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| 62. |  | GUIMARÃES, C. M.; YOKOYAMA, L. P.; BRESEGHELLO, F. Sistemas de produção de arroz de terras altas. In: REUNIÃO NACIONAL DE PESQUISA DE ARROZ, 6., 1998, Goiânia, GO. Perspectivas para a cultura do arroz nos ecossistemas de várzeas e terras altas: painel, conferências e mesas-redondas. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 1999. v. 2. p. 181-208. (Embrapa Arroz e Feijão. Documentos, 96).| Biblioteca(s): Embrapa Arroz e Feijão. |
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| Registros recuperados : 411 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
28/05/2020 |
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Data da última atualização: |
28/05/2020 |
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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: |
MORAIS, P. A. de O.; SOUZA, D. M. de; MADARI, B. E.; OLIVEIRA, A. E. de. |
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Afiliação: |
PEDRO AUGUSTO DE OLIVEIRA MORAIS, UFG; DIEGO MENDES DE SOUZA, CNPAF; BEATA EMOKE MADARI, CNPAF; ANSELMO ELCANA DE OLIVEIRA, UFG. |
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Título: |
A computer-assisted soil texture analysis using digitally scanned images. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Computers and Electronics in Agriculture, v. 174, 105435, July 2020. |
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ISSN: |
0168-1699 |
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DOI: |
https://doi.org/10.1016/j.compag.2020.105435 |
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Idioma: |
Inglês |
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Conteúdo: |
A computer-assisted soil texture analysis is presented using digitally scanned soil images of 177 soil samples collected from different regions of Brazil. Soil digital images were correlated to texture results determined by the standard pipette method using three multivariate methods: successive projections algorithm combined with multivariate linear regression (SPA-MLR), partial least-squares regression (PLSR), and least-squares support vector machine regression (LSSVMR). Sand and clay particle size were better estimated using LSSVMR presenting correlations above 90%. Following soil sample particle size content estimates, soil texture classes were also estimated achieving 90.6% accuracy. The proposed method using digital images is fast, cheap and has low environmental impact when compared to the standard method. |
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Thesagro: |
Textura do Solo. |
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Thesaurus NAL: |
Computer-assisted instruction; Digital images; Image analysis; Sand; Soil texture. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 2122735
005 2020-05-28
008 2020 bl uuuu u00u1 u #d
022 $a0168-1699
024 7 $ahttps://doi.org/10.1016/j.compag.2020.105435$2DOI
100 1 $aMORAIS, P. A. de O.
245 $aA computer-assisted soil texture analysis using digitally scanned images.$h[electronic resource]
260 $c2020
520 $aA computer-assisted soil texture analysis is presented using digitally scanned soil images of 177 soil samples collected from different regions of Brazil. Soil digital images were correlated to texture results determined by the standard pipette method using three multivariate methods: successive projections algorithm combined with multivariate linear regression (SPA-MLR), partial least-squares regression (PLSR), and least-squares support vector machine regression (LSSVMR). Sand and clay particle size were better estimated using LSSVMR presenting correlations above 90%. Following soil sample particle size content estimates, soil texture classes were also estimated achieving 90.6% accuracy. The proposed method using digital images is fast, cheap and has low environmental impact when compared to the standard method.
650 $aComputer-assisted instruction
650 $aDigital images
650 $aImage analysis
650 $aSand
650 $aSoil texture
650 $aTextura do Solo
700 1 $aSOUZA, D. M. de
700 1 $aMADARI, B. E.
700 1 $aOLIVEIRA, A. E. de
773 $tComputers and Electronics in Agriculture$gv. 174, 105435, July 2020.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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