Location: Dale Bumpers Small Farms Research Center
Project Number: 6020-21500-001-017-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: May 15, 2024
End Date: May 15, 2027
Objective:
Combine remotely sensed and field data with laboratory analysis to develop high spatial resolution maps of soil properties to support precision agriculture for small farms.
Approach:
Precision agriculture technologies can reduce the footprint of agriculture activities and input to the environment while saving cost at the same time. However, high spatial resolution maps of soils and properties are needed and are not widely available, especially for small farms who can benefit the most from such maps. Experimental Design: Spectral reflectance data from satellite-borne sensors for visible, near infrared, and shortwave infrared portions of the electromagnetic spectrum will be collected for time-series analysis of soil and vegetation responses to climate and hydrological conditions. Variability in spectral response will be leveraged to drive inference regarding variability of soil moisture related to clay content and clay mineralogy. Ground conditions will be quantified for livestock, row crops, forage, and other land uses and their variability will be linked to treatment, environmental, and inherent baseline variables. Models relating landscape heterogeneity and spectral reflectance to baseline soil properties will be developed. The clay content will be quantified through hydrometer method and the clay mineralogy will be determined using X-ray Diffraction. Models will be refined and validated based on ground-truth measurements of soil, forage, and livestock behavioral variability. Novel technologies involving remotely sensed spectral reflectance, X-ray diffraction, and laboratory spectroscopy will be analyzed for feasibility and applied as applicable for predicting and characterizing site variability. Maps of parent material, soil organic matter, and other soil properties will be derived from observations to aid in site-specific management and studies of systems variability.
