The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Anders Pedersen - One of the best experts on this subject based on the ideXlab platform.
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stepwise Chemical Digestion near infrared spectroscopy or total n measurement to take account of decomposability of plant c and n in a mechanistic model
Soil Biology & Biochemistry, 2007Co-Authors: Trond Maukon Henriksen, Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Lars Stoumann Jensen, Audun Korsaeth, Fridrik Palmason, Anders Pedersen, Tapio SaloAbstract:Abstract Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise Chemical Digestion (SCD) and values predicted from near-infrared (NIR) spectra or total plant N concentration were compared. Seventy-six cash, forage, green manure and cover crop plant materials representing a wide range in biological origin and Chemical quality were incubated in a sandy soil at 15 °C and −10 kPa water potential for 217 d. A mechanistic decomposition model was calibrated with data from soil without plant material and initialised by data on amounts of C and N in fractions obtained from SCD directly or C and N in SCD fractions as predicted from NIR spectroscopy or plant N concentration. All model parameters describing C and N flows from plant material were kept at default values as defined in previous, independent works with the same model. When results from SCD were used directly to initialise the decomposition model, C and N mineralisation dynamics were predicted well ( r 2 =0.76 and 0.70 for C mineralisation rates and accumulation of inorganic N, respectively). When a NIR calibration was used to predict the SCD data, this resulted in nearly equally good model performance ( r 2 =0.76 and 0.69 for C and N mineralisation, respectively). This was also the case when SCD data were predicted from plant material N concentration ( r 2 =0.76 and 0.69 for C and N). We conclude that the combined use of a mechanistic decomposition model and quality data from SCD is a highly adequate basis for an a priori description of the mineralisation of both C and N from common agricultural plant materials, and that both NIR spectroscopy and measurement of total N concentration offer good and cost-effective alternatives if they are calibrated with SCD data.
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empirical predictions of plant material c and n mineralization patterns from near infrared spectroscopy stepwise Chemical Digestion and c n ratios
Soil Biology & Biochemistry, 2005Co-Authors: Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Trond Maukon Henriksen, Lars Stoumann Jensen, Audun Korsaeth, Jesper Luxhoi, Fridrik Palmason, Anders PedersenAbstract:Abstract Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize bioChemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise Chemical Digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R 2 =0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R 2 =0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R 2 =0.911), but considerably better than the C/N ratios (best R 2 =0.851). In contrast, N mineralization was better predicted by SCD fractions (best R 2 =0.533) than the C/N ratio (best R 2 =0.497), which was better than NIR predictions (best R 2 =0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.
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Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil
Journal of Near Infrared Spectroscopy, 2004Co-Authors: Bo Stenberg, Sander Bruun, Tor Arvid Breland, Lars Stoumann Jensen, Fridrik Palmason, Anders Pedersen, Tapio Salo, Erik Nordkvist, Jón GuÐmundsson, Trond Maukon HenriksenAbstract:For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise Chemical Digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise Chemical Digestion (SCD);...
Sander Bruun - One of the best experts on this subject based on the ideXlab platform.
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stepwise Chemical Digestion near infrared spectroscopy or total n measurement to take account of decomposability of plant c and n in a mechanistic model
Soil Biology & Biochemistry, 2007Co-Authors: Trond Maukon Henriksen, Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Lars Stoumann Jensen, Audun Korsaeth, Fridrik Palmason, Anders Pedersen, Tapio SaloAbstract:Abstract Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise Chemical Digestion (SCD) and values predicted from near-infrared (NIR) spectra or total plant N concentration were compared. Seventy-six cash, forage, green manure and cover crop plant materials representing a wide range in biological origin and Chemical quality were incubated in a sandy soil at 15 °C and −10 kPa water potential for 217 d. A mechanistic decomposition model was calibrated with data from soil without plant material and initialised by data on amounts of C and N in fractions obtained from SCD directly or C and N in SCD fractions as predicted from NIR spectroscopy or plant N concentration. All model parameters describing C and N flows from plant material were kept at default values as defined in previous, independent works with the same model. When results from SCD were used directly to initialise the decomposition model, C and N mineralisation dynamics were predicted well ( r 2 =0.76 and 0.70 for C mineralisation rates and accumulation of inorganic N, respectively). When a NIR calibration was used to predict the SCD data, this resulted in nearly equally good model performance ( r 2 =0.76 and 0.69 for C and N mineralisation, respectively). This was also the case when SCD data were predicted from plant material N concentration ( r 2 =0.76 and 0.69 for C and N). We conclude that the combined use of a mechanistic decomposition model and quality data from SCD is a highly adequate basis for an a priori description of the mineralisation of both C and N from common agricultural plant materials, and that both NIR spectroscopy and measurement of total N concentration offer good and cost-effective alternatives if they are calibrated with SCD data.
