Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils - Critical review and research perspectives

This paper is an extensive review of the research that has been undertaken on near-infrared (NIR) and mid-infrared (MIR) spectroscopy applied to soil particularly for determining carbon (C) content. The objective is to determine which acquisition method (NIR. MIR, in the field or in the laboratory) might be recommended for the purpose of C stock measurement with a particular interest in carbon credit trading. For this purpose, an optimal method has to satisfy the dual constraints of low-cost and high throughput analysis. The various methods proposed in the literature are compared. In order to make comparisons as reliable as possible, special attention has been paid to the conditions of data acquisition (sample preparation), and to calibration and validation procedures. In particular, whether the validation has been carried out on fully independent samples or on samples similar to the ones of the calibration set greatly influences the results. Also, for C stock measurement, it is absolutely necessary to measure the bias of the prediction in order to be conclusive about the feasibility of the method. However, only few researchers provide this parameter and we recommend including it as a matter of course in future reports. Finally, although MIR on dried and ground samples is the most accurate method, on-the-go and in-field sensors provide predictions accurate enough to show promise in being a valuable component of technologies that would be used for C-credit purposes. But in order to meet the cost/accuracy trade-off, the main issue using such field sensors is to be able to simultaneously measure the bulk density or, better, to directly measure the volumetric concentration of C in soil. This circumvents the costs of field extraction and laboratory analysis. This is the next great challenge to be met by soil scientists. (C) 2011 Elsevier Ltd. All rights reserved.