The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
José Alexandre Melo Demattê - One of the best experts on this subject based on the ideXlab platform.
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Chemometric Soil Analysis on the determination of specific bands for the detection of magnesium and potassium by spectroscopy
Geoderma, 2017Co-Authors: José Alexandre Melo Demattê, Leonardo Ramirez-lopez, Karina P.p. Marques, Arnaldo Antonio RodellaAbstract:Abstract The laboratory Soil Analysis is traditionally used to establish elements, such as those related with fertility. It is costly and time consuming, which insures issues for future of precision agriculture, which is stagnated in some countries. Reflectance spectroscopy has recently emerged as a potential tool to reduce these issues. However, chemical elements are usually only underlined with spectra by a “coincidently” statistics and doesn't provide real detection. This study aims to investigate to interaction of K + and Mg 2 + with electromagnetic energy for decrease the demand of Soil Analysis and rationalize the use of fertilizers. The experiment was carried out using three major Soil classes with different textures from tropical environment in Brazil. To reach K + and Mg 2 + saturation in different levels, the Soils were saturated with concentrated solutions of KCl and MgCl 2 in vertical columns and then washed with distilled and deionized water to extract the residual elements. A second experiment was made by incubation of these elements in Soils during four days in room temperature around 30 °C. Laboratory spectral sensing was carried out in the VIS-NIR-SWIR regions (350–2500 nm). Spectra were processed by the Continuum Removal, the Principal Components Analysis (PCA) and Partial Least Squares regression. The PCA showed a high degree of association between spectral and chemical variations. There was no alteration on mineralogy, texture, organic matter, moisture and effective cation exchange capacity (CEC) after the experiment occurs. On the other hand, differences on spectral, mainly where occurs CEC around 2200 nm, did change. Thus, the incident energy interacts with K + and Mg 2 + which promoted these alterations, mostly for Arenosol and Ferrasol. In Cambisol (2:1 mineralogy) we had a double effect due to effective CEC and cations alteration. Were encountered specific bands which altered features due to K + and Mg 2 + content mainly in 2186, 2189 and 2200 nm. Based on the results, the identified bands (related to K + and Mg 2 + contents in the Soil) were extracted from the spectral data of Soil samples obtained from a Brazilian Soil spectral library. Indeed calibrations of K + and Mg 2 + models allowed to quantify these elements with 0.66 R 2 for the selected bands and 0.64 for the entire spectrum. Thus, the results indicate that it is possible to detect chemical elements, such K + and Mg 2 + in VIS-NIR-SWIR, looking forward on to assist Soil Analysis and all inherent approaches.
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Variation of routine Soil Analysis when compared with hyperspectral narrow band sensing method
Remote Sensing, 2010Co-Authors: José Alexandre Melo Demattê, Peterson R. Fiorio, Suzana R. AraújoAbstract:The objectives of this research were to: (i) develop hyperspectral narrow-band models to determine Soil variables such as organic matter content (OM), sum of cations (SC = Ca + Mg + K), aluminum saturation (m%), cations saturation (V%), cations exchangeable capacity (CEC), silt, sand and clay content using visible-near infrared (Vis-NIR) diffuse reflectance spectra; (ii) compare the variations of the chemical and the spectroradiometric Soil Analysis (Vis-NIR). The study area is located in São Paulo State, Brazil. The Soils were sampled over an area of 473 ha divided into grids (100 × 100 m) with a total of 948 Soil samples georeferenced. The laboratory RS data were obtained using an IRIS (Infrared Intelligent Spectroradiometer) sensor (400–2,500 nm) with a 2-nm spectral resolution between 450 and 1,000 nm and 4-nm between 1,000 and 2,500 nm. Satellite reflectance values were sampled from corrected Landsat Thematic Mapper (TM) images. Each pixel in the image was evaluated as its vegetation index, color compositions and Soil line concepts regarding certain locations of the field in the image. Chemical and physical Analysis (organic matter content, sand, silt, clay, sum of cations, cations saturation, aluminum saturation and cations exchange capacity) were performed in the laboratory. Statistical Analysis and multiple regression equations for Soil attribute predictions using radiometric data were developed. Laboratory data used 22 bands and 13 “Reflectance Inflexion Differences, RID” from different wavelength intervals of the optical spectrum. However, for TM-Landsat six bands were used in Analysis (1, 2, 3, 4, 5, and 7).Estimations of some tropical Soil attributes were possible using laboratory spectral Analysis. Laboratory spectral reflectance (SR) presented high correlations with traditional laboratory analyses for the Soil attributes such as clay (R2 = 0.84, RMSE = 3.75) and sand (R2 = 0.85, RMSE = 3.74). The most sensitive narrow-bands in modeling (using 474 observations) these attributes were B8 (1,350–1,417 nm), B10 (1,417–1,449 nm), B11 (1,449–1,793 nm), B15 (1,927–2,102 nm), B16 (2,101–2,139 nm), and B17 (2,139–2,206 nm); B7 (975–1,350 nm), B10, B11, B16, B19 (2,206–2,258 nm) and B21 (2,258–2,389 nm) for clay and sand, respectively. The bands selected to model sand and clay, by orbital data, were 3, 5 and 7 of TM-Landsat-5 and 2, 5 and 7 sand and clay, respectively. The use of Soil Analysis methodology by ground remote sensing constitutes an alternative to traditional routine laboratory Analysis.
