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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
07/07/2017 |
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Data da última atualização: |
16/11/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MORAS FILHO, L. O.; FIGUEIREDO, E. O.; ISAAC JÚNIOR, M. A.; BARROS, V. C. C. de; HOTT, M. C.; BORGES, L. A. C. |
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Afiliação: |
Luiz Otávio Moras Filho, Universidade Federal de Lavras (Ufla); EVANDRO ORFANO FIGUEIREDO, CPAF-Acre; Marcos Antônio Isaac Júnior, Universidade Federal de Lavras (Ufla); Vanessa Cabral Costa de Barros, Universidade Federal de Lavras (Ufla); Marcos Cicarini Hott, Universidade Federal de Lavras (Ufla); Luís Antônio Coimbra Borges, Universidade Federal de Lavras (Ufla). |
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Título: |
Classificador de máxima verossimilhança aplicado à identificação de espécies nativas na Floresta Amazônica. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. |
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Páginas: |
6 p. |
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ISBN: |
978-85-11-00088-1 |
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Idioma: |
Português |
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Conteúdo: |
Among a variety of digital classification methods based on remote sensing images, the Maximum Likelihood (ML) is widely used in environmental studies, mainly for land cover and vegetation analysis. This study aimed to evaluate the effectiveness of supervised classification by ML technique in a forest management area of dense ombrophilous forest, using one RapidEye image. With this purpose, it was conducted the census of species over 30 cm in diameter at breast height and calculated the Cover Value Index (CVI), and selected the 20 species with the highest CVI as a parameter for classification in a Geographic Information System. 13 of the 20 species selected in the study area were not identified by the classification method, and among the seven identified species, two were underestimated and the others were overestimated. Both the maximum likelihood technique and the spatial resolution of the image used were not suitable for supervised classification of native vegetation, with Kappa index of 0.05 and global accuracy of 5.53%. Studies using spectral characterization in leaf level supported by higher or hyper spectral and spatial resolution images are recommended to increase the accuracy of classification. |
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Palavras-Chave: |
Acre; Amazonia Occidental; Amazônia Ocidental; Análisis estadístico; Bosques tropicales; Especies nativas; Estimación; Identificación de plantas; Manejo florestal; Máxima verossimilhança; Maximum Likelihood; Método de classificação digital; Rio Branco (AC); Sistemas de información geográfica; Teledetección; Western Amazon. |
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Thesagro: |
Análise estatística; Espécie nativa; Estimativa; Floresta tropical; Identificação; Método estatístico; Sensoriamento remoto; Sistema de informação geográfica. |
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Thesaurus Nal: |
Estimation; Geographic information systems; Indigenous species; Plant identification; Remote sensing; Statistical analysis; Tropical forests. |
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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/161507/1/26344.pdf
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Marc: |
LEADER 02999nam a2200565 a 4500
001 2072220
005 2023-11-16
008 2017 bl uuuu u00u1 u #d
020 $a978-85-11-00088-1
100 1 $aMORAS FILHO, L. O.
245 $aClassificador de máxima verossimilhança aplicado à identificação de espécies nativas na Floresta Amazônica.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe$c2017
300 $a6 p.
520 $aAmong a variety of digital classification methods based on remote sensing images, the Maximum Likelihood (ML) is widely used in environmental studies, mainly for land cover and vegetation analysis. This study aimed to evaluate the effectiveness of supervised classification by ML technique in a forest management area of dense ombrophilous forest, using one RapidEye image. With this purpose, it was conducted the census of species over 30 cm in diameter at breast height and calculated the Cover Value Index (CVI), and selected the 20 species with the highest CVI as a parameter for classification in a Geographic Information System. 13 of the 20 species selected in the study area were not identified by the classification method, and among the seven identified species, two were underestimated and the others were overestimated. Both the maximum likelihood technique and the spatial resolution of the image used were not suitable for supervised classification of native vegetation, with Kappa index of 0.05 and global accuracy of 5.53%. Studies using spectral characterization in leaf level supported by higher or hyper spectral and spatial resolution images are recommended to increase the accuracy of classification.
650 $aEstimation
650 $aGeographic information systems
650 $aIndigenous species
650 $aPlant identification
650 $aRemote sensing
650 $aStatistical analysis
650 $aTropical forests
650 $aAnálise estatística
650 $aEspécie nativa
650 $aEstimativa
650 $aFloresta tropical
650 $aIdentificação
650 $aMétodo estatístico
650 $aSensoriamento remoto
650 $aSistema de informação geográfica
653 $aAcre
653 $aAmazonia Occidental
653 $aAmazônia Ocidental
653 $aAnálisis estadístico
653 $aBosques tropicales
653 $aEspecies nativas
653 $aEstimación
653 $aIdentificación de plantas
653 $aManejo florestal
653 $aMáxima verossimilhança
653 $aMaximum Likelihood
653 $aMétodo de classificação digital
653 $aRio Branco (AC)
653 $aSistemas de información geográfica
653 $aTeledetección
653 $aWestern Amazon
700 1 $aFIGUEIREDO, E. O.
700 1 $aISAAC JÚNIOR, M. A.
