Is Agriculture Missing an Environmental 'Energy Grid'?

Summary:

• Environmental data is needed by Agriculture to drive sustainable farming practices, carbon offsets markets and on-farm efficiencies.
• The problem today is that environmental data is 'stove piped' across service providers, agtech companies and data 'generators'.
• We need better 'infrastructure' to manage and share environmental data across agriculture.
• FarmLab are developing the 'energy grid' to support the transfer, interpretation and use of environmental data across the sector.

I've had a few discussions lately with investors about sustainability and environmental data in Agriculture; in particular which companies and service providers are managing what data, and where FarmLab fits amongst these.

It's clear to me (and most of us working in this sector) that there are 'stovepipes of excellence' across Agriculture when it comes to the generation and use of environmental data. We have a range of specialist service providers, Agtech companies and government datasets that all collect and provide really good environmental information for specific purposes to farmers. The issue is the transfer and management of this information is poor. A cynic might suggest many companies and service providers are just being territorial, and holding their cards close to their chest – whilst some might be, the reality is there's no easy way to do share and transfer environmental data.

In the case of FarmLab, we don’t really fit into any of these categories. We don’t interpret, generate or apply the data. Instead we support the collection and management of it – and we’ve built a raft of infrastructure to do so. This includes integrations with labs that conduct soil, plant and water testing, access to remote imagery and more recently analytics features to analyse and interpret that data. Now we’re opening up that infrastructure in support of agriculture’s needs; working more closely with other Agtech partners and service providers to support their collection and provision of these datasets to farmers. One of those was our recent integration with FarmOS and Regen Farmers Mutual, where we provided our infrastructure to access soil testing labs and a payment system to farmers and RFM agronomists to support them to collect soil tests and use soil data alongside the other datasets in their platform.

The Environmental Energy Grid in Agriculture

It’s still early days, but the writing’s on the wall when it comes to the transfer, collection and management of environmental data. We need a system to better collect it, and manage it – and the analogy of the energy grid is one we developed as a framework for how. This is an oversimplification of how the industry actually works; the reality is that often it's two-way, environmental data is collected and fed back upstream to labs, and it also includes consumers or supply chains downstream from the farmer.

But for now, it’s a good start (would love your feedback on what other analogies might work and what I’m missing). In the case of the Environmental energy grid, I’ve classified the industry into 4 components;

1. Environmental Data Generators (the Power Plants). These are the agencies that generate or process raw environmental data. Sometimes they may also apply an interpretation to that, for example a soil testing laboratory may provide some rough guidance on what a 'good' or 'bad' result looks like. But most of the analysis is left to the interpreter.
2. Environmental Data Interpreters (the Substations). These are the service providers, and Agtech companies that overlay their specific interpretation for the data user. This may be 'what rate of fertiliser to apply to what part of the paddock' based on a Nitrogen result, or it could be the identification of pest and disease using remotely sensed imagery. Either way it involves the specialised interpretation of the data being returned from the generator.
3. Environmental Data Users (the Households). These are more often than not the farmer, but they could also include other Agtech companies or on farm automations that need a layer of interpretation to execute a task on farm (think autonomous spray rigs that require an application map telling it where to apply fertiliser or spray for pests). This segment aren't able to use the raw data by itself, instead it needs to be processed by the data interpreters before it can be used.
4. Data transfer capabilities (the Grid). These are the powerlines that support data transfer, standardisation and management. This provides a system to collect, interpret and sometimes use the environmental data. These are the powerlines that move the electrons, and this is what FarmLab does.

How they interact is outlined in the diagram below:

Data moves through the grid: labs conduct tests and send the results to agronomists, agronomists apply their interpretation to the results and share that interpretation with the farmer, and farmers use this interpretation to make a decision about where and how much fertiliser to apply. The grid provides standardisation and transparency for the data that passes through it.

The challenge right now is that often this transfer happens without that grid. Data is moved slowly offline and often lost. There’s no way for the farmer to look at the results and compare them to last years, remotely sensed data might be looked at in isolation without knowledge of what’s happening under the soil, and farmers are unable to benefit from hindsight given the poor quality of the data they have. As the data moves beyond the farmer, into the supply chain, it’s integrity is eroded or it’s lost entirely. This is an all too common issue with our clients, who might have years of soil tests in their filing cabinets, but no easy way to digitise it and compare it to understand changes over time.

Our vision is that there is a centralised grid to allow for data collection, transfer and management, allowing for better fertiliser application, more transparent carbon markets and supports consumer trust in the agricultural supply chain. To support this we’ve already built a common data standard for soil test results used by our partner labs, as well as implemented standards and tests around soil sample collection for the labs and soil testers we work with across the US. This gives our users the ability to quickly interpret carbon stocks across an area, or identify yield limiting factors across a farm and compare those results back in time.

Conclusion

Agriculture needs environmental data more than ever, and good data at that. Without it we’re leaving a lot on the table when it comes to implementing on-farm efficiencies and mitigating climate change. The challenge is that without the ability to collect and transfer that data easily across the industry we’re going to struggle to support those sustainable initiatives and drivers we need to adopt. This was the premise of FarmLab when we first started back in 2017, and continuing to build the environmental grid to support the industry is going to be our primary focus moving forward. It’s probably not sexy, but it’s needed.