Growing concerns regarding the impact of global carbon emissions have led to rigorous studies to find effective methods and processes to sequester atmospheric carbon back into a terrestrial phase of the carbon cycle. A number of innovative mechanical sequestration solutions have been developed including geologic sub surface and deep ocean storage, while research into passive natural systems have led to a better understanding of the potential for certain soils to act as carbon sinks. Soil Organic Carbon (SOC) sequestration, in which carbon dioxide present in the atmosphere is transferred into the soil through crop residues and other organic solids is not only an important source of carbon in the soil but also provides an off-set from fossil-fuel combustion and other carbon emitting activities (OSU, SOC Factsheet).

Understanding the mechanics of SOC is important for determining soil health, productivity, and developing land management strategies, as well as carbon dioxide fluxes in the atmosphere. Accurately measuring current soil organic carbon (SOC) concentrations, understanding the contributing factors, and being able to assess a given soil’s potential to sequester additional carbon (Iowa EPSCoR) are at the core of understanding these dynamics. SOC sequestration potential is defined as the maximum possible storage of Total Below-Ground Carbon Allocation (TBCA) under a specific soil-climate-land management regime. Traditional lab-based methods for determining TBCA are costly, time-consuming and tend to destroy the sample in which it is measured (Iowa EPSCoR).

Near-infrared (NIR) reflectance spectroscopy provides an efficient cost-effective alternative to traditional lab-based SOC analysis. With NIR reflectance analysis, rapid non-destructive measurements can be taken in the field or in a controlled laboratory environment. Quantitative calibration models can be developed for rapid characterization of soil nutrients and other physical properties. Coupling this technology with hyperspectral imagery and improved spatial statistical methodologies breaks the bottleneck of sample collection and lab analysis and facilitates large-area soil characterization assessments.

The goal of this evaluation was to create a calibration model for percent SOC using near-infrared spectra of soil samples collected on the ASD LabSpec 2500 by Kenneth Wacha at the University of Iowa.

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