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empirical predictions of plant material c and n mineralization patterns from near infrared spectroscopy stepwise Chemical Digestion and c n ratios
Soil Biology & Biochemistry, 2005Co-Authors: Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Trond Maukon Henriksen, Lars Stoumann Jensen, Audun Korsaeth, Jesper Luxhoi, Fridrik Palmason, Anders PedersenAbstract:Abstract Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize bioChemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise Chemical Digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R 2 =0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R 2 =0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R 2 =0.911), but considerably better than the C/N ratios (best R 2 =0.851). In contrast, N mineralization was better predicted by SCD fractions (best R 2 =0.533) than the C/N ratio (best R 2 =0.497), which was better than NIR predictions (best R 2 =0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.
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Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil
Journal of Near Infrared Spectroscopy, 2004Co-Authors: Bo Stenberg, Sander Bruun, Tor Arvid Breland, Lars Stoumann Jensen, Fridrik Palmason, Anders Pedersen, Tapio Salo, Erik Nordkvist, Jón GuÐmundsson, Trond Maukon HenriksenAbstract:For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise Chemical Digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise Chemical Digestion (SCD);...
Trond Maukon Henriksen - One of the best experts on this subject based on the ideXlab platform.
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stepwise Chemical Digestion near infrared spectroscopy or total n measurement to take account of decomposability of plant c and n in a mechanistic model
Soil Biology & Biochemistry, 2007Co-Authors: Trond Maukon Henriksen, Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Lars Stoumann Jensen, Audun Korsaeth, Fridrik Palmason, Anders Pedersen, Tapio SaloAbstract:Abstract Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise Chemical Digestion (SCD) and values predicted from near-infrared (NIR) spectra or total plant N concentration were compared. Seventy-six cash, forage, green manure and cover crop plant materials representing a wide range in biological origin and Chemical quality were incubated in a sandy soil at 15 °C and −10 kPa water potential for 217 d. A mechanistic decomposition model was calibrated with data from soil without plant material and initialised by data on amounts of C and N in fractions obtained from SCD directly or C and N in SCD fractions as predicted from NIR spectroscopy or plant N concentration. All model parameters describing C and N flows from plant material were kept at default values as defined in previous, independent works with the same model. When results from SCD were used directly to initialise the decomposition model, C and N mineralisation dynamics were predicted well ( r 2 =0.76 and 0.70 for C mineralisation rates and accumulation of inorganic N, respectively). When a NIR calibration was used to predict the SCD data, this resulted in nearly equally good model performance ( r 2 =0.76 and 0.69 for C and N mineralisation, respectively). This was also the case when SCD data were predicted from plant material N concentration ( r 2 =0.76 and 0.69 for C and N). We conclude that the combined use of a mechanistic decomposition model and quality data from SCD is a highly adequate basis for an a priori description of the mineralisation of both C and N from common agricultural plant materials, and that both NIR spectroscopy and measurement of total N concentration offer good and cost-effective alternatives if they are calibrated with SCD data.
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empirical predictions of plant material c and n mineralization patterns from near infrared spectroscopy stepwise Chemical Digestion and c n ratios
Soil Biology & Biochemistry, 2005Co-Authors: Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Trond Maukon Henriksen, Lars Stoumann Jensen, Audun Korsaeth, Jesper Luxhoi, Fridrik Palmason, Anders PedersenAbstract:Abstract Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize bioChemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise Chemical Digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R 2 =0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R 2 =0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R 2 =0.911), but considerably better than the C/N ratios (best R 2 =0.851). In contrast, N mineralization was better predicted by SCD fractions (best R 2 =0.533) than the C/N ratio (best R 2 =0.497), which was better than NIR predictions (best R 2 =0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.
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Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil
Journal of Near Infrared Spectroscopy, 2004Co-Authors: Bo Stenberg, Sander Bruun, Tor Arvid Breland, Lars Stoumann Jensen, Fridrik Palmason, Anders Pedersen, Tapio Salo, Erik Nordkvist, Jón GuÐmundsson, Trond Maukon HenriksenAbstract:For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise Chemical Digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise Chemical Digestion (SCD);...
Tapio Salo - One of the best experts on this subject based on the ideXlab platform.
