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Registro Completo |
Biblioteca(s): |
Embrapa Meio Ambiente. |
Data corrente: |
10/01/2019 |
Data da última atualização: |
30/01/2019 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
SALAZAR, D. U.; DEMATTÊ, J. A. M.; VICENTE, L. E.; GUIMARÃES, C. C.; SOUZA, A. B. de; INFORSATO, L.; CARVALHO, H. W. L. de. |
Afiliação: |
Diego Fernando Urbina Salazar, Department of Soil Science/ESALQ/USP; José A. M. Demattê, Department of Soil Science/ESALQ/USP; LUIZ EDUARDO VICENTE, CNPMA; Clecia C. Guimarães, Department of Soil Science/ESALQ/USP; Arnaldo Barros de Souza, Department of Soil Science/ESALQ/USP; Leonardo Inforsato, CENA/USP; Hudson Wallace Pereira de Carvalho, CENA/USP. |
Título: |
Spectral range (FRX-VIS-NIR-SWIR-MIR) interaction on the organic matter prediction. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. Trabalho 392. |
Idioma: |
Português |
Conteúdo: |
Organic matter (OM) is an important indicator of soil quality and, therefore, must be quantified quickly and efficiently. Besides traditional methods, and countless studies with sensors have been advanced, but few integratively. This work aimed to develop models for OM content prediction using the FRX-VIS-NIR-SWIR-MIR regions separately and together. A total of 22 soil samples were collected in the state of São Paulo, Brazil (80-100 cm). Each sample was oven dried at 45 ° C for 48 hours, milled and sieved to a diameter of 0.150 mm and had a series of 8 treatments, considering the addition of humified organic material (MOH) in different amounts (0, 5, 10, 15, 20, 30, 40, 50 g). Afterwards, the treated samples were read in the sensors FIELDSPEC-PRO (VISNIRSWIR), ALPHA FTIR (MIR), and portable FRX for the extraction of the spectral responses. For the creation of the best model by Partial least squares regression (PLSR), 70% of the samples were used for calibration and 30% for validation and different preprocessing techniques were used: transformation of the reflectance data for absorbance, smoothing, first derivative Savitzky-Golay (SGD), standard normal variation (SNV) and multiplicative signal correction (MSC). The spectral data were tested separately and together using the absorbance transformation as a fixed preprocessing to which other was added. The calibration results for all models presented R² greater than 0.8 for the best preprocessing, which varies according to the spectral region analyzed. The best validation occurred for the preprocessed model with only absorbance and smoothing using the VIS-NIR-SIWIR-MIR spectral regions and presented values of R², RMSE and RPIQ equal to 0.8, 6.8 and 4.55, respectively. When using all the regions (RX-VIS-NIR-SWIR-MIR) simultaneously, validation values similar to those cited above (R² = 0.8, RMSE = 6.96 and RPIQ = 4.45)were obtained, indicating that the X-ray region does not influence the improvement of the prediction of OM. Models created only with a the spectral x-ray region presented the worst validation values. OM considerably influences on the spectral response from visible to medium infrared regions and, in this manner, they can be used for more accurate prediction of its values. MenosOrganic matter (OM) is an important indicator of soil quality and, therefore, must be quantified quickly and efficiently. Besides traditional methods, and countless studies with sensors have been advanced, but few integratively. This work aimed to develop models for OM content prediction using the FRX-VIS-NIR-SWIR-MIR regions separately and together. A total of 22 soil samples were collected in the state of São Paulo, Brazil (80-100 cm). Each sample was oven dried at 45 ° C for 48 hours, milled and sieved to a diameter of 0.150 mm and had a series of 8 treatments, considering the addition of humified organic material (MOH) in different amounts (0, 5, 10, 15, 20, 30, 40, 50 g). Afterwards, the treated samples were read in the sensors FIELDSPEC-PRO (VISNIRSWIR), ALPHA FTIR (MIR), and portable FRX for the extraction of the spectral responses. For the creation of the best model by Partial least squares regression (PLSR), 70% of the samples were used for calibration and 30% for validation and different preprocessing techniques were used: transformation of the reflectance data for absorbance, smoothing, first derivative Savitzky-Golay (SGD), standard normal variation (SNV) and multiplicative signal correction (MSC). The spectral data were tested separately and together using the absorbance transformation as a fixed preprocessing to which other was added. The calibration results for all models presented R² greater than 0.8 for the best preprocessing, which varies according to the s... Mostrar Tudo |
Palavras-Chave: |
Soil sensing; Spectral library. |
Thesaurus Nal: |
Environment; Organic matter; Spectroscopy. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/190317/1/RA-VicenteLE-21WCSS-2018-Trabalho-392.pdf
|
Marc: |
