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 | Acesso ao texto completo restrito à biblioteca da Epagri-Sede. Para informações adicionais entre em contato com biblio@epagri.sc.gov.br. |
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
01/10/2004 |
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Data da última atualização: |
01/10/2004 |
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Autoria: |
MACHADO, E. C.; PEREIRA, M. L.; AMANCIO, G. C.; CARVALHO, E. P. de. |
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Título: |
Identificacao de perigos e pontos criticos de controle e avaliacao das praticas de fabricacao de uma industria mineira de pao de queijo. |
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Ano de publicação: |
2004 |
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Fonte/Imprenta: |
Revista Higiene Alimentar, Sao Paulo, v. 18, n. 121, p. 100-103, jul. 2004. |
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Idioma: |
Português |
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Palavras-Chave: |
APPCC; Armazenagem; Manipulacao; Pao de queijo; Situacao de limpeza. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00661naa a2200205 a 4500
001 1032656
005 2004-10-01
008 2004 bl uuuu u00u1 u #d
100 1 $aMACHADO, E. C.
245 $aIdentificacao de perigos e pontos criticos de controle e avaliacao das praticas de fabricacao de uma industria mineira de pao de queijo.
260 $c2004
653 $aAPPCC
653 $aArmazenagem
653 $aManipulacao
653 $aPao de queijo
653 $aSituacao de limpeza
700 1 $aPEREIRA, M. L.
700 1 $aAMANCIO, G. C.
700 1 $aCARVALHO, E. P. de.
773 $tRevista Higiene Alimentar, Sao Paulo$gv. 18, n. 121, p. 100-103, jul. 2004.
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Epagri-Sede (Epagri-Sede) |
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
30/06/2016 |
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Data da última atualização: |
30/06/2016 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
SILVA, E. B.; CATEN, A. T.; DALMOLIN, R. S. D.; DOTTO, A. C.; SILVA, W. C.; GIASSON, E. |
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Título: |
Estimating Soil Texture from a Limited Region of the Visible/Near-Infrared Spectrum. |
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Edição: |
1. Ed. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: Hartemink, A. E.; Minasny, B. Progress in Soil Science: Digital Soil Morphometrics. 1. ed. Suiça: Springer International Publishing, 2016. p. 73-87. |
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Idioma: |
Inglês |
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Conteúdo: |
Soil particle size is an attribute of fundamental importance when defining soil horizons. Proximal soil sensors can facilitate the acquisition of a larger amount of soil data using a faster and less-laborious technique. Thus, the objective of this study is to evaluate the capacity of a limited spectral acquisition region (325-1075 nm) for estimating soil texture. Soil samples were collected in the southwest part of Marombas river watershed located near the center of Santa Catarina state, south of Brazil. A total of 42 soil profiles were sampled according to the Globalsoilmap specification. A data set of 166 samples was used for model calibration and a different data set, 71 samples, was used for model validation. Diffuse reflectance spectroscopy of sieved samples (2 mm) was collected with a spectrometer FieldSpecHandHeld II (ASD Inc.). Savitzky-Golay second derivatives were calculated and used in partial least-squares regression modeling. Calibration and validation data setshowed statistically similar mean and variance. The root mean square error of prediction for sand, silt and clay content are 5.47, 5.18 and 5.39 g 100g-1, respectively. The R² for validation are 0.30, 0.59 and 0.69 for the same attributes. Partitioning the model by depth did not improve the predictions significantly. The results show that estimating soil texture from a limited spectral region is promising and can contribute towards the development of cheaper spectrometers or infrared cameras that can be used for digital soil morphometrics. MenosSoil particle size is an attribute of fundamental importance when defining soil horizons. Proximal soil sensors can facilitate the acquisition of a larger amount of soil data using a faster and less-laborious technique. Thus, the objective of this study is to evaluate the capacity of a limited spectral acquisition region (325-1075 nm) for estimating soil texture. Soil samples were collected in the southwest part of Marombas river watershed located near the center of Santa Catarina state, south of Brazil. A total of 42 soil profiles were sampled according to the Globalsoilmap specification. A data set of 166 samples was used for model calibration and a different data set, 71 samples, was used for model validation. Diffuse reflectance spectroscopy of sieved samples (2 mm) was collected with a spectrometer FieldSpecHandHeld II (ASD Inc.). Savitzky-Golay second derivatives were calculated and used in partial least-squares regression modeling. Calibration and validation data setshowed statistically similar mean and variance. The root mean square error of prediction for sand, silt and clay content are 5.47, 5.18 and 5.39 g 100g-1, respectively. The R² for validation are 0.30, 0.59 and 0.69 for the same attributes. Partitioning the model by depth did not improve the predictions significantly. The results show that estimating soil texture from a limited spectral region is promising and can contribute towards the development of cheaper spectrometers or infrared cameras that can be us... Mostrar Tudo |
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Palavras-Chave: |
diffuse reflectance spectroscopy; digital soil morphometrics; proximal soil sensing; soil attribute; soil reflectance. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02384naa a2200253 a 4500
001 1125212
005 2016-06-30
008 2016 bl uuuu u00u1 u #d
100 1 $aSILVA, E. B.
245 $aEstimating Soil Texture from a Limited Region of the Visible/Near-Infrared Spectrum.$h[electronic resource]
250 $a1. Ed.
260 $c2016
520 $aSoil particle size is an attribute of fundamental importance when defining soil horizons. Proximal soil sensors can facilitate the acquisition of a larger amount of soil data using a faster and less-laborious technique. Thus, the objective of this study is to evaluate the capacity of a limited spectral acquisition region (325-1075 nm) for estimating soil texture. Soil samples were collected in the southwest part of Marombas river watershed located near the center of Santa Catarina state, south of Brazil. A total of 42 soil profiles were sampled according to the Globalsoilmap specification. A data set of 166 samples was used for model calibration and a different data set, 71 samples, was used for model validation. Diffuse reflectance spectroscopy of sieved samples (2 mm) was collected with a spectrometer FieldSpecHandHeld II (ASD Inc.). Savitzky-Golay second derivatives were calculated and used in partial least-squares regression modeling. Calibration and validation data setshowed statistically similar mean and variance. The root mean square error of prediction for sand, silt and clay content are 5.47, 5.18 and 5.39 g 100g-1, respectively. The R² for validation are 0.30, 0.59 and 0.69 for the same attributes. Partitioning the model by depth did not improve the predictions significantly. The results show that estimating soil texture from a limited spectral region is promising and can contribute towards the development of cheaper spectrometers or infrared cameras that can be used for digital soil morphometrics.
653 $adiffuse reflectance spectroscopy
653 $adigital soil morphometrics
653 $aproximal soil sensing
653 $asoil attribute
653 $asoil reflectance
700 1 $aCATEN, A. T.
700 1 $aDALMOLIN, R. S. D.
700 1 $aDOTTO, A. C.
700 1 $aSILVA, W. C.
700 1 $aGIASSON, E.
773 $tIn: Hartemink, A. E.; Minasny, B. Progress in Soil Science: Digital Soil Morphometrics. 1. ed. Suiça: Springer International Publishing, 2016. p. 73-87.
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