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Orbital and laboratory spectral data to optimize Soil Analysis
Scientia Agricola, 2009Co-Authors: Peterson R. Fiorio, José Alexandre Melo DemattêAbstract:Traditional Soil analyses are time-consuming with high cost and environmental risks, thus the use of new technologies such as remote sensing have to be estimulated. The purpose of this work was to quantify Soil attributes by laboratory and orbital sensors as a non-destructive and a non-pollutant method. The study area was in the region of Barra Bonita, state of Sao Paulo, Brazil, in a 473 ha bare Soil area. A sampling grid was established (100 × 100 m), with a total of 474 locations and a total of 948 Soil samples. Each location was georeferenced and Soil samples were collected for Analysis. Reflectance data for each Soil sample was measured with a laboratory sensor (450 to 2,500 nm). For the same locations, reflectance data was obtained from a TM-Landsat-5 image. Multiple linear regression equations were developed for 50% of the samples. Two models were developed: one for spectroradiometric laboratory data and the second for TM-Landsat-5 orbital data. The remaining 50% of the samples were used to validate the models. The test compared the attribute content quantified by the spectral models and that determined in the laboratory (conventional methods). The highest coefficients of determination for the laboratory data were for clay content (R2 = 0.86) and sand (R2 = 0.82) and for the orbital data (R2 = 0.61 and 0.63, respectively). By using the present methodology, it was possible to estimate CEC (R2 = 0.64) by the laboratory sensor. Laboratory and orbital sensors can optimize time, costs and environment pollutants when associated with traditional Soil Analysis.
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spectral reflectance methodology in comparison to traditional Soil Analysis
Soil Science Society of America Journal, 2006Co-Authors: Marcos Rafael Nanni, José Alexandre Melo DemattêAbstract:Traditional Soil analyses are expensive, time-consuming, and may also result in environmental pollutants. The objective of this study was to develop and evaluate a methodology to measure Soil attributes using spectral reflectance (SR) as an alternative to traditional methods. Tropical Brazilian Soils were sampled over a 196-ha area divided into grids. Samples (n 5 184) were obtained from the 0- to 20- and 80- to 100-cm depths and georeferenced. The laboratory SR data were obtained using a Spectroradiometer (400–2 500 nm). Satellite reflectance values were sampled from corrected Landsat Thematic Mapper (TM) images. Particle-size distribution and chemical Analysis (organic matter [OM], cation-exchange capacity [CEC], total SiO2 ,F e 2O3, TiO2, sum of cations, cation, and Al saturation) were performed in the laboratory. Statistical Analysis and multiple regression equations for Soilattribute predictionsusingradiometricdataweredeveloped.Laboratory data used 22 bands and 13 ‘‘Reflectance Inflexion Differences, RID’’ from different wavelength intervals of the optical spectrum. However, the satellite data used only the reflectance of the 1, 2, 3, 4, 5, and 7 TM-Landsat bands. Multiple regression equations were derived from surface and subsurface Soil layers. Estimations of some tropical Soil attributes were possible using laboratory spectral Analysis. Laboratory SR yielded high correlations with traditional laboratory analyses (R 2 . 0.79) for the Soil attributes such as clay, sand, TiO2, and Fe2O3. Satellite spectral data correlated well with most of the Soil attributes such as clay, Fe2O3, and TiO2 (reaching R 2 5 0.72). The use of Soil Analysis methodology by satellite and/or ground remote sensing constitutes an alternative to traditional routine laboratory Analysis.
André J. Simpson - One of the best experts on this subject based on the ideXlab platform.
