Field measurement using NIR spectroscopy is becoming a popular method to provide in situ, rapid, and inexpensive estimation of soil organic carbon (SOC) content. However NIR reflectance is quite sensitive to external environmental conditions, such as temperature and soil moisture. In the field, the soil moisture content can be highly variable. It is a challenge to find a chemometric method that allows for prediction of soil organic carbon from spectra obtained under field conditions that is insensitive to variable moisture content. This paper utilises an external parameter orthogonalisation (EPO) algorithm to remove the effect of soil moisture from NIR spectra for the calibration of SOC content. The algorithm projects all the soil spectra orthogonal to the space of unwanted variation, and thus the variations of soil moisture can be effectively removed. We designed a protocol with 3 independent datasets to be used for calibration of NIR spectra: (1) the calibration dataset, which contains soil samples with measured spectra and SOC content under standard (or laboratory) condition (air-dried), (2) the EPO development dataset contains spectra under laboratory condition (air-dried samples) and spectra collected under field conditions (varying soil moisture content), and (3) the validation dataset contains spectra collected under field condition and measured SOC content. We conducted experiments using soils at different moisture contents in laboratory conditions. Using the EPO algorithm, we are able to remove the effect of soil moisture from the spectra, which resulted in improved calibration and prediction of SOC content

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Near-infrared spectroscopy (NIRS) is a powerful non-destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in line in industries, in vivo with biomedical applications, or in field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentration. Instead of spectral pre-processing, which is commonly used by NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, i.e., coupling polarized light with NIR spectrometry, to free spectra from scattering effect. This should allow us to retrieve linear and steady conditions for spectral analysis. When tested in visible-NIR (Vis-NIR) range (400-800 nm) on model media, mixtures of scattering and absorbing particles, the setup provided significant improvements in absorber concentration estimation precision as well as in the quality and robustness of the calibration model.

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