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Research Project: Towards Resilient Agricultural Systems to Enhance Water Availability, Quality, and Other Ecosystem Services under Changing Climate and Land Use

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Title: Prediction of soil health indicators using a field spectroradiometer equipped with an illuminating contact probe

item Fortuna, Ann Marie
item Starks, Patrick
item Nelson, Amanda
item STEINER, JEAN - Retired ARS Employee

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/23/2019
Publication Date: 11/13/2019
Citation: Fortuna, A., Starks, P.J., Nelson, A.M., Steiner, J.L. 2019. Prediction of soil health indicators using a field spectroradiometer equipped with an illuminating contact probe [abstract]. In: Proceedings of ASA-CSSA-SSSA Annual Meeting. Embracing the Digital Environment, November 10-13, 2019, San Antonio, Texas. Poster No. 1118. Available:

Interpretive Summary: Abstract only

Technical Abstract: The inherent heterogeneity of soil and added variation resulting from soil sampling makes in-situ measurements of edaphic soil properties highly desirable. This research compares the accuracy of laboratory reference measurements to that determined using a portable field spectroradiameter fitted with an illuminating contact probe for prediction of carbon (C) and nitrogen (N) fractions used as indicators of soil health. The study site is located at the USDA-ARS Grazinglands Research Laboratory El Reno, OK and is comprised of eight 1.6 ha watershed treatments established in 1978 to monitor runoff amount, suspended sediment, nitrogen and phosphorus. The current experiment includes paddocks that are representative of native warm season grasslands or winter wheat (Triticum aestivum) managed by either conventional or no-till systems. We are currently establishing a soil health baseline that will integrate a diversified adaptive crop livestock system. Landform complexes serve as replicates within and among 1.6 ha sized watershed treatments that serve as paddocks (3-4% slope, westerly exposure) allowing us to monitor biological, chemical and physical indicators of soil health. A baseline set of soil samples was taken at 0-5, 5-15 and 15-30 cm depths. Measurements included total soil organic carbon (TSOC), total soil nitrogen (TSN) and particulate organic matter C (POMC) and N (POMN). The prediction efficiencies of the baseline models for each chemometric measurement were highly quantitative: TSOC for whole and ground (R2 = 0.9, RPD = 2.7 and 0.95, 2.9 respectively); TSN for whole and ground soil (R2 = 0.95, RPD = 2.4 and 0.95, 3.3 respectively); and POMC (R2 = 0.97, RPD = 2.70 respectively) and POMN (R2 = 0.96, RPD = 3.91 respectively). These calibrated models will be used to continue to monitor shifts in soil health resulting from adaption of management practices designed to address climatic variation