Author
Veum, Kristen | |
Sudduth, Kenneth - Ken | |
Kitchen, Newell |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 2/15/2017 Publication Date: N/A Citation: N/A Interpretive Summary: Technical Abstract: Assessment of soil health involves determining how well a soil is performing its biological, chemical, and physical functions relative to its inherent potential. Within the Central Claypan Region of Missouri, the Salt River Basin was selected as a benchmark watershed to assess long-term effects of conservation practices on soil health. Due to high cost, labor requirements, and soil disturbance, traditional laboratory analyses cannot provide high resolution soil health data. Therefore, sensor-based approaches are important to facilitate cost-effective, site-specific management for soil health. The primary objectives of this long-term research project include (1) comparison of soil health under multiple long-term perennial and annual cropping systems, and (2) evaluation of a sensor fusion approach to estimate soil health indicators using visible and near-infrared (VNIR) spectroscopy in conjunction with soil apparent electrical conductivity (ECa), and penetration resistance measured by cone penetrometer (i.e., cone index, CI). Surface (0-5 cm) and subsurface (5-15 cm) soil samples were obtained from 10 agricultural systems representing a range of management practices. Multiple biological, physical, and chemical soil health indicators (SQI) were measured and scored using the Soil Management Assessment Framework (SMAF). VNIR spectral data were obtained in the laboratory, while CI and ECa data were obtained in situ. In the surface layer, systems with permanent, vegetative cover and living roots demonstrated the greatest SMAF scores, ranging from 88 to 98% of the soil’s inherent potential. Across SQIs, biological and physical indicators were the most sensitive to management effects. Models estimating overall SMAF scores were improved by integrating ECa and CI with VNIR reflectance data (R2 = 0.78, RPD = 2.13, RPIQ = 3.66) relative to VNIR alone (R2 = 0.69, RPD = 1.82, RPIQ = 3.14), reducing RMSE by 14%. The results of this study demonstrate the strong influence of vegetative cover and living roots on soil health, and emphasize the importance of diversified cropping systems that reduce soil disturbance and maximize soil cover. In addition, these results illustrate the potential for rapid quantification of soil health by fusing VNIR sensors with auxiliary data obtained from complementary sensors. |