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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #341133

Research Project: Sustainable Intensification of Grain and Biomass Cropping Systems using a Landscape-Based GxExM Approach

Location: Cropping Systems and Water Quality Research

Title: Soil profile property estimation with field and laboratory VNIR spectroscopy

item Veum, Kristen
item Sudduth, Kenneth - Ken
item Kitchen, Newell

Submitted to: European Conference on Precision Agriculture Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 4/28/2017
Publication Date: 7/16/2017
Citation: Veum, K.S., Sudduth, K.A., Kitchen, N.R. 2017. Soil profile property estimation with field and laboratory VNIR spectroscopy [abstract]. In: Abstracts of 11th European Conf. on Precision Agriculture, July 16-20, 2017, Edinburgh, UK.

Interpretive Summary:

Technical Abstract: Diffuse reflectance spectroscopy (DRS) soil sensors have the potential to provide rapid, high-resolution estimation of multiple soil properties. Although many studies have focused on laboratory-based visible and near-infrared (VNIR) spectroscopy of dried soil samples, previous work has demonstrated that in-situ DRS may be an efficient and viable alternative to laboratory DRS. The objective of this study was to compare estimates of soil properties using VNIR spectra generated in the laboratory with an in-situ profile DRS spectrometer. Soil cores were obtained to approximately 1 m depth from multiple sites in the Midwestern United States, representing a wide range of soil types and agricultural management practices. At the time of core collection, in-situ profile DRS spectrometer scans were obtained at each sampling location. In the laboratory, soil cores were split by horizon, air-dried, sieved (< 2mm), and scanned with the laboratory DRS spectrometer. Laboratory measurement of soil properties including soil organic carbon (SOC), total nitrogen (TN), active C, and texture fractions is underway. Soil properties will be estimated from spectra using partial least squares regression and models will be compared using R2, RMSE, and RPIQ. If in-situ DRS performs well for profile soil property estimation, it may become a cost-effective and practical tool for large-scale soil investigations examining soil health, carbon sequestration, and other important topics related to environmental protection and agronomic sustainability.