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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #317937

Title: Estimation of soil profile physical and chemical properties using a VIS-NIR-EC-force probe

item CHO, YONGJIN - University Of Missouri
item Sudduth, Kenneth - Ken

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 6/8/2015
Publication Date: 7/26/2015
Citation: Cho, Y., Sudduth, K.A. 2015. Estimation of soil profile physical and chemical properties using a VIS-NIR-EC-force probe. ASABE, St. Joseph, MI [available online]. 2015.

Interpretive Summary: Quantification of profile soil properties such as soil carbon, bulk density, and water content is traditionally accomplished by collection of soil samples in the field and subsequent laboratory analysis. This process is inefficient and may be impractical when measurements are needed at many locations and depths across a field or landscape, for example to develop precision agriculture management plans, to quantify spatial variability in soil quality, or to drive spatially-explicit process-based models. Field-deployable sensors that can collect data at multiple depths in the soil profile are a potential solution to this problem. This research evaluated one such commercial sensor, the Veris P4000. The P4000 measures visible (VIS) and near-infrared (NIR) soil reflectance, soil electrical conductivity (ECa) and soil strength to a depth of approximately 1 m. We evaluated its ability to estimate soil carbon, bulk density, and water content for five different central Missouri fields with varying soils. We found that soil carbon was estimated with good accuracy throughout the soil profile and that soil bulk density was estimated with fair accuracy in surface soil layers, both using VIS-NIR reflectance. Fusion of data from ECa and soil strength sensors with the VIS-NIR data improved results marginally at best, and soil water content was not estimated well with any dataset. While this multiple-sensor probe showed some potential, additional data collection and improved analyses are needed to more thoroughly evaluate its ability to quantify profile soil properties. These results will benefit researchers and practitioners interested in applying soil profile sensors to improve the efficiency of quantifying spatially-variable soil properties.

Technical Abstract: Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Previous work has usually used bench spectrometers in the laboratory with some in-field data collection. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related those sensor measurements to soil properties such as bulk density, water content, and texture. One instrument that can simultaneously collect reflectance spectra, ECa and soil strength data is the Veris P4000 VIS-NIR-EC-force probe. The objective of this research was to relate laboratory-measured soil properties, including carbon, bulk density, and water content to sensor data from the Veris P4000. At field sites in mid-Missouri, profile measurements to 0.9 m were collected with the P4000 followed by removal of soil cores at each site for laboratory measurements. Using reflectance data alone, soil carbon was most accurately estimated (r2 > 0.76), and good carbon estimates were maintained for both soil profile and surface soil layers. Adding other sensor data provided only a slight improvement. Bulk density estimates using reflectance data were fair for surface soil layers (r2 = 0.57), but were poor across the soil profile. Water content was poorly estimated for both surface and profile soil layers. This study showed promise for in-field sensor measurement of some soil profile properties. Additional field data collection and model development are needed for those soil properties where combination of data from multiple sensors is required.