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| 1. |  | LEMOS, O. L.; REBOUCAS, T. N. H.; SAO JOSE, A. R.; VILA, M. T. R.; SILVA, K. S.; SILVA, D. S.; BARRETO, A. P. P.; BOMFIM, M. P. Conservacao do pimentao 'Magali R' em duas condicoes de armazenamento associada a atmosfera modificada. Magistra, Cruz das Almas, v.20, n.1, p.06-15, jan./mar. 2008.| Biblioteca(s): Epagri-Sede. |
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| 2. | | SILVA, K. S.; REBOUÇAS, T. N. H.; LEMOS, O. L.; BOMFIM, M. P.; BOMFIM, A. A.; ESQUIVEL, G. L.; BARRETO, A. P. P.; SÃO JOSÉ, A. R.; DIAS, N. O.; TAVARES, G. M. Patogenicidade causada pelo fungo Colletotrichum gloeosporioides (Penz) em diferentes espécies frutíferas. Revista Brasileira Fruticultura, Jaboticabal, SP, v. 28, n. 1, p.131-133, abril, 2006.| Biblioteca(s): Epagri-Sede. |
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| Registros recuperados : 2 | |
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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
16/01/2019 |
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Data da última atualização: |
16/01/2019 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
SILVA, E. B.; GIASSON, E.; CATEN, A. T.; DOTTO, A. C.; DEMATTÊ, J. A. M.; VEIGA, M. |
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Título: |
Building a spectral library for estimating soil texture in the Santa Catarina State, Brazil. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Abstracts... Viçosa: Sociedade Brasileira de Ciência do Solo, 2018. |
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Idioma: |
Inglês |
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Conteúdo: |
Soil properties characterization is required to inform and lead decision-makers into action. To
achieve this goal, it is necessary to develop effective methods to soil measure and monitoring.
Several soil databases have been used to build large spectral library for improving and facilitating
the use of VIS-NIR-SWIR spectroscopy approach in a collaborative way. In this study, the
performance of four multivariate statistical techniques (e.g., Partial least-squares - PLS, Support
vector machine - SVM, Random forest - RF, Gaussian process regression - GPR) were compared to
evaluated their ability to predict sand, silt and clay content (%) using a regional soil spectral library.
A total of 1534 observations were collected throughout the State of Santa Catarina (SC). These
observations were used as dataset for the calibration (n = 1151) and validation (n = 383)
procedures. Soil spectra was obtained using the FieldSpec 3 (ASD) sensor in the VIS-NIR-SWIR
range. The spectra were subjected to seven preprocessing techniques including raw spectra (RAW),
first derivative (FD-SG), second derivative (SD-SG), continuum removed reflectance (CR),
detrending (DT), normalization by range (NBR) and multiplicative scatter correction (MSC). The
ranges of sand (1.0 to 99.0%), silt (0.0 to 83.0%) and clay (0.0 to 77.0 %) content are wide and
their coefficients of variation are large, indicating great variability of samples as a result of different
soil-forming factors. |
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Palavras-Chave: |
chemometrics techniques; reflectance spectroscopy; Sand; silt and Clay content. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02225naa a2200229 a 4500
001 1128237
005 2019-01-16
008 2018 bl uuuu u00u1 u #d
100 1 $aSILVA, E. B.
245 $aBuilding a spectral library for estimating soil texture in the Santa Catarina State, Brazil.$h[electronic resource]
260 $c2018
520 $aSoil properties characterization is required to inform and lead decision-makers into action. To achieve this goal, it is necessary to develop effective methods to soil measure and monitoring. Several soil databases have been used to build large spectral library for improving and facilitating the use of VIS-NIR-SWIR spectroscopy approach in a collaborative way. In this study, the performance of four multivariate statistical techniques (e.g., Partial least-squares - PLS, Support vector machine - SVM, Random forest - RF, Gaussian process regression - GPR) were compared to evaluated their ability to predict sand, silt and clay content (%) using a regional soil spectral library. A total of 1534 observations were collected throughout the State of Santa Catarina (SC). These observations were used as dataset for the calibration (n = 1151) and validation (n = 383) procedures. Soil spectra was obtained using the FieldSpec 3 (ASD) sensor in the VIS-NIR-SWIR range. The spectra were subjected to seven preprocessing techniques including raw spectra (RAW), first derivative (FD-SG), second derivative (SD-SG), continuum removed reflectance (CR), detrending (DT), normalization by range (NBR) and multiplicative scatter correction (MSC). The ranges of sand (1.0 to 99.0%), silt (0.0 to 83.0%) and clay (0.0 to 77.0 %) content are wide and their coefficients of variation are large, indicating great variability of samples as a result of different soil-forming factors.
653 $achemometrics techniques
653 $areflectance spectroscopy
653 $aSand
653 $asilt and Clay content
700 1 $aGIASSON, E.
700 1 $aCATEN, A. T.
700 1 $aDOTTO, A. C.
700 1 $aDEMATTÊ, J. A. M.
700 1 $aVEIGA, M.
773 $tIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Abstracts... Viçosa: Sociedade Brasileira de Ciência do Solo, 2018.
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