Location: Cropping Systems and Water Quality ResearchTitle: Sensor data fusion for precision soil health
|Sudduth, Kenneth - Ken|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/4/2018
Publication Date: 11/4/2018
Citation: Veum, K.S., Sudduth, K.A., Kitchen, N.R. 2018. Sensor data fusion for precision soil health [abstract]. ASA-CSSA Meeting, November 4-7, 2018, Baltimore, Maryland. Paper 112723.
Technical Abstract: Traditional laboratory analyses cannot provide high resolution soil health data due to cost, labor requirements, and soil disturbance. Sensor-based approaches such as diffuse reflectance spectroscopy (DRS), apparent electrical conductivity (ECa), and penetrometer readings have the potential to provide rapid, high-resolution, in-situ estimation of multiple soil properties. The primary objective of this study was to compare model performance of spectra generated in the laboratory with an in-situ profile Veris P4000 DRS spectrometer that simultaneously collects spectra, ECa, and penetrometer data. A total of 157 soil cores were obtained to approximately 1 m depth from 22 sites in the Midwestern United States, representing a range of soil types and agricultural management practices. In-situ profile data were obtained at each sampling location by soil horizon, totaling 751 data points. For comparison, laboratory spectra were obtained on air-dried soil using an ASD FieldSpec Pro FR spectrometer and the Veris P4000 DRS spectrometer (adapted for laboratory spectral collection). Estimation models were developed for soil organic carbon (SOC), total nitrogen (TN), clay, silt, sand, and moisture content. Multiple techniques were evaluated to account for the effects of field soil moisture on DRS spectra. Ultimately, in-situ soil profile estimation of soil properties may become a cost-effective and practical tool for large-scale soil health investigations.