In 2021, carbon capture dominated industry conversations — especially in agriculture. What started as buzz-worthy talk has resulted in millions of dollars pledged to farmers who participated in the initial carbon credit pilots.

Unfortunately, carbon capture is often unfairly presented as either the end-all climate change solution or overblown vapor talk.

The real problem is that the carbon capture market — even if it is a viable solution for helping companies meet their goals for climate change — often has no data legs to stand on in agricultural supply chains.

The data needed to support carbon capture is not interoperable, scaleable or easy to get. Not to mention that nearly half of farmers surveyed are skeptical of environmental, social and governance (ESG) and carbon markets.

Even when you have big players like Microsoft and Bayer offering money for farm-based climate credits or programs to secure the use of those credits, there are still systemic problems with measuring and monitoring the data.

With the advent of precision agriculture and modern farming practices, the agriculture sector has already benefited from incorporating data to help reduce farming’s dependence on material resources.

Capturing carbon data is difficult because the equation for measuring carbon capture is incredibly complicated. For a variety of reasons, it cannot rely solely on remote sensing data sources, such as satellite imagery. The monitoring, reporting and verification platforms must rely on field-level layers of data that capture stewardship practices from planting through harvest to paint a complete picture of a farming operation.

Machine data is just as important as agronomic data because our agriculture equipment’s carbon footprint also plays a role. We need historical data in order to set a baseline and show improvement over time. There is financial risk and added expense, and it takes seasons to make it visual with growers.

To date, data capture in agriculture has largely been a manual process, and the data has been low-quality or incomplete. It is often self-reported or collected by hand and, as a result, low-resolution. Farmers simply haven’t had the tools.

Lastly, there is not a single data standard that makes it easily shared, compared or used. Even if you could piece the data puzzle together, nothing is in the same format, and it becomes difficult to interpret results or extrapolate them to the economic implications for your farm. Without standards around the ecosystem assets that are being created, it’s impossible to set fair and accurate prices.

As cited in an article from Agri-Pulse, "A priority for the USDA in the coming years will be judging the feasibility of setting up, executing and paying for a federal carbon bank to help farmers reduce greenhouse gas emissions and reward them for their actions, Agriculture Secretary Tom Vilsack said [in 2021]." Without solid data behind carbon capture, the government won't provide the necessary incentives and support for this and other emerging markets.

With political and social tailwinds supporting climate initiatives, this is a historic moment that farmers need to capitalize on. If the data gap persists, farmers will miss out on a big financial opportunity. The technology is already better at proving out what is happening at the field level, and the agriculture industry is finally waking up to the data problem/opportunity as other companies need interoperable data as well.

The carbon capture industry needs to match the size of the oil industry in the next 30 years.

If we don’t start collecting the data now, we won’t know the kind of data actually needed to succeed in emerging markets and will be without the data infrastructure to participate.

The urgency is extraordinary.

There are a number of barriers standing in the way of widespread adoption. There’s no established market for credits, nor is there a widely acknowledged price. Furthermore, farmers need at minimum two to four years of historical data to develop a baseline calculation for their credits.

The eligible farmers who are participating (less than 1% of farmers surveyed) in these markets have done it at a small scale. According to Farm Journal’s Carbon Survey, farmers said “they would need a return on investment of more than $20,000 to participate in carbon markets.”

The burden of participating in these programs needs to be reduced. Government incentives will go a long way in supporting this market, but promises will continue to be empty if we don’t have the data to back up claims about carbon capture and which farming practices are most efficient at it. Modern documentation will go far in helping government programs see better and faster adoption.

It’s the wild west. Programs rolled out over the past year could be confusing and radically different agreements offered to the same farmer could slow adoption, trust and commitments. The farmers with the best systems of record and the cleanest data sets will be the ones to not only get in first and start making revenue quickly but will also have the greatest amount of leverage.

There’s plenty of room for collaboration with external partners regarding new solutions that incentivize change. We’ve seen this to great effect in the modernization of the American healthcare industry with its adoption of electronic health records, which propelled the industry forward 20 years.

Farmers and retailers have to move to real-time data collection and collect agronomic and machine-level data. They have to start now — historical data will be crucial.

This is a long-term initiative and will take several seasons before we start seeing a return, but the time is now. We don’t want to see farmers get left behind.

Think of Bitcoin’s rapid rise and the early adopters who’ve made massive fortunes. Farmers should not delay in collecting, organizing and cleansing the data required to create their assets or risk losing another year of potential revenue.

Quality data will serve as the arbiter for the first to take advantage of these new opportunities. Maybe this time, we can give farmers a fighting chance.