All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Prediction of Soil Fertility Properties from a Globally Distributed Soil Mid-Infrared Spectral Library Nutrient Management & Soil & Plant Analysis S oil chemical and physical information is needed to give advice on land management. Th is is especially true in developing countries, where soil diagnostic surveillance systems have been proposed to overcome data shortages (Shepherd and Walsh, 2007). Mid-infrared (MIR) diff use refl ectance spectroscopy is a reliable and fast soil analytical tool (Janik et al., 1998) that could form a basis for diagnostic surveillance systems. Soil properties are predicted either by direct absorption of the light associated with functional groups (properties such as organic C, total N, or clay composition; Van der Marel and Beutelspacher, 1976) or by correlation to such properties and the mineral composition of the soil (properties such as cation exchange capacity [CEC] and soil texture). New samples can be predicted only if they fall within the property range of the calibration set (Naes et al., 2002). In many situations, a rapid and approximate estimate of soil chemical and physical properties is adequate, and resources for an elaborate analysis may not be available. A global calibration may meet this purpose. Some studies have tested soil infrared spectroscopy on diverse data sets at the regional scale. Reeves and Smith (2009), working with a North American library of 720 samples, came to the conclusion that neither MIR nor near-infrared (NIR) spectra yielded suitable calibrations even for organic C. Th ey attributed the poor performance to the extreme sample diversity in parent material, land

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.

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PNSS P171/2B SummaryThe usefulness and limitations of near-infrared reflectance spectroscopy (NIRS) for the assessment of several soil characteristics are still not sufficiently explored. The objective of this study was to evaluate the ability of visible and near-infrared reflectance (VIS-NIR) spectroscopy to predict the composition of organic matter in soils and litter. Reflectance spectra of the VIS-NIR region (400-2500 nm) 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 modified partial least-square method and cross-validation were used to develop equations for the different constituents over the whole spectrum (1st to 3rd derivation). Near-infrared spectroscopy predicted well the C : N ratios, the percentages of O-alkyl C and alkyl C, the ratio of alkyl C to O-alkyl C, and the sum of phenolic oxidation products: the ratios of standard deviation of the laboratory results to standard error of cross-validation (RSC) were greater than 2, the regression coefficients (a) of a linear regression (measured against predicted values) ranged from 0.9 to 1.1, and the correlation coefficients (r) were greater than 0.9. Satisfactorily (0.8 ≤ a ≤ 1.2, r ≥ 0.8, and 1.4 ≤ RSC ≤ 2.0) assessed were the contents of C, N, and production of DOC, the percentages of carbonyl C and aromatic C and the ratio of alkyl C to aromatic C. However, the N-mineralization rate and the microbial biomass were predicted unsatisfactorily (RSC < 1.4). The good and satisfactory predictions reported above indicate a marked usefulness of NIRS in the assessment of biological and chemical characteristics of soils and litter.

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