Fingerprinting soil

By Haly Neely

Soil organic matter, which primarily consists of organic carbon, is a key component of healthy soil. Organic carbon is largely the product of decomposing crop residues and is a highly complex soil property. The amount of organic carbon, as well as the soil texture (i.e., the amount of sand, silt, and clay), drive how productive the soil is, and even small changes can have significant impacts on soil function. Despite its importance as a key soil property, the high cost of traditional analysis methods for carbon has limited our understanding of the impact of management practices on organic carbon.

Enter a new tool. Mid-infrared (MIR) spectral analysis uses emitted and absorbed energy from chemical bonds in soil to construct a fingerprint (spectrum). A MIR spectrometer is able to analyze samples within minutes and does not require any expensive reagents or other materials. The instrument collects a spectrum, which is the reflected energy of the sample along the energy spectrum, which is then translated into absorbance (Figure 1). Each soil sample will have a unique spectrum based on the properties of the sample.

After we collect a spectrum, we can use a soil “library” to predict soil properties for the sample. These libraries are inventories of hundreds or thousands of processed soil samples that also have traditional laboratory data (Figure 2). Statistical models are then used to predict soil properties for an unknown sample using these libraries.

MIR spectroscopy has been reliably used to predict multiple soil properties such as organic carbon, inorganic carbon, clay content, and many others from a single scan and has been shown to be much less expensive than traditional analysis methods. This method has been widely used in the Midwest, which has proven that this technology can work. However, to get the most accurate predictions, soil libraries need to cover the same region as the unknown soil samples.

This new tool will improve our understanding of the interaction of management practices, soil properties, and climate conditions on carbon dynamics. As previously stated, the labor and cost of measuring organic carbon in soils has significantly hindered our comprehension of soil carbon dynamics because we could not afford to analyze enough samples to get a
clear picture.

Our current understanding is that, in general, soils with more organic carbon capture and store more rainfall, supply more nutrients to plants, encourage root growth, decrease the potential for soil erosion, and improve overall soil health. We also know that we can increase the amount of carbon in the soil by decreasing soil disturbance and increasing the amount of plant residue being added back to the soil.

However, soil organic carbon is one of the most dynamic components of soil, and it is difficult to predict what impact management practices will have on how much carbon is in the soil. For example, moving from a high-disturbance drill to a low-disturbance drill is likely to increase soil organic carbon, but by how much and how fast that happens is still hard to predict.

Adding further complexity, soil is incredibly variable across a single field (Figure 3, next page). This is especially true in Washington state where few fields are flat, and even those that are, had complex formation factors that don’t often happen simultaneously. By being able to analyze thousands of samples quickly and cheaply, we will be able to build better models that are capable of predicting how management, soil properties, and climate interact to either build or decrease organic carbon.

As stated before, we have an incomplete picture of soil carbon storage dynamics at the field scale. Additionally, changes in total soil organic carbon following the implementation of a new management practice can be small and difficult to detect against the background soil carbon levels. However, there are many pools of carbon present in the soil that have different rates of decomposition as well as different functions.

For example, particulate organic matter (POM), consisting of recently decomposed plant inputs, is considered to have a turnover time of years to decades and responds quickly to changes in land management. Mineral-associated organic matter (MAOM) is generally less susceptible to change by management but can be vulnerable to tillage. These pools are incredibly important for understanding soil carbon dynamics, but are very labor intensive and not routinely offered in commercial soil testing labs. In addition to accurate total carbon measurements, there has already been research on using MIR for soil carbon fractions.

In addition to its value to long-term sustainability, there are now programs that will pay farmers for the carbon in their soils. Although the science isn’t clear on the benefits and there is some controversy to the practice, carbon incentive programs are gaining traction in both the policy arena and the farming community. Many carbon markets already exist, and large federal investments in incentive programs are being initiated (e.g., the $3.1 billion investment into U.S. Department of Agriculture Climate Smart Commodity programs in 2022). The global voluntary carbon credit market has been estimated to be worth over $50 billion by 2030 according to a report from McKinsey & Company, and interest continues to grow as more and more companies pledge to achieve carbon-neutral status.

Carbon credit programs can be broken down into two groups: those that pay for implementing soil carbon sequestering practices including Truterra and Agoro Carbon Alliance (i.e., process driven), and those that pay for actual soil carbon stored such as Indigo Ag (i.e., outcome driven). There continues to be many questions and concerns about the carbon credit market space, including how different regions will be treated in these programs. For example, one of the practices that is often eligible for carbon credits is planting cover crops; however, this is not a viable option in some regions in Washington state.

The Pacific Northwest represents a significant potential opportunity for long-term, stable, carbon storage including highly complex landscapes and fewer options to build soil organic carbon. Also, because most of the current programs are process driven, farmers who have been using carbon sequestering practices for years are currently not eligible for compensation. Moving from process-driven to outcome-driven programs may open up more opportunities for Washington state farmers to receive revenue from measured soil carbon. Soil scientists are currently working to identify fair and rational soil reference states (i.e., as-good-as-we-can-get scenarios) to provide evidence that a farmer has reached soil carbon sequestration potential; outcome-driven programs could be developed to compensate farmers.

Whether we need organic carbon measurements for assessing management practices, for carbon credit programs, or for research questions, MIR spectroscopy can provide these measurements inexpensively and quickly. It is an exciting time in soil science as we continue to unlock dynamic processes so we can provide better information to stakeholders.