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stepwise Chemical Digestion near infrared spectroscopy or total n measurement to take account of decomposability of plant c and n in a mechanistic model
Soil Biology & Biochemistry, 2007Co-Authors: Trond Maukon Henriksen, Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Lars Stoumann Jensen, Audun Korsaeth, Fridrik Palmason, Anders Pedersen, Tapio SaloAbstract:Abstract Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise Chemical Digestion (SCD) and values predicted from near-infrared (NIR) spectra or total plant N concentration were compared. Seventy-six cash, forage, green manure and cover crop plant materials representing a wide range in biological origin and Chemical quality were incubated in a sandy soil at 15 °C and −10 kPa water potential for 217 d. A mechanistic decomposition model was calibrated with data from soil without plant material and initialised by data on amounts of C and N in fractions obtained from SCD directly or C and N in SCD fractions as predicted from NIR spectroscopy or plant N concentration. All model parameters describing C and N flows from plant material were kept at default values as defined in previous, independent works with the same model. When results from SCD were used directly to initialise the decomposition model, C and N mineralisation dynamics were predicted well ( r 2 =0.76 and 0.70 for C mineralisation rates and accumulation of inorganic N, respectively). When a NIR calibration was used to predict the SCD data, this resulted in nearly equally good model performance ( r 2 =0.76 and 0.69 for C and N mineralisation, respectively). This was also the case when SCD data were predicted from plant material N concentration ( r 2 =0.76 and 0.69 for C and N). We conclude that the combined use of a mechanistic decomposition model and quality data from SCD is a highly adequate basis for an a priori description of the mineralisation of both C and N from common agricultural plant materials, and that both NIR spectroscopy and measurement of total N concentration offer good and cost-effective alternatives if they are calibrated with SCD data.
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Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil
Journal of Near Infrared Spectroscopy, 2004Co-Authors: Bo Stenberg, Sander Bruun, Tor Arvid Breland, Lars Stoumann Jensen, Fridrik Palmason, Anders Pedersen, Tapio Salo, Erik Nordkvist, Jón GuÐmundsson, Trond Maukon HenriksenAbstract:For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise Chemical Digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise Chemical Digestion (SCD);...
Bo Stenberg - One of the best experts on this subject based on the ideXlab platform.
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stepwise Chemical Digestion near infrared spectroscopy or total n measurement to take account of decomposability of plant c and n in a mechanistic model
Soil Biology & Biochemistry, 2007Co-Authors: Trond Maukon Henriksen, Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Lars Stoumann Jensen, Audun Korsaeth, Fridrik Palmason, Anders Pedersen, Tapio SaloAbstract:Abstract Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise Chemical Digestion (SCD) and values predicted from near-infrared (NIR) spectra or total plant N concentration were compared. Seventy-six cash, forage, green manure and cover crop plant materials representing a wide range in biological origin and Chemical quality were incubated in a sandy soil at 15 °C and −10 kPa water potential for 217 d. A mechanistic decomposition model was calibrated with data from soil without plant material and initialised by data on amounts of C and N in fractions obtained from SCD directly or C and N in SCD fractions as predicted from NIR spectroscopy or plant N concentration. All model parameters describing C and N flows from plant material were kept at default values as defined in previous, independent works with the same model. When results from SCD were used directly to initialise the decomposition model, C and N mineralisation dynamics were predicted well ( r 2 =0.76 and 0.70 for C mineralisation rates and accumulation of inorganic N, respectively). When a NIR calibration was used to predict the SCD data, this resulted in nearly equally good model performance ( r 2 =0.76 and 0.69 for C and N mineralisation, respectively). This was also the case when SCD data were predicted from plant material N concentration ( r 2 =0.76 and 0.69 for C and N). We conclude that the combined use of a mechanistic decomposition model and quality data from SCD is a highly adequate basis for an a priori description of the mineralisation of both C and N from common agricultural plant materials, and that both NIR spectroscopy and measurement of total N concentration offer good and cost-effective alternatives if they are calibrated with SCD data.
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empirical predictions of plant material c and n mineralization patterns from near infrared spectroscopy stepwise Chemical Digestion and c n ratios
Soil Biology & Biochemistry, 2005Co-Authors: Sander Bruun, Bo Stenberg, Tor Arvid Breland, Jon Gudmundsson, Trond Maukon Henriksen, Lars Stoumann Jensen, Audun Korsaeth, Jesper Luxhoi, Fridrik Palmason, Anders PedersenAbstract:Abstract Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize bioChemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise Chemical Digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R 2 =0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R 2 =0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R 2 =0.911), but considerably better than the C/N ratios (best R 2 =0.851). In contrast, N mineralization was better predicted by SCD fractions (best R 2 =0.533) than the C/N ratio (best R 2 =0.497), which was better than NIR predictions (best R 2 =0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.
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Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil
Journal of Near Infrared Spectroscopy, 2004Co-Authors: Bo Stenberg, Sander Bruun, Tor Arvid Breland, Lars Stoumann Jensen, Fridrik Palmason, Anders Pedersen, Tapio Salo, Erik Nordkvist, Jón GuÐmundsson, Trond Maukon HenriksenAbstract:For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise Chemical Digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise Chemical Digestion (SCD);...