700 1 $aBARROS, V. C. C. de
700 1 $aHOTT, M. C.
700 1 $aBORGES, L. A. C.
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Registro original: |
Embrapa Acre (CPAF-AC) |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
26/08/2022 |
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Data da última atualização: |
25/04/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
LEÃO, P. C. de S.; CUNHA, M. A. C. da; SOUZA, E. R. de. |
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Afiliação: |
PATRICIA COELHO DE SOUZA LEÃO, CPATSA; MARCOS ANDREI CUSTÓDIO DA CUNHA, UNIVERSIDADE DE PERNAMBUCO; EDIMARA RIBEIRO DE SOUZA, UNIVERSIDADE DE PERNAMBUCO. |
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Título: |
Performance of BRS Magna vines grown under different training systems, rootstocks and production cycles. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Scientia Agricola, v. 80, e20220018, 2023. |
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ISSN: |
1678-992X |
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DOI: |
https://doi.org/10.1590/1678-992X-2022-0018 |
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Idioma: |
Inglês |
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Conteúdo: |
Over the past decade, the business of producing juice from grapes (Vitis labrusca L. and hybrids) has been expanding in response to increasing consumption encouraged by campaigns promoting the benefits grape juice can have on health. This study aimed to determine the effect of the production cycle, vine training system, and rootstock on the yield and physical and physical-chemical characteristics of ?BRS Magna? grapes grown in the Vale do Submédio São Francisco in the northeastern region of Brazil. The study was conducted in Petrolina, Pernambuco, over eight production cycles (2017 to 2020). The grapevines were trained in three vine training trellis systems: espalier, lyre, and pergola; and grafted onto two rootstocks: IAC 572 and IAC 766. The production cycle, training system, and rootstocks affected the yield components, vigor, and physical characteristics of the BRS Magna grapes. The combination of the pergola training system and rootstock IAC 766 stood out from the others, providing mean yields estimated at 26 t ha?1 per production cycle. The soluble solids content (SS), titratable acidity (TA), and SS TA?1 ratio were affected neither by the training system nor the rootstock, and higher values for SS and lower values for TA were obtained in the first, second, fourth and eighth production cycles. Thus, the pergola training system and rootstock IAC 766 are recommended for promoting yield gains in the ?BRS Magna? grape in the Vale do Submédio São Francisco. |
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Palavras-Chave: |
BRS Magna; Enxerto IAC 766; Sistema de condução; Viticultura tropical. |
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Thesagro: |
Porta Enxerto; Produtividade; Suco; Suco de Fruta; Uva; Variedade; Viticultura; Vitis Labrusca. |
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Thesaurus NAL: |
Crop management; Grape juice; Grapes; Tropical agriculture. |
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Categoria do assunto: |
A Sistemas de Cultivo |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1145771/1/BRS-Magna-vines-grown.Scientia-Agricola.pdf
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Marc: |
LEADER 02511naa a2200361 a 4500
001 2145771
005 2024-04-25
008 2023 bl uuuu u00u1 u #d
022 $a1678-992X
024 7 $ahttps://doi.org/10.1590/1678-992X-2022-0018$2DOI
100 1 $aLEÃO, P. C. de S.
245 $aPerformance of BRS Magna vines grown under different training systems, rootstocks and production cycles.$h[electronic resource]
260 $c2023
520 $aOver the past decade, the business of producing juice from grapes (Vitis labrusca L. and hybrids) has been expanding in response to increasing consumption encouraged by campaigns promoting the benefits grape juice can have on health. This study aimed to determine the effect of the production cycle, vine training system, and rootstock on the yield and physical and physical-chemical characteristics of ?BRS Magna? grapes grown in the Vale do Submédio São Francisco in the northeastern region of Brazil. The study was conducted in Petrolina, Pernambuco, over eight production cycles (2017 to 2020). The grapevines were trained in three vine training trellis systems: espalier, lyre, and pergola; and grafted onto two rootstocks: IAC 572 and IAC 766. The production cycle, training system, and rootstocks affected the yield components, vigor, and physical characteristics of the BRS Magna grapes. The combination of the pergola training system and rootstock IAC 766 stood out from the others, providing mean yields estimated at 26 t ha?1 per production cycle. The soluble solids content (SS), titratable acidity (TA), and SS TA?1 ratio were affected neither by the training system nor the rootstock, and higher values for SS and lower values for TA were obtained in the first, second, fourth and eighth production cycles. Thus, the pergola training system and rootstock IAC 766 are recommended for promoting yield gains in the ?BRS Magna? grape in the Vale do Submédio São Francisco.
650 $aCrop management
650 $aGrape juice
650 $aGrapes
650 $aTropical agriculture
650 $aPorta Enxerto
650 $aProdutividade
650 $aSuco
650 $aSuco de Fruta
650 $aUva
650 $aVariedade
650 $aViticultura
650 $aVitis Labrusca
653 $aBRS Magna
653 $aEnxerto IAC 766
653 $aSistema de condução
653 $aViticultura tropical
700 1 $aCUNHA, M. A. C. da
700 1 $aSOUZA, E. R. de
773 $tScientia Agricola$gv. 80, e20220018, 2023.
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