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Cross polarization-single pulse/magic angle spinning (CPSP/MAS): A robust technique for routine Soil Analysis by solid-state NMR
Geoderma, 2020Co-Authors: Denis Courtier-murias, Hashim Farooq, James G. Longstaffe, Brian P. Kelleher, Kris M. Hart, Myrna J. Simpson, André J. SimpsonAbstract:International audienceSoils are amongst the largest organic carbon reservoirs on earth containing approximately three times the carbon contained in all living systems and roughly double the amount present in the atmosphere. Soil organic matter is central to agriculture, carbon cycling, and contaminant sequestration, but due to its extreme heterogeneity it is challenging to study with most modern analytical approaches. As such 13C NMR spectroscopy has emerged as an indispensable technique for the characterization of Soil organic matter in the solid-state. Single pulse (SP) 13C NMR approaches theoretically provide the highest level of quantitation for Soil organic matter, however, due to its relative insensitivity, sample Analysis can take a prohibitively long time. Consequently, for routine studies the more sensitive approach of cross-polarization under magic angle spinning conditions (CP/MAS) is more commonly utilized. In particular, 13C CP is extremely useful when low organic carbon content samples are compared and is normally used to reveal the nature, transformations and fate of organic matter in Soils. Here, the performance of a novel NMR scheme, which so far has not yet been applied to Soils samples, is investigated. The ramp-CPSP scheme adds a SP block to a ramp-CP scheme, taking advantage of both techniques without extending the experimental time. This method shows enhancements higher than 100% for key regions of the 13C spectra and also provides 13C profiles that are closer to quantitative when compared to the widely used ramp-CP scheme. In addition, a critical Analysis of these enhancements is presented. Even under the worst case scenario, when the SP element adds little additional signal, the result still reflects the conventional ramp-CP experiment. As such the ramp-CPSP approach can be implemented in a routine fashion without drawback. The results shown here suggest replacing conventional ramp-CP with the ramp-CPSP sequence for routine Soil Analysis in the solid-state since it can save considerable experimental time and provide a more representative 13C spectrum of the Soil in general
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Cross polarization-single pulse/magic angle spinning (CPSP/MAS): A robust technique for routine Soil Analysis by solid-state NMR
Geoderma, 2014Co-Authors: Denis Courtier-murias, Hashim Farooq, James G. Longstaffe, Brian P. Kelleher, Kris M. Hart, Myrna J. Simpson, André J. SimpsonAbstract:Soils are amongst the largest organic carbon reservoirs on earth containing approximately three times the carbon contained in all living systems and roughly double the amount present in the atmosphere. Soil organic matter is central to agriculture, carbon cycling, and contaminant sequestration, but due to its extreme heterogeneity it is challenging to study with most modern analytical approaches. As such 13C NMR spectroscopy has emerged as an indispensable technique for the characterization of Soil organic matter in the solid-state. Single pulse (SP) 13C NMR approaches theoretically provide the highest level of quantitation for Soil organic matter, however, due to its relative insensitivity, sample Analysis can take a prohibitively long time. Consequently, for routine studies the more sensitive approach of cross-polarization under magic angle spinning conditions (CP/MAS) is more commonly utilized. In particular, 13C CP is extremely useful when low organic carbon content samples are compared and is normally used to reveal the nature, transformations and fate of organic matter in Soils. Here, the performance of a novel NMR scheme, which so far has not yet been applied to Soils samples, is investigated. The ramp-CPSP scheme adds a SP block to a ramp-CP scheme, taking advantage of both techniques without extending the experimental time. This method shows enhancements higher than 100% for key regions of the 13C spectra and also provides 13C profiles that are closer to quantitative when compared to the widely used ramp-CP scheme. In addition, a critical Analysis of these enhancements is presented. Even under the worst case scenario, when the SP element adds little additional signal, the result still reflects the conventional ramp-CP experiment. As such the ramp-CPSP approach can be implemented in a routine fashion without drawback. The results shown here suggest replacing conventional ramp-CP with the ramp-CPSP sequence for routine Soil Analysis in the solid-state since it can save considerable experimental time and provide a more representative 13C spectrum of the Soil in general.
James B Reeves - One of the best experts on this subject based on the ideXlab platform.
