The Experts below are selected from a list of 246 Experts worldwide ranked by ideXlab platform
Youssef Fouad - One of the best experts on this subject based on the ideXlab platform.
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in situ measurements of soil colour mineral composition and clay content by vis nir spectroscopy
Geoderma, 2009Co-Authors: R Viscarra A Rossel, Stephen R Cattle, A S Ortega, Youssef FouadAbstract:Proximal soil sensing (PSS) using portable visible-near infrared (vis-NIR: 400-2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell Book estimates, although the vis-NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis-NIR was effective, with good agreement between the results of this method and XRD analysis. The vis-NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by 'spiking' them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty.
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In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy
Geoderma, 2009Co-Authors: R.a. Viscarra Rossel, Stephen R Cattle, A. Ortega, Youssef FouadAbstract:Proximal soil sensing (PSS) using portable visible-near infrared (vis-NIR: 400-2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell Book estimates, although the vis-NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis-NIR was effective, with good agreement between the results of this method and XRD analysis. The vis-NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by 'spiking' them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty
Alexei A. Kamshilin - One of the best experts on this subject based on the ideXlab platform.
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Recovery of reflection spectra in a multispectral imaging system with light emitting diodes
Optics Express, 2010Co-Authors: Laure Fauch, Victor Teplov, Ervin Nippolainen, Alexei A. KamshilinAbstract:Performance of recently proposed multispectral imaging system for fast acquisition of two dimensional distribution of reflectance spectrum is experimentally studied. The system operation is based on a subspace vector model in which any reflectance spectrum is described in the compressed form as a linear combination of few spectral functions. A key element of the proposed system is a light source which includes a set of light-emitting diodes with different central wavelengths. The light source provides illumination of the object by fast-switchable sequences of spectral bands whose energy distributions are proportional to mutually orthogonal spectral functions (calculated in-advance). Object illumination is synchronized with a monochrome digital camera. The system allows us fast acquisition of reflectance spectra in a compressed form with high spatial resolution. A model of the system calibration by using standard white matte sample is proposed. Reconstruction of the reflectance spectrum from the compressed data collected after illumination of selected color samples from the Munsell Book by 7 mutually orthogonal spectral functions is demonstrated. Parameters of the system, which affect the accuracy of the spectrum reconstruction, are analyzed and discussed.
R Viscarra A Rossel - One of the best experts on this subject based on the ideXlab platform.
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in situ measurements of soil colour mineral composition and clay content by vis nir spectroscopy
Geoderma, 2009Co-Authors: R Viscarra A Rossel, Stephen R Cattle, A S Ortega, Youssef FouadAbstract:Proximal soil sensing (PSS) using portable visible-near infrared (vis-NIR: 400-2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell Book estimates, although the vis-NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis-NIR was effective, with good agreement between the results of this method and XRD analysis. The vis-NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by 'spiking' them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty.
Gaspar-oliveira, Carolina Maria - One of the best experts on this subject based on the ideXlab platform.
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Tetrazolium solution concentration and test staining period for castor bean seeds
Associação Brasileira de Tecnologia de Sementes (ABRATES), 2009Co-Authors: Gaspar-oliveira, Carolina Maria, Martins, Cibele Chalita [unesp], Nakagawa, João [unesp]Abstract:O objetivo do trabalho foi estudar a concentração da solução de tetrazólio e o período de coloração do teste para a avaliação do potencial fisiológico de sementes de mamoneira (Ricinus communis L.), padronizando a nomenclatura das cores observadas nas sementes após a coloração. Os tratamentos de concentração da solução de tetrazólio e períodos de coloração estudados foram: 0,075% e 0,1% por 120, 180 e 240 minutos, 0,2% por 60, 120 e 180 minutos, 0,5% por 60, 90 e 120 minutos e 1,0% por 30, 60 e 90 minutos. Os resultados foram comparados com os obtidos nos testes de germinação. A coloração das sementes após o teste de tetrazólio, em cada tratamento, foi avaliada mediante comparação com as fichas de cor do catálogo de Munsell, determinando-se a porcentagem de sementes observada em cada cor. O delineamento experimental foi o inteiramente casualizado e a comparação de médias realizada pelo teste de Tukey a 5% de probabilidade. Para avaliar o potencial fisiológico pelo teste de tetrazólio, as sementes de mamoneira devem ser imersas na solução de tetrazólio na concentração de 0,2% por 120 minutos, a 35ºC. Nesse tratamento, as sementes viáveis após a coloração na solução de tetrazólio apresentaram predominantemente as cores rosa e rosa-escuro em suas estruturas essenciais, portanto essas podem ser consideradas como as cores características para o teste de tetrazólio em sementes de mamoneira.The objective of this research was to study the