Soil organic carbon plays a pivotal role in influencing crucial functional processes within the soil, encompassing nutrient storage, particularly for nitrogen, water retention capacity, and the stability of soil aggregates. Furthermore, it exerts a substantial impact on microbial activity, thus establishing itself as an integral constituent of soil fertility (Cardoso et al., 2013).
Soil organic carbon has been directly associated with several significant ecosystem services, including carbon sequestration, climate regulation, biomass production, the filtrating, buffering, and transformation of substances, as well as the preservation of genetic diversity within ecosystems (Guerra et al., 2021).
The percentage of organic matter is determined by loss on ignition, based on the change in mass after a soil is exposed to high temperature (500 °C or 932°F) in a furnace.
To determine soil organic carbon by loss of ignition:
Detailed information on how to monitor soil organic carbon
The guide includes:
In general higher soil organic carbon is considered good for soil health as it can provide nutrition for microbes and release nutrients for plant growth, as well as improve soil structure and water-holding capacities. Thresholds will depend on the type of habitat, vegetation cover and soil type. In general, in the UK it is difficult to define a specific threshold as it can range from 5 % in light coarse-textured soils in arable land to 95 % in wetlands with carbon-rich soils, as benchmarked by the UKCEH (Feeney et al., 2023).
Near-Infrared Spectroscopy (NIRS) can be employed for soil organic carbon measurement by examining the relationship between soil spectral reflectance and the spectral characteristics of soil organic matter. This approach has demonstrated efficiency and cost-effectiveness. Calibration of NIRS models necessitates the utilization of a well-representative dataset of soil samples, accompanied by corresponding laboratory measurements. The calibration process, while effective, can be time-consuming and demands expertise to ensure precise predictions. NIR models developed for a specific region may not be universally applicable to other regions due to variations in soil properties, climate, and vegetation (Long et al., 2023).