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near versus mid infrared diffuse reflectance spectroscopy for Soil Analysis emphasizing carbon and laboratory versus on site Analysis where are we and what needs to be done
Geoderma, 2010Co-Authors: James B ReevesAbstract:Over several decades, near infrared (NIR) diffuse reflectance spectroscopy (NIRS) has been shown to be extremely versatile for the rapid Analysis of many agricultural materials including forages, foods and grains. More recently, mid-infrared (mid-IR) diffuse reflectance spectroscopy (DRIFTS) and NIRS have come under intense scrutiny for their potential to provide a rapid method for the Analysis of Soil C, minerals and other Soil parameters of interest. Research has demonstrated that for the determination of Soil C, DRIFTS is often more accurate and produces more robust calibrations than NIRS when analyzing ground, dry Soils under laboratory conditions. However, mid-IR spectra are known to be more affected by moisture and sample preparation than NIR. In reality, DRIFTS is not even considered feasible on samples containing high levels of moisture due to the strong water absorptions in the mid-IR, although the presence of water is also known to often degrade even NIR spectra and subsequent calibrations. While both techniques offer the potential for the Analysis of Soils on-site, and even in situ, many questions remain to be answered including: 1. What are the advantages and disadvantages of on-site as opposed to laboratory Analysis? 2. What are the effects of moisture and particle size on accuracy if samples are to be analyzed on-site? 3. Which spectral range (mid-IR or NIR) is the most effective for in laboratory and/or on-site Analysis? 4. Which analytes can be accurately analyzed by NIR and/or mid-IR spectroscopy? 5. What are the effects of different Soil types and compositions on the entire process of calibration development? In addition, while DRIFTS has been shown to be advantageous in the laboratory, if samples need to be ground and dried, and instruments purged to obtain useable data, it may not be practical for on-site use. This review will try to answer some of these questions and show where the science stands and what needs to be done before NIRS or DRIFTS can be fully exploited for routine Soil Analysis.
Denis Courtier-murias - One of the best experts on this subject based on the ideXlab platform.
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Cross polarization-single pulse/magic angle spinning (CPSP/MAS): A robust technique for routine Soil Analysis by solid-state NMR
Geoderma, 2020Co-Authors: Denis Courtier-murias, Hashim Farooq, James G. Longstaffe, Brian P. Kelleher, Kris M. Hart, Myrna J. Simpson, André J. SimpsonAbstract:International audienceSoils are amongst the largest organic carbon reservoirs on earth containing approximately three times the carbon contained in all living systems and roughly double the amount present in the atmosphere. Soil organic matter is central to agriculture, carbon cycling, and contaminant sequestration, but due to its extreme heterogeneity it is challenging to study with most modern analytical approaches. As such 13C NMR spectroscopy has emerged as an indispensable technique for the characterization of Soil organic matter in the solid-state. Single pulse (SP) 13C NMR approaches theoretically provide the highest level of quantitation for Soil organic matter, however, due to its relative insensitivity, sample Analysis can take a prohibitively long time. Consequently, for routine studies the more sensitive approach of cross-polarization under magic angle spinning conditions (CP/MAS) is more commonly utilized. In particular, 13C CP is extremely useful when low organic carbon content samples are compared and is normally used to reveal the nature, transformations and fate of organic matter in Soils. Here, the performance of a novel NMR scheme, which so far has not yet been applied to Soils samples, is investigated. The ramp-CPSP scheme adds a SP block to a ramp-CP scheme, taking advantage of both techniques without extending the experimental time. This method shows enhancements higher than 100% for key regions of the 13C spectra and also provides 13C profiles that are closer to quantitative when compared to the widely used ramp-CP scheme. In addition, a critical Analysis of these enhancements is presented. Even under the worst case scenario, when the SP element adds little additional signal, the result still reflects the conventional ramp-CP experiment. As such the ramp-CPSP approach can be implemented in a routine fashion without drawback. The results shown here suggest replacing conventional ramp-CP with the ramp-CPSP sequence for routine Soil Analysis in the solid-state since it can save considerable experimental time and provide a more representative 13C spectrum of the Soil in general
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Cross polarization-single pulse/magic angle spinning (CPSP/MAS): A robust technique for routine Soil Analysis by solid-state NMR
Geoderma, 2014Co-Authors: Denis Courtier-murias, Hashim Farooq, James G. Longstaffe, Brian P. Kelleher, Kris M. Hart, Myrna J. Simpson, André J. SimpsonAbstract:Soils are amongst the largest organic carbon reservoirs on earth containing approximately three times the carbon contained in all living systems and roughly double the amount present in the atmosphere. Soil organic matter is central to agriculture, carbon cycling, and contaminant sequestration, but due to its extreme heterogeneity it is challenging to study with most modern analytical approaches. As such 13C NMR spectroscopy has emerged as an indispensable technique for the characterization of Soil organic matter in the solid-state. Single pulse (SP) 13C NMR approaches theoretically provide the highest level of quantitation for Soil organic matter, however, due to its relative insensitivity, sample Analysis can take a prohibitively long time. Consequently, for routine studies the more sensitive approach of cross-polarization under magic angle spinning conditions (CP/MAS) is more commonly utilized. In particular, 13C CP is extremely useful when low organic carbon content samples are compared and is normally used to reveal the nature, transformations and fate of organic matter in Soils. Here, the performance of a novel NMR scheme, which so far has not yet been applied to Soils samples, is investigated. The ramp-CPSP scheme adds a SP block to a ramp-CP scheme, taking advantage of both techniques without extending the experimental time. This method shows enhancements higher than 100% for key regions of the 13C spectra and also provides 13C profiles that are closer to quantitative when compared to the widely used ramp-CP scheme. In addition, a critical Analysis of these enhancements is presented. Even under the worst case scenario, when the SP element adds little additional signal, the result still reflects the conventional ramp-CP experiment. As such the ramp-CPSP approach can be implemented in a routine fashion without drawback. The results shown here suggest replacing conventional ramp-CP with the ramp-CPSP sequence for routine Soil Analysis in the solid-state since it can save considerable experimental time and provide a more representative 13C spectrum of the Soil in general.
