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Visible near-infrared spectroscopy (VisNIR) has been used to measure many soil properties. Typically, VisNIR is used on air-dried and ground soils in the laboratory. Recent developments in VisNIR instrumentation have allowed for the collection of VisNIR spectra from in situ soils. In this study, we demonstrate the viability of an in situ VisNIR system. VisNIR spectra were collected using a penetrometer-mounted VisNIR probe. The penetrometer-mounted VisNIR system requires no field calibration or pre-drilling of access holes. This system has several advantages in that it: 1) allows for measurement of soil properties without sample collection, preparation, and laboratory analysis and 2) can provide rapid soil measurement at high-depth-resolutions (2 cm). We applied an external parameter orthogonalization (EPO) to the in situ spectra to remove the effects of soil moisture and other in situ effects from the spectra. We calibrated partial least-squares (PLS) models using spectra from an existing library of air-dried and ground spectra. PLS models were then used to predict clay content of the EPO-transformed in situ spectra. Model results showed good predictive ability for in situ spectra with RMSE, bias, and R 2 of 88 g kg − 1 , − 15 g kg − 1 , and 0.76, respectively. A site-wise hold–out validation of EPO calibration demonstrated that EPO calibrations were robust to changes in soil characteristics and parent materials between study areas. These results show that by using the EPO-PLS method, in situ VisNIR is a viable tool for rapid, minimally invasive collection of soil data. [ABSTRACT FROM AUTHOR]

The effect of variable soil moisture, which is found in natural field conditions, is the single most limiting aspect that limits proximal implementation of VisNIR spectroscopy for predicting soil properties using dried-ground spectral libraries. Though the external parameter orthogonalization algorithm (EPO) has shown promise in removing the effect of soil moisture on soil spectra of intact-field moist soils without having to know the soil moisture, EPO has not been widely tested and has not been tested on soils with highly weathered mineralogy (oxides and kaolinite). Thus, the objective of this work was to test the effectiveness of EPO on intact field moist soil spectra and a dried-ground spectral library from highly weathered soils located in Brazil and to use this diverse dataset to assess the sensitivity of the EPO-PLS parameterization and performance to changes in the structure of the calibration spectral dataset. A dried-ground spectral library of 1515 soils collected from Piracicaba and Sao Paulo State, Brazil was transformed using the EPO P-matrix from 80 surface and subsurface soils collected independently of the library and scanned at field-moist intact and at dried-ground condition. Results show that EPO can remove the effect of soil water from field-moist spectra for tropical soils with kaolinitic and ferritic mineralogies. Predicted clay content improved from 320 to 120 g kg − 1 for spectra before and after EPO, respectively. Bootstrapping analysis was performed to assess the sensitivity of the EPO-PLS procedure to changes in the structure of the calibration spectral dataset. All EPO-PLS parameterizations were constrained to a small set of values and small changes to EPO-PLS parameterization had little observed effect on model performance. Large spectral libraries, those developed at the national or continental level, will contain soils of varying mineralogy. While research has shown that EPO is effective on smectitic soils as well as on kaolinitic soils, it is still unclear to what extent mineralogy controls EPO effectiveness. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we investigated the possibility of using the VisNIR spectra of dry ground soils to predict properties of soils scanned in their natural physical state with unknown water content. We regard this as an important nexus between large soil spectral libraries (based on dried and ground soil samples) and in-field use of VisNIR where variable soil moisture and secondary structure affect predictions of soil properties of interest. External parameter orthogonalization — EPO — was used in developing a partial least squares regression (PLSR) model to predict clay and organic C contents of soil samples with variable moisture contents. The Texas Soil Spectral Library based on spectra of dried and ground soil samples along with spectra of intact and dried and ground soil cores from Central Texas USA were used for EPO–PLSR model calibration and validation. Using EPO, three matrices were developed to project VisNIR reflectance spectra to a subspace insensitive to soil moisture. The first matrix P1 was developed using spectra collected from rewetted samples that had been dried and ground. The second and third matrices, P2 and P3 were developed using spectra from soil core samples that were in their natural physical state when scanned and either field-moist (P2), or air-dried (P3). The results showed that EPO–PLSR successfully removed the effect of moisture without knowing the moisture at time of scanning and substantially improved the prediction of clay content compared to organic C content. For clay content, the validation results were as follows: No correction, R 2 =0.63, RMSEP=355gkg−1; P1 correction, R 2 =0.73, RMSEP=141gkg−1; and P2 correction, R 2 =0.77, RMSEP=90gkg−1. For organic C content, the validation statistics were: No correction, R 2 =0.49, RMSEP=9.4gkg−1; P1 correction, R 2 =0.51, RMSEP=7.5gkg−1; and P2 correction, R 2 =0.53, RMSEP=7.3gkg−1. Corrections of soil intactness alone had the following results for clay content: No correction RMSEP=125gkg−1 and P3 correction RMSEP=97gkg−1, and for organic C content: No correction RMSEP=7.5gkg−1, and P3 correction RMSEP=7.4gkg−1. Model results using the P2 matrix were consistently better than using P1. Particularly in predicting clay, P2 reduced the bias, non-unity, and lack of correlation, possibly because P2 accounted for the effect of natural aggregation of the soil in addition to soil moisture. Improvements for correction for intactness alone were small in clay and not significant in organic C content. We concluded that it is feasible to apply the EPO algorithm to employ VisNIR models from dried ground spectral libraries for prediction of soil properties based on field scans of soils in the natural physical state and at variable water contents. [Copyright &y& Elsevier]