Journal
SOIL & TILLAGE RESEARCH
Volume 145, Issue -, Pages 93-102Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.still.2014.08.007
Keywords
Online spectra acquisition; PLSR regression; Proximal soil sensing; Sensor application; Spatial heterogeneity
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Funding
- German Federal Ministry of Education and Research (BMBF)
- European Union
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Proximal sensing of soil organic carbon (SOC) in the field using diffuse reflectance spectroscopy is still difficult under variable weather conditions. Here, we introduce a tractor-driven measuring chamber for on-the-go visible and near-infrared diffuse reflectance spectroscopy (Vis-NIRS) meeting experimental and precision agriculture demands. A commercial full-range spectrometer operates in a closed dark chamber with artificial light. Sensor view angle, distance to soil, and illumination conditions were optimized. The mobile chamber was placed on drum rollers to flatten the ploughed and tilled soil surface and to minimize disturbances in Vis-NIR spectra by surface roughness. Prior to on-the-go spectra acquisition under field conditions, SOC prediction models for the soils under study were independently calibrated under variable moisture and roughness conditions. Driving at a tractor velocity of 3 km h(-1) resulted in measuring spots of approximately 8 cm length and 3 cm width at 0.6 m distance to one another in the direction of movement, delivering geo-referenced SOC concentrations at a sub-m spatial resolution. Gravel on the soil surface resulted in erratic extremes of predicted SOC concentrations, but these could be eliminated as outliers. The system was tested under field conditions on two long-term experiments at two different sites which revealed each a large span of SOC concentrations. On-the-go predicted SOC concentrations and those obtained from conventional plot-wise lab analyses were correlated with coefficients of determination of R-2 = 0.65 and a standard error of 1.22 g SOC kg(-1). Further improvements, particularly in data processing, will enable a reliable proximal sensing on-the-go for precision agriculture purposes in the near future. (C) 2014 Elsevier B.V. All rights reserved.
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