Article ID Journal Published Year Pages File Type
2025552 Soil Biology and Biochemistry 2007 12 Pages PDF
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 (r2=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 (r2=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 (r2=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.

Related Topics
Life Sciences Agricultural and Biological Sciences Soil Science
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