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Sensors 2017, 17(10), 2366; https://doi.org/10.3390/s17102366

Effects of Moisture and Particle Size on Quantitative Determination of Total Organic Carbon (TOC) in Soils Using Near-Infrared Spectroscopy

1
Department of Life Science and Biotechnology, University of Ferrara, Via L. Borsari, 46, 44121 Ferrara, Italy
2
Research Centre on Animal Production, CRPA, Viale Timavo, 43/2, 42121 Reggio Emilia, Italy
*
Author to whom correspondence should be addressed.
Received: 4 August 2017 / Revised: 9 October 2017 / Accepted: 12 October 2017 / Published: 17 October 2017
(This article belongs to the Section Physical Sensors)
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Abstract

Near-Infrared Spectroscopy is a cost-effective and environmentally friendly technique that could represent an alternative to conventional soil analysis methods, including total organic carbon (TOC). Soil fertility and quality are usually measured by traditional methods that involve the use of hazardous and strong chemicals. The effects of physical soil characteristics, such as moisture content and particle size, on spectral signals could be of great interest in order to understand and optimize prediction capability and set up a robust and reliable calibration model, with the future perspective of being applied in the field. Spectra of 46 soil samples were collected. Soil samples were divided into three data sets: unprocessed, only dried and dried, ground and sieved, in order to evaluate the effects of moisture and particle size on spectral signals. Both separate and combined normalization methods including standard normal variate (SNV), multiplicative scatter correction (MSC) and normalization by closure (NCL), as well as smoothing using first and second derivatives (DV1 and DV2), were applied to a total of seven cases. Pretreatments for model optimization were designed and compared for each data set. The best combination of pretreatments was achieved by applying SNV and DV2 on partial least squares (PLS) modelling. There were no significant differences between the predictions using the three different data sets (p < 0.05). Finally, a unique database including all three data sets was built to include all the sources of sample variability that were tested and used for final prediction. External validation of TOC was carried out on 16 unknown soil samples to evaluate the predictive ability of the final combined calibration model. Hence, we demonstrate that sample preprocessing has minor influence on the quality of near infrared spectroscopy (NIR) predictions, laying the ground for a direct and fast in situ application of the method. Data can be acquired outside the laboratory since the method is simple and does not need more than a simple band ratio of the spectra. View Full-Text
Keywords: near infrared spectroscopy; soil; moisture effect; particle size effect; total organic carbon; spectra pretreatments near infrared spectroscopy; soil; moisture effect; particle size effect; total organic carbon; spectra pretreatments
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Tamburini, E.; Vincenzi, F.; Costa, S.; Mantovi, P.; Pedrini, P.; Castaldelli, G. Effects of Moisture and Particle Size on Quantitative Determination of Total Organic Carbon (TOC) in Soils Using Near-Infrared Spectroscopy. Sensors 2017, 17, 2366.

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