Modelling the transformation of organic materials in soil with nuclear magnetic resonance spectra

Abstract

Changes in the carbon (C) and nitrogen (N) compartments that result from the addition of organic material (OM) to the soil are predicted by the transformation of added OM (TAO) model with three parameters: very labile (P′L) and stable (PS) fractions of the OM and the rate of remineralization (kremin) of nitrogen immobilized by microorganisms. We propose relations between P′L, PS, kremin and various chemical groups in the OM identified by their 13C nuclear magnetic resonance (NMR) spectra. The aromatic content increased the predicted PS in accordance with published results. The O-aromatic content also increased PS, but much less so than the aromatic content. The carboxyl content decreased PS and increased P′L as in the TAO model based on infrared spectrometry. The carbonyl content decreased P′L, whereas di-O-alkyl increased P′L. The chemical composition of the population of decomposer organisms did not appear to be homeostatic, but was related rather to the composition of the substrate: kremin was positively correlated with the carboxyl and di-O-alkyl content and negatively correlated with the alkyl content. Solid state 13C NMR spectroscopy gave better predictions of the transformations that resulted from adding OM than biochemical fractionation and near infrared reflectance spectrometry (NIRS). It is fast and non-destructive and provides new insights into the processes that control decomposition for research into waste recycling, agro-ecology and climate change. (Résumé d'auteur

Quantifying and simulating carbon and nitrogen mineralization from diverse exogenous organic matters

“…Other EOM characteristics not considered here might contribute to improving the prediction of EOM model parameters and, subsequently, the simulation of C and N mineralization. For example, the C:N ratio of biochemical fractions has been shown to be useful in predicting N mineralization Parnaudeau et al, 2004), as well as 13C-CPMAS NMR spectral regions (Bonanomi et al, 2019;Pansu et al, 2017). However, these characteristics were not available in the EOM database we used and are not usually available outside research laboratories.…”

Modelling the continuous exchange of nitrogen between microbial decomposers, the organs and symbionts of plants, soil reserves and the atmosphere

“…1 = 0 for all t), j defines the plant (cereal or legume) and k defines the plant organ or symbiont (litter-NC, root-NC, or nodule-NC). Using f Sj,k the stable fraction of each plant organ j,k (data invariant with time which can be estimated by the TAO model from fiber measurements (Thuriès et al, 2002), near infrared (Kaboré et al, 2012), or solid state nuclear magnetic resonance spectrometry (Pansu et al, 2017) and stored in a data base. The B N vector of N inputs was adjusted daily to C inputs (Ibrahim et al, 2016) by the balance equation:…”