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

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2015 ASABE Annual International Meeting  152189140.(doi:10.13031/aim.20152189140)
Authors:   Yongjin Cho, Kenneth A Sudduth
Keywords:   Precision agriculture, NIR spectroscopy, soil properties, reflectance spectra, soil sensing.

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 properties. Additional field data collection and model development are needed for those soil properties where combination of data from multiple sensors is required.

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