Combining frequency domain reflectometry and visible and near infrared spectroscopy for assessment of soil bulk density

This paper introduces a new approach for the assessment of soil bulk density (BD), which relies on an existed model to predict BD as a function of a visible and near infrared spectroscopy (vis-NIRS) measured gravimetric moisture content (omega) and a frequency domain reflectometry (FDR) measured volumetric moisture content (theta v). A total of 1013 soil samples collected from England and Wales, from 32 arable and grassland fields with different soil types were measured with a vis-NIR spectrophotometer (LabSpec (R) Pro Near Infrared Analyzer, Analytical Spectral Devices, Inc., USA) after in situ measurement with a ThetaProbe FDR (Delta-T Device Ltd.). Two calibration methods of the vis-NIRS were tested, namely, partial least squares regression (PLSR) and artificial neural network (ANN). ThetaProbe calibration was performed with traditional methods and ANN. ANN analyses were based on a single-variable input or multiple-variable input (data fusion). During ANN - data fusion analysis, vis-NIRS spectra and ThetaProbe output voltage (V) were fused in one matrix with or without laboratory measured texture fractions and organic matter content (OM). For the vis-NIRS and ThetaProbe traditional calibration, samples were divided into calibration (75%) and prediction (25%) sets, whereas for the ANN analyses these were divided into calibration (65%), test (10%) and independent validation (25%) sets. Results proved that high measurement accuracy can be obtained for omega and theta v with PLSR and the best performing traditional calibration method of the ThetaProbe with R-2 values of 0.91 and 0.97, and root mean square error of prediction (RMSEp) values of 0.027 g g(-1) and 0.019 cm(3) cm(-3), respectively. However, the ANN - data fusion resulted in improved accuracy (R-2 = 0.98 and RMSEp = 0.014 g g(-1) and 0.015 cm(3) cm(-3), respectively). This data fusion approach led to the best accuracy for BD assessment when vis-NIRS spectra and ThetaProbe V only were used as input data (R-2 = 0.81 and RMSEp = 0.095 g cm(-3)). It can be concluded that BD can be measured by combining the vis-NIRS and FDR techniques based on ANN-data fusion approach. (C) 2013 Elsevier B.V. All rights reserved.