Prediction of Soil Properties in a Field in Typical Black Soil Areas Using in situ MIR Spectra and Its Comparison with vis-NIR Spectra

Abstract

As a precious soil resource, black soils in Northeast China are currently facing severe land degradation. Visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm) and mid-infrared spectroscopy (MIR, 2500–25,000 nm) have shown great potential to predict soil properties. However, there is still limited research on using MIR in situ. The aim of this study was to explore the feasibility of in situ MIR for the prediction of soil total nitrogen (TN) and total phosphorus (TP) and to compare its performance with the use of laboratory MIR, as well as the use of in situ and laboratory vis-NIR. A total of 450 samples from 90 soil profiles, along with their in situ and laboratory spectra of MIR and vis-NIR, were collected in a field with ten different tillage and management practices in a typical black soil area of Northeast China. Partial least square regression (PLSR), random forest (RF) and multivariate adaptive regression splines (MARS) were used to generate the calibrations between the spectra and the two properties. The results showed that both MIR and vis-NIR were able to predict the TN whether in laboratory or in situ conditions, but neither of them could predict the TP quantitatively since there was no sensitive band on both spectra regarding the TP. The prediction accuracy of the TN with laboratory spectra was higher than that with in situ spectra, for both vis-NIR and MIR. The optimal prediction accuracy of the TN with laboratory MIR (RMSE = 0.11 g/kg, RPD = 3.12) was higher than that of laboratory vis-NIR (RMSE = 0.14 g/kg, RPD = 2.45). The optimal prediction accuracy of in situ MIR (RMSE = 0.20 g/kg, RPD = 1.80) was lower than that of in situ vis-NIR (RMSE = 0.16 g/kg, RPD = 2.14). The prediction performance of the spectra followed laboratory MIR > laboratory vis-NIR > in situ vis-NIR > in situ MIR. The performance of in situ MIR was relatively poor, mainly due to the fact that MIR was more influenced by soil moisture. This study verified the feasibility of in situ MIR for soil property prediction and provided an approach for obtaining rapid soil information and a reference for soil research and management in black soil areas.

Predicting Soil Properties for Agricultural Land in the Caucasus Mountains Using Mid-Infrared Spectroscopy

“…The value of WC as well as soil fertility elements (K and P) was considerably decoupled from PC1 and PC2 due to their weak relations to the soil properties; they were ultimately predicted with low accuracy. The soil properties that showed a better correspondence to PC1 and PC2 coincided with better estimates, and vice versa; this trend is in line with recent studies [26,33,35].…”

“…Most of the soil spectroscopic studies in the literature have focused on laboratory benchtop devices rather than portative spectrometers with in situ measurement capacities [32,33]. Therefore, a special emphasis has been paid to the comparative evaluation of alternative devices (e.g., handheld vs. benchtop, in situ vs. laboratory) coupled with different modeling approaches [15].…”

In‐field soil spectroscopy in Vis–NIR range for fast and reliable soil analysis: A review

“…Most of the paper evaluated here emphasized the fact that models with laboratory spectra are generally more robust (Sleep et al, 2022), but some papers underlined that the method is suitable for in situ measurements. Yet, a procedure to link field and laboratory samples and measurements to be able to use SSLs with new field samples must be defined (Biney et al, 2020;Yin et al, 2023).…”

“…For example, the 16 studies about soil use and management reviewed here did not give any information on the background of the considered soils. Since soil management can have a large impact on the needed calibration and consequently on the output accuracy, such missing information will likely be reflected in larger error terms (Greenberg et al, 2022;Karapetsas et al, 2022;Pei et al, 2019;Yin et al, 2023).…”

Prediction Accuracy of Soil Chemical Parameters by Field- and Laboratory-Obtained vis-NIR Spectra after External Parameter Orthogonalization

“…In addition, other distortions are caused by different soil aggregates, coarse particles, dead plant material and roots that can interfere with vis-NIR radiation [ 15 , 16 , 17 ]. Because of such distortions, generally, the prediction of soil parameters from laboratory-obtained vis-NIR spectra is better than from field-obtained (in situ) spectra because soil samples are preliminarily dried, sieved and often also ground, eliminating many issues associated with moisture content or structural heterogeneity [ 18 , 19 , 20 ]. However, the possibility of predicting soil parameters directly and reliably from field-obtained spectra has certainly the major advantage of avoiding or limiting the time spent for sample collection, transport, drying, sieving and grinding as is typical for laboratory-based spectra.…”