S Ciavarella - One of the best experts on this subject based on the ideXlab platform.
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the potential of near infrared reflectance spectroscopy for Soil Analysis a case study from the riverine plain of south eastern australia
Animal Production Science, 2002Co-Authors: B W Dunn, G D Batten, H G Beecher, S CiavarellaAbstract:Environmental management in agricultural systems must be maintained while controlling costs and increasing productivity. To obtain a better response from inputs in agriculture, cost-effective Soil Analysis is needed to enable site-specific applications. Near-infrared reflectance spectroscopy (NIRS) technology has the potential to provide a rapid, low-cost Analysis enabling within field variability to be identified. NIRS was evaluated for its ability to predict a range of Soil properties in the Riverine Plain Soils of southern New South Wales. Over 550 topSoil (0-10 cm) and 300 subSoil (40-50 cm) samples from a range of Soil types were air dried and ground before scanning with a NIRSystems model 6500 scanning spectrophotometer. The Partial Least Squares (PLS) regression procedure was used to determine the best correlation (i.e. calibration) between the chemical reference data and spectral data for both topSoil and subSoil samples. A validation set of samples was used to test the predictive ability of NIRS for a number of Soil properties. The results demonstrated that NIRS can successfully determine some Soil properties in both the topSoil and subSoil. In the topSoil, cation exchange capacity (CEC), exchangeable Ca and Mg, pH and Ca : Mg ratio were predicted with a high level of accuracy and organic carbon and exchangeable sodium percentage (ESP) with an acceptable level of accuracy. In the subSoil, CEC, exchangeable Na, Ca, Mg, ESP, pH and Ca : Mg ratio were all predicted with a high degree of accuracy. The predictive ability of NIRS for many Soil constituents may make it suitable for use in agricultural Soil assessment for site-specific agriculture in the Riverine Plain Soils of southern New South Wales.
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The potential of near-infrared reflectance spectroscopy for Soil Analysis — a case study from the Riverine Plain of south-eastern Australia
Animal Production Science, 2002Co-Authors: B W Dunn, G D Batten, H G Beecher, S CiavarellaAbstract:Environmental management in agricultural systems must be maintained while controlling costs and increasing productivity. To obtain a better response from inputs in agriculture, cost-effective Soil Analysis is needed to enable site-specific applications. Near-infrared reflectance spectroscopy (NIRS) technology has the potential to provide a rapid, low-cost Analysis enabling within field variability to be identified. NIRS was evaluated for its ability to predict a range of Soil properties in the Riverine Plain Soils of southern New South Wales. Over 550 topSoil (0-10 cm) and 300 subSoil (40-50 cm) samples from a range of Soil types were air dried and ground before scanning with a NIRSystems model 6500 scanning spectrophotometer. The Partial Least Squares (PLS) regression procedure was used to determine the best correlation (i.e. calibration) between the chemical reference data and spectral data for both topSoil and subSoil samples. A validation set of samples was used to test the predictive ability of NIRS for a number of Soil properties. The results demonstrated that NIRS can successfully determine some Soil properties in both the topSoil and subSoil. In the topSoil, cation exchange capacity (CEC), exchangeable Ca and Mg, pH and Ca : Mg ratio were predicted with a high level of accuracy and organic carbon and exchangeable sodium percentage (ESP) with an acceptable level of accuracy. In the subSoil, CEC, exchangeable Na, Ca, Mg, ESP, pH and Ca : Mg ratio were all predicted with a high degree of accuracy. The predictive ability of NIRS for many Soil constituents may make it suitable for use in agricultural Soil assessment for site-specific agriculture in the Riverine Plain Soils of southern New South Wales.