LEADER 03087nam a2200241 a 4500 001 2103530 005 2019-01-30 008 2018 bl uuuu u00u1 u #d 100 1 $aSALAZAR, D. U. 245 $aSpectral range (FRX-VIS-NIR-SWIR-MIR) interaction on the organic matter prediction.$h[electronic resource] 260 $aIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. Trabalho 392.$c2018 520 $aOrganic matter (OM) is an important indicator of soil quality and, therefore, must be quantified quickly and efficiently. Besides traditional methods, and countless studies with sensors have been advanced, but few integratively. This work aimed to develop models for OM content prediction using the FRX-VIS-NIR-SWIR-MIR regions separately and together. A total of 22 soil samples were collected in the state of São Paulo, Brazil (80-100 cm). Each sample was oven dried at 45 ° C for 48 hours, milled and sieved to a diameter of 0.150 mm and had a series of 8 treatments, considering the addition of humified organic material (MOH) in different amounts (0, 5, 10, 15, 20, 30, 40, 50 g). Afterwards, the treated samples were read in the sensors FIELDSPEC-PRO (VISNIRSWIR), ALPHA FTIR (MIR), and portable FRX for the extraction of the spectral responses. For the creation of the best model by Partial least squares regression (PLSR), 70% of the samples were used for calibration and 30% for validation and different preprocessing techniques were used: transformation of the reflectance data for absorbance, smoothing, first derivative Savitzky-Golay (SGD), standard normal variation (SNV) and multiplicative signal correction (MSC). The spectral data were tested separately and together using the absorbance transformation as a fixed preprocessing to which other was added. The calibration results for all models presented R² greater than 0.8 for the best preprocessing, which varies according to the spectral region analyzed. The best validation occurred for the preprocessed model with only absorbance and smoothing using the VIS-NIR-SIWIR-MIR spectral regions and presented values of R², RMSE and RPIQ equal to 0.8, 6.8 and 4.55, respectively. When using all the regions (RX-VIS-NIR-SWIR-MIR) simultaneously, validation values similar to those cited above (R² = 0.8, RMSE = 6.96 and RPIQ = 4.45)were obtained, indicating that the X-ray region does not influence the improvement of the prediction of OM. Models created only with a the spectral x-ray region presented the worst validation values. OM considerably influences on the spectral response from visible to medium infrared regions and, in this manner, they can be used for more accurate prediction of its values. 650 $aEnvironment 650 $aOrganic matter 650 $aSpectroscopy 653 $aSoil sensing 653 $aSpectral library 700 1 $aDEMATTÊ, J. A. M. 700 1 $aVICENTE, L. E. 700 1 $aGUIMARÃES, C. C. 700 1 $aSOUZA, A. B. de 700 1 $aINFORSATO, L. 700 1 $aCARVALHO, H. W. L. de
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Registro original: |
Embrapa Meio Ambiente (CNPMA) |
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Biblioteca(s): |
Embrapa Semiárido. |
Data corrente: |
19/12/2011 |
Data da última atualização: |
03/07/2023 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
COELHO, M. S.; SILVA, N. B. G.; SANTOS, A. P. B; SILVA, T. A.; VILARONGA, D. P.; KIILL, L. H. P.; COSTA, N. D.; PINTO, J. M. |
Afiliação: |
M. S. COELHO; N. B. G. SILVA; A. P. B. SANTOS; T. A. SILVA; D. P. VILARONGA; LUCIA HELENA PIEDADE KIILL, CPATSA; NIVALDO DUARTE COSTA, CPATSA; JOSE MARIA PINTO, CPATSA. |
Título: |
Evaluation of floral visitors of the melon crop at organic farming in the São Francisco Valley, Petrolina-PE, Brasil. |
Ano de publicação: |
2011 |
Fonte/Imprenta: |
In: CONGRESO INTERNACIONAL DE APICULTURA, 42., 2011, Buenos Aires. Posters... Buenos Aires: Consejo Federal de Inversiones, 2011. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Inglês |
Conteúdo: |
This study aimed to evaluate the floral visitors of melon plants in organic harming. |
Palavras-Chave: |
Adubação orgânica; Vale do São Francisco. |
Thesagro: |
Melão; Polinização. |
Thesaurus NAL: |
Melons; Pollination. |
Categoria do assunto: |
A Sistemas de Cultivo |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/50786/1/Kiiill-2011.pdf
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Marc: |
LEADER 00955nam a2200277 a 4500 001 1910240 005 2023-07-03 008 2011 bl uuuu u00u1 u #d 100 1 $aCOELHO, M. S. 245 $aEvaluation of floral visitors of the melon crop at organic farming in the São Francisco Valley, Petrolina-PE, Brasil. 260 $aIn: CONGRESO INTERNACIONAL DE APICULTURA, 42., 2011, Buenos Aires. Posters... Buenos Aires: Consejo Federal de Inversiones$c2011 300 $c1 CD-ROM. 520 $aThis study aimed to evaluate the floral visitors of melon plants in organic harming. 650 $aMelons 650 $aPollination 650 $aMelão 650 $aPolinização 653 $aAdubação orgânica 653 $aVale do São Francisco 700 1 $aSILVA, N. B. G. 700 1 $aSANTOS, A. P. B 700 1 $aSILVA, T. A. 700 1 $aVILARONGA, D. P. 700 1 $aKIILL, L. H. P. 700 1 $aCOSTA, N. D. 700 1 $aPINTO, J. M.
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