The use of visible and near‐infrared spectroscopy for in situ characterization of agricultural soil fertility: a proposition of best practice by comparing scanning positions and spectrometers

Abstract

AbstractThe application of visible and near‐infrared (vis‐NIR) spectroscopy to characterize soil samples has gained growing interest as a fast and cost‐effective methodology for soil fertility assessment. In order to profit from the full potential of vis‐NIR spectroscopy, the acquisition of soil spectra directly in‐situ would increase the possibility to obtain data rapidly and at a high spatial and temporal resolution. In the present study, we test and propose the best practice to characterize a set of fertility‐related parameters (i.e. texture, organic carbon, pH, cation exchange capacity and major nutrients) of agricultural soils by measuring vis‐NIR spectra in the field. To reach this goal, we compare the spectra obtained from different scanning positions with two portable spectrometers, i.e. a micro‐electro‐mechanical systems (MEMS)‐based spectrometer and a research‐grade vis‐NIR spectrometer. On the basis of 134 soil sampling points, vis‐NIR spectra were recorded from: 1) the cutaway side of a soil sample collected with an Edelman auger to a depth of 20 cm, 2) the raw soil surface, as well as 3) the cleaned and smoothed soil surface. Partial least squares regression (PLSR) calibration models were built for the selected soil parameters, scanning positions and different spectral pre‐treatments for both spectrometers. The model performance was evaluated based on the ratio of performance to interquartile range (RPIQ), the R2, the root mean squared error (RMSE) and Lin's Correlation Concordance Coefficient (CCC). Overall, the following soil parameters were successfully predicted: clay, sand, pH, organic carbon, cation exchange capacity, total nitrogen and exchangeable magnesium. In contrast, total and exchangeable Ca, K and P, as well as total Mg could not be predicted at a satisfactory level for both the spectrometers. The best scanning position for the successfully calibrated models was along the cutaway sides of the Edelman auger. Although the research‐grade spectrometer gave better performance indicators for most of the parameters, the calibrations with the MEMS‐based spectrometer still resulted in satisfactory predictions. Based on these findings, the proposed best practice for obtaining in situ soil vis‐NIR scans is to scan along the cutaway sides of a soil core using at least five replicate scans.