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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: |
20/12/2017 |
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Data da última atualização: |
12/02/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
TOMÀS, J. C.; FARIA, F. A.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; MEDEIROS, C. B. |
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Afiliação: |
JORDI CREUS TOMÀS, IC/Unicamp; FABIO AUGUSTO FARIA, Federal University of São Paulo, São José dos Campos; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; CLAUDIA BAUZER MEDEIROS, IC/Unicamp. |
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Título: |
SiRCub: a novel approach to recognize agricultural crops using supervised classification. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
International Journal of Agricultural and Environmental Information Systems, v. 8, n. 4, p. 20-36, Oct./Dec. 2017. |
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DOI: |
10.4018/IJAEIS.2017100102 |
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Idioma: |
Inglês |
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Notas: |
Publicado também em: INFORMATION RESOURCES MANAGEMENT ASSOCIATION (Ed.). Environmental information systems: concepts, methodologies, tools, and applications. Hershey: IGI Global, 2019. v. II, chap. 50, p. 1129-1147. DOI: 10.4018/978-1-5225-7033-2.ch050. |
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Conteúdo: |
This paper presents a new approach to deal with agricultural crop recognition using SVM (Support Vector Machine), applied to time series of NDVI images. The presented method can be divided into two steps. First, the Timesat software package is used to extract a set of crop features from the NDVI time series. These features serve as descriptors that characterize each NDVI vegetation curve, i.e., the period comprised between sowing and harvesting dates. Then, it is used an SVM to learn the patterns that define each type of crop, and create a crop model that allows classifying new series. The authors present a set of experiments that show the effectiveness of this technique. They evaluated their algorithm with a collection of more than 3000 time series from the Brazilian State of Mato Grosso spanning 4 years (2009-2013). Such time series were annotated in the field by specialists from Embrapa (Brazilian Agricultural Research Corporation). This methodology is generic, and can be adapted to distinct regions and crop profiles. |
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Palavras-Chave: |
Aprendizado de máquina; Crop classification; Enhanced Vegetation Index; Índice de vegetação; LULC; Machine Learning; Séries temporais; SIRCub; Support Vector Machine. |
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Thesagro: |
Sensoriamento remoto; Uso da terra. |
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Thesaurus Nal: |
Artificial intelligence; Land cover; Land use; normalized difference vegetation index; Remote sensing; Time series analysis; Vegetation index. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02556naa a2200409 a 4500
001 2082972
005 2020-02-12
008 2017 bl uuuu u00u1 u #d
024 7 $a10.4018/IJAEIS.2017100102$2DOI
100 1 $aTOMÀS, J. C.
245 $aSiRCub$ba novel approach to recognize agricultural crops using supervised classification.$h[electronic resource]
260 $c2017
500 $aPublicado também em: INFORMATION RESOURCES MANAGEMENT ASSOCIATION (Ed.). Environmental information systems: concepts, methodologies, tools, and applications. Hershey: IGI Global, 2019. v. II, chap. 50, p. 1129-1147. DOI: 10.4018/978-1-5225-7033-2.ch050.
520 $aThis paper presents a new approach to deal with agricultural crop recognition using SVM (Support Vector Machine), applied to time series of NDVI images. The presented method can be divided into two steps. First, the Timesat software package is used to extract a set of crop features from the NDVI time series. These features serve as descriptors that characterize each NDVI vegetation curve, i.e., the period comprised between sowing and harvesting dates. Then, it is used an SVM to learn the patterns that define each type of crop, and create a crop model that allows classifying new series. The authors present a set of experiments that show the effectiveness of this technique. They evaluated their algorithm with a collection of more than 3000 time series from the Brazilian State of Mato Grosso spanning 4 years (2009-2013). Such time series were annotated in the field by specialists from Embrapa (Brazilian Agricultural Research Corporation). This methodology is generic, and can be adapted to distinct regions and crop profiles.
