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Use of mid‐infrared spectroscopy in the diffuse‐reflectance mode for the prediction of the composition of organic matter in soil and litter
Author(s) -
Ludwig Bernard,
Nitschke Renate,
TerhoevenUrselmans Thomas,
Michel Kerstin,
Flessa Heiner
Publication year - 2008
Publication title -
journal of plant nutrition and soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 87
eISSN - 1522-2624
pISSN - 1436-8730
DOI - 10.1002/jpln.200700022
Subject(s) - chemistry , soil water , infrared spectroscopy , diffuse reflectance infrared fourier transform , organic matter , analytical chemistry (journal) , spectroscopy , total organic carbon , soil organic matter , coefficient of determination , alkyl , chemical composition , infrared , environmental chemistry , soil science , environmental science , organic chemistry , mathematics , physics , statistics , photocatalysis , quantum mechanics , optics , catalysis
Mid‐infrared spectroscopy (MIRS) is assumed to be superior to near‐infrared spectroscopy (NIRS) for the prediction of soil constituents, but its usefulness is still not sufficiently explored. The objective of this study was to evaluate the ability of MIRS to predict the chemical and biological properties of organic matter in soils and litter. Reflectance spectra of the mid‐infrared region including part of the near‐infrared region (7000–400 cm –1 ) were recorded for 56 soil and litter samples from agricultural and forest sites. Spectra were used to predict general and biological characteristics of the samples as well as the C composition which was measured by 13 C CPMAS‐NMR spectroscopy. A partial least‐square method and cross‐validation were used to develop equations for the different constituents over selected spectra ranges after several mathematical treatments of the spectra. Mid‐infrared spectroscopy predicted well the C : N ratio: the modeling efficiency EF was 0.95, the regression coefficient ( a ) of a linear regression (measured against predicted values) was 1.0, and the correlation coefficient ( r ) was 0.98. Satisfactorily (EF ≥ 0.70, 0.8 ≤ a ≤ 1.2, r ≥ 0.80) assessed were the contents of C, N, and lignin, the production of dissolved organic carbon, and the contents of carbonyl C, aromatic C, O‐alkyl C, and alkyl C. However, the N mineralization rate, the microbial biomass and the alkyl–to–aromatic C ratio were predicted less satisfactorily (EF < 0.70). Limiting the sample set to mineral soils did generally not result in improved predictions. The good and satisfactory predictions reported above indicate a marked usefulness of MIRS in the assessment of chemical characteristics of soils and litter, but the accuracies of the MIRS predictions in the diffuse‐reflectance mode were generally not superior to those of NIRS.