, T. M.; MIYAUCHI, T. A.; OLIVEIRA, E. R.; GARCIA, J. A. D.; GIOSO, M. M.; FERNANDES, C. A. de C.; PALHÃO, M. P. Potencial para produção in vitro de embriões de doadoras bovinas das raças gir (Bos taurus indicus) e holandesa (Bos taurus taurus). In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE TECNOLOGIA DE EMBRIÕES, 25., 2011, Cumbuco. Anais... Jaboticabal: Sociedade Brasileira de Transferência de Embriões, 2011. p. 403.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
| |
| 3. | | FERNANDES, C. A. de C.; MIYAUCHI, T. M.; FIGUEIREDO, A. S. de; PALHÃO, M. P.; VARAGO, F. C.; NOGUEIRA, E. S. C.; NEVES, J. P.; MIYAUCHI, T. A. Hormonal protocols for in vitro production of zebu and taurine embryos. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 10, p. 813-817, out. 2014. Título em português: Protocolos hormonais para produção in vitro de embriões de zebuínos e taurinos.| Biblioteca(s): Embrapa Unidades Centrais. |
| |
| 4. | | ROSSI, T. C.; ROSSI, J.; MIYAUCHI, T. M.; FERNANDES, C. A. C.; CAMARGO, L. S. de A.; VIANA, J. H. M.; PALHÃO, M. P. In vitro embryo production after exposure of bovine oocytes to different transportation media and periods: preliminary results. In: ANNUAL CONFERENCE OF THE INTERNATIONAL EMBRYO TRANSFER SOCIETY, 2013, Hannover. Proceedings... Hannover: [s.n.], 2013.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
| |
| 5. | | MIYAUCHI, T. A.; SOUZA, E. D.; IGUMA, L. T.; RODRIGUES, A. C. F.; ARAÚJO, T. D.; QUINELATO, G. N.; MIYAUCHI, T. M.; CAMARGO, L. S. de A.; FERNANDES, C. A. C. Capacidade de desenvolvimento pré-implantacional de embriões bovinos partenogenéticos ou fecundados in vitro. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE TECNOLOGIA DE EMBRIÕES, 26., 2012, Foz do Iguaçu. Anais. Belo Horizonte: CBRA, 2012.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
| |
| Registros recuperados : 5 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
