Comparison of soil reflectance spectra and calibration models obtained using multiple spectrometers

In the literature of visible and near infrared diffuse reflectance spectroscopy (VNIR-DRS) for soil characterization, the effects of instruments and scanning environments on reflectance spectra and calibration models have not been well documented. To fill this knowledge gap, the goal of this study is to compare soil reflectance spectra and calibration models obtained with different spectrometers operated under different lab environments. Two sets of soil samples were used in this study. The first set (containing 180 samples collected from Quemado, Texas) was scanned by three spectrometers and no effort was provided to control the scanning protocol. The second set (containing 264 samples from Central Texas) was scanned by two spectrometers, and efforts were provided intentionally to control the scanning protocol. Partial least squares regression was applied to develop calibration models for soil organic carbon (OC) content using the first derivative spectra. Three calibration transfer methods (namely, slope and bias correction, direct standardization, and piecewise direct standardization) were used to transfer calibration models from one instrument to another. In the experiment where no scanning control was provided, significant differences were seen in mean soil spectra by different spectrometers. But cross-validation indicated that all three models can predict OC accurately. However, the OC models are quite dissimilar to each other in terms of the regression coefficients at each wavelength, and their application to the spectra measured by other instruments generally yielded poor results. All three calibration transfer methods provided a satisfactory application of the OC model calibrated on the primary instrument to secondary instruments. In the experiment where some controls were provided, mean soil spectra by different spectrometers matched each other well. The two OC models were quite similar, and model application to the spectra measured by the other instrument yielded satisfactory predictions. When scanning control was provided; however, model transfer methods improved the calibration model only marginally. All results indicate that VNIR-DRS calibration models are highly instrument/scanning environment dependent, and their extent of applicability could be highly limited. Provision of controls over the scanning protocol has the potential to remove a great deal of spectral variations that are related to extraneous effects due to multiple instruments/scanning environment. The results of this study have important implications on the future use of VNIR-DRS as a routine method for soil characterization, such as comparisons among VNIR prediction models derived from different soil labs and a global soil spectral library, where multiple instruments have to be involved.