650 $aArtificial intelligence
650 $aLand cover
650 $aLand use
650 $anormalized difference vegetation index
650 $aRemote sensing
650 $aTime series analysis
650 $aVegetation index
650 $aSensoriamento remoto
650 $aUso da terra
653 $aAprendizado de máquina
653 $aCrop classification
653 $aEnhanced Vegetation Index
653 $aÍndice de vegetação
653 $aLULC
653 $aMachine Learning
653 $aSéries temporais
653 $aSIRCub
653 $aSupport Vector Machine
700 1 $aFARIA, F. A.
700 1 $aESQUERDO, J. C. D. M.
700 1 $aCOUTINHO, A. C.
700 1 $aMEDEIROS, C. B.
773 $tInternational Journal of Agricultural and Environmental Information Systems$gv. 8, n. 4, p. 20-36, Oct./Dec. 2017.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
16/08/2021 |
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Data da última atualização: |
16/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
PEREZ, V. K. C.; COSTA, G. M. da; GUIMARÃES, A. S.; HEINEMANN, M. B.; LAGE, A. P.; DORNELES, E. M. S. |
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Afiliação: |
VERÓNICA KAREN CASTRO PÉREZ, Universidade Federal de Lavras; GERALDO MÁRCIO DA COSTA, Universidade Federal de Lavras; ALESSANDRO DE SA GUIMARAES, CNPGL; MARCOS BRYAN HEINEMANN, Universidade de São Paulo; ANDREY PEREIRA LAGE, Universidade Federal de Minas Gerais; ELAINE MARIA SELES DORNELES, Universidade Federal de Lavras. |
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Título: |
Relationship between virulence factors and antimicrobial resistance in Staphylococcus aureus from bovine mastitis. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Journal of Global Antimicrobial Resistance, v. 22, p. 792-802, 2020. |
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DOI: |
http://doi.org/10.1016/j.jgar.2020.06.010 |
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Idioma: |
Inglês |
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Conteúdo: |
Objectives: This review summarizes the literature on the role of virulence and antimicrobial resistance genes of Staphylococcus aureus in bovine mastitis, focusing on the association between these characteristics and their implications for public and animal health. Conclusions: There is the possibility of antimicrobial resistance gene exchange among different bacteria, which is of serious concern in livestock husbandry, as well as in the treatment of human staphylococcal infections. |
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Palavras-Chave: |
Infecção intramamária; Mastite; Virulência. |
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Thesagro: |
Bovino; Gado; Staphylococcus Aureus. |
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Thesaurus NAL: |
Cattle; Virulence. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 01367naa a2200289 a 4500
001 2133616
005 2021-08-16
008 2020 bl uuuu u00u1 u #d
024 7 $ahttp://doi.org/10.1016/j.jgar.2020.06.010$2DOI
100 1 $aPEREZ, V. K. C.
245 $aRelationship between virulence factors and antimicrobial resistance in Staphylococcus aureus from bovine mastitis.$h[electronic resource]
260 $c2020
520 $aObjectives: This review summarizes the literature on the role of virulence and antimicrobial resistance genes of Staphylococcus aureus in bovine mastitis, focusing on the association between these characteristics and their implications for public and animal health. Conclusions: There is the possibility of antimicrobial resistance gene exchange among different bacteria, which is of serious concern in livestock husbandry, as well as in the treatment of human staphylococcal infections.
650 $aCattle
650 $aVirulence
650 $aBovino
650 $aGado
650 $aStaphylococcus Aureus
653 $aInfecção intramamária
653 $aMastite
653 $aVirulência
700 1 $aCOSTA, G. M. da
700 1 $aGUIMARÃES, A. S.
700 1 $aHEINEMANN, M. B.
700 1 $aLAGE, A. P.
700 1 $aDORNELES, E. M. S.
773 $tJournal of Global Antimicrobial Resistance$gv. 22, p. 792-802, 2020.
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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