Prediction of nitrogen, active carbon, and organic carbon‐to‐clay ratio in agricultural soils by in‐situ spectroscopy

Abstract

Visible and near‐infrared (vis–NIR) spectroscopy is a promising technology for the analysis of different soil quality parameters. In this study, we used in‐situ vis–NIR spectroscopy in association with partial least squares regression to predict the total and the mineral (nitrate + ammonium) nitrogen content, the permanganate oxidizable carbon (POXC), as well as the ratio of soil organic carbon‐to‐clay content in different agricultural soils in Switzerland. These parameters can indeed be used as indicators of soil quality in response to agronomic practices. To this goal, a total number of 134 soil samples were used for carbon‐, total nitrogen‐ and clay‐related parameters, whereas 69 soil samples were used for the mineral nitrogen‐related parameters. We found that the partial least squares regression model can successfully predict the total nitrogen and the POXC content as well as the ratio of soil organic carbon‐to‐clay content (ratio of performance to interquartile range, RPIQ > 2.62, R2 > 0.73, Lin's concordance correlation coefficient > 0.83). As concerns the mineral nitrogen, it was not possible to successfully predict this parameter by vis–NIR spectroscopy. By demonstrating the possibility to reliably predict POXC content and the soil organic carbon‐to‐clay ratio, we show that vis–NIR can be also used to analyse soil parameters associated with both the quality of organic carbon and the structural quality of agricultural soils.