tetrazolium solution concentration and staining period for the evaluation of the physiological quality of castor bean seeds (Ricinus communis L.) by the tetrazolium test, standardizing the nomenclature of the observed colors in seeds after staining. The treatments of tetrazolium solution concentration and staining period were: 0.075% and 0.1% for 120, 180 and 240 minutes, 0.2% for 60, 120 and 180 minutes, 0.5% for 60, 90 and 120 minutes and 1.0% for 30, 60 and 90 minutes. The results were compared to the germination test. The seed color after the tetrazolium test in each treatment was evaluated by comparing with the Munsell Book of color, and the percentage of seeds observed in each color was established. A randomized complete block design was used and the means were compared by the Tukey test at the 0.05 level of probability. To evaluate physiological quality by the tetrazolium test, castor bean seeds should be placed in tetrazolium solution at the concentration 0.2% for 120 minutes, at 35ºC, for staining development, and in this treatment, the viable seeds after the staining in tetrazolium solution showed predominantly the colors pink and dark pink in their essential structures. Thus these colors can be considered as the characteristics colors for the tetrazolium test in castor bean seeds
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Concentração da solução de tetrazólio e período de coloração do teste para sementes de mamoneira
Associação Brasileira de Tecnologia de Sementes (ABRATES), 2009Co-Authors: Gaspar-oliveira, Carolina Maria, Martins, Cibele Chalita, Nakagawa JoãoAbstract:O objetivo do trabalho foi estudar a concentração da solução de tetrazólio e o período de coloração do teste para a avaliação do potencial fisiológico de sementes de mamoneira (Ricinus communis L.), padronizando a nomenclatura das cores observadas nas sementes após a coloração. Os tratamentos de concentração da solução de tetrazólio e períodos de coloração estudados foram: 0,075% e 0,1% por 120, 180 e 240 minutos, 0,2% por 60, 120 e 180 minutos, 0,5% por 60, 90 e 120 minutos e 1,0% por 30, 60 e 90 minutos. Os resultados foram comparados com os obtidos nos testes de germinação. A coloração das sementes após o teste de tetrazólio, em cada tratamento, foi avaliada mediante comparação com as fichas de cor do catálogo de Munsell, determinando-se a porcentagem de sementes observada em cada cor. O delineamento experimental foi o inteiramente casualizado e a comparação de médias realizada pelo teste de Tukey a 5% de probabilidade. Para avaliar o potencial fisiológico pelo teste de tetrazólio, as sementes de mamoneira devem ser imersas na solução de tetrazólio na concentração de 0,2% por 120 minutos, a 35ºC. Nesse tratamento, as sementes viáveis após a coloração na solução de tetrazólio apresentaram predominantemente as cores rosa e rosa-escuro em suas estruturas essenciais, portanto essas podem ser consideradas como as cores características para o teste de tetrazólio em sementes de mamoneira.The objective of this research was to study the tetrazolium solution concentration and staining period for the evaluation of the physiological quality of castor bean seeds (Ricinus communis L.) by the tetrazolium test, standardizing the nomenclature of the observed colors in seeds after staining. The treatments of tetrazolium solution concentration and staining period were: 0.075% and 0.1% for 120, 180 and 240 minutes, 0.2% for 60, 120 and 180 minutes, 0.5% for 60, 90 and 120 minutes and 1.0% for 30, 60 and 90 minutes. The results were compared to the germination test. The seed color after the tetrazolium test in each treatment was evaluated by comparing with the Munsell Book of color, and the percentage of seeds observed in each color was established. A randomized complete block design was used and the means were compared by the Tukey test at the 0.05 level of probability. To evaluate physiological quality by the tetrazolium test, castor bean seeds should be placed in tetrazolium solution at the concentration 0.2% for 120 minutes, at 35ºC, for staining development, and in this treatment, the viable seeds after the staining in tetrazolium solution showed predominantly the colors pink and dark pink in their essential structures. Thus these colors can be considered as the characteristics colors for the tetrazolium test in castor bean seeds
Stephen R Cattle - One of the best experts on this subject based on the ideXlab platform.
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in situ measurements of soil colour mineral composition and clay content by vis nir spectroscopy
Geoderma, 2009Co-Authors: R Viscarra A Rossel, Stephen R Cattle, A S Ortega, Youssef FouadAbstract:Proximal soil sensing (PSS) using portable visible-near infrared (vis-NIR: 400-2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell Book estimates, although the vis-NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis-NIR was effective, with good agreement between the results of this method and XRD analysis. The vis-NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by 'spiking' them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty.
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In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy
Geoderma, 2009Co-Authors: R.a. Viscarra Rossel, Stephen R Cattle, A. Ortega, Youssef FouadAbstract:Proximal soil sensing (PSS) using portable visible-near infrared (vis-NIR: 400-2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell Book estimates, although the vis-NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis-NIR was effective, with good agreement between the results of this method and XRD analysis. The vis-NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by 'spiking' them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty
