In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy

Proximal soil sensing (PSS) using portable visible–near infrared (vis–NIR: 400–2500 nm) spectrophotometers can be used to measure soil properties in situ. The objectives of this research were: (i) to compare field spectra collected in situ to spectra collected in the laboratory, (ii) to estimate soil colour and mineral composition from the spectra, and (iii) to make predictions of clay content using a spectral library that contains mostly spectra collected in the laboratory but also a smaller number of field spectra that were collected in situ. The evaluation was conducted using 10 soil profiles derived from different parent materials. Spectroscopic measurements were collected both in the field and in the laboratory at different depths, in triplicate. These spectra were compared multivariately using principal component analysis and by using wavelength specific t-tests. Except in the water absorption regions around 1400 nm and 1900 nm and in regions that are not primarily used to characterise soil mineral composition, field-collected spectra were not significantly different to spectra collected in the laboratory. Estimates of soil colour and mineral composition were made from the spectra using a continuum-removal technique and by targeting characteristic absorption features. Estimates of soil colour were derived from the spectra of each profile using the Munsell HVC and CIELab colour models. These were compared to qualitative estimates of Munsell colour made in the field. Spectroscopic estimates of soil colour were in fair agreement with Munsell book estimates, although the vis–NIR estimates tended to be somewhat darker and more yellow. Quantitative estimates of mineral composition were derived by comparing soil spectra to the spectra of pure minerals. These estimates were assessed using qualitative X-ray diffraction (XRD) analysis. The characterisation of soil mineral composition by vis–NIR was effective, with good agreement between the results of this method and XRD analysis. The vis–NIR technique was less laborious than conventional XRD, did not require sample preparation and was better at detecting iron oxides. A spectral library containing 1287 laboratory-collected spectra and 74 spectra collected in situ at field conditions was used to develop partial least squares regression (PLSR) models to predict the clay content of both the field- and laboratory-collected spectra from the 10 soil profiles. Predictions of clay content from the field-collected spectra (RMSE = 7.9%) were slightly more accurate than those from the laboratory-collected spectra (RMSE = 8.3%). Extending the range of the PLSR calibrations by ‘spiking’ them with 74 field spectra improved the generalisation capacity of the models. PLSR with bootstrap aggregation, or bagging-PLSR (bPLSR), produced predictions of clay content for each profile with a measure of their uncertainty.