AI in Farming: The Hidden Opportunity for Co-ops

Jan de Vries · 2026-05-28

Small farms generate a constant stream of highly valuable data on pest outbreaks, treatment outcomes, climate effects, and soil responses. But after the season ends, these insights are often lost. It doesn't have to be this way, says AI agricultural venture Greenda. Spain is Europe's leading citrus producer, supplying oranges, mandarins, lemons, and other fruits to markets across the continent. But the local agricultural cooperatives that grow your favorite citrus have a hundred responsibilities. They need to maintain consistent crop outcomes across thousands of small, geographically dispersed farms. They also provide farmers agronomic support and ensure regulatory compliance—all at the same time. In practice, that means a small number of agronomists working for these co-ops operate under increasing pressure. They're expected to monitor, advise, and document decisions across hundreds of plots simultaneously. And that model is starting to strain. Recognizing this squeeze, the Greenda team spoke to hundreds of farmers and visited both co-ops and plots. Here's what they heard again and again. ### The Three Big Problems **Info is scattered and trends are invisible.** First, field coverage is structurally limited. Agronomists simply can't physically visit all farms at the frequency that pest and disease dynamics require to act preventatively. Monitoring becomes reactive rather than continuous, often based on sample visits instead of full visibility. Second, administrative and compliance burdens are on the rise. With upcoming regulatory shifts like the EU's digital farm notebook requirements, agronomists spend more time documenting decisions and treatments—and less time in the field where those decisions originate. Third, coordination is fragmented. Farmers often report issues through WhatsApp, phone calls, or other informal channels. Information is scattered across conversations, spreadsheets, and memory. That makes it difficult to detect patterns across regions or synchronize interventions between neighboring plots. > "Valuable field information exists, but it's not structured in a way that can be reused across seasons or aggregated across farms."  ### The Hidden Cost of Disorganization Agronomists and coop managers describe a recurring pattern: valuable field information exists, but it's not structured for reuse across seasons or aggregation across farms. Over time, that leads to predictable inefficiencies practically everywhere: - Overuse of pesticides - Inconsistent treatment timing - Preventable crop losses that only become visible at harvest In other words, there's plenty of scattered signals and data—but systemized intelligence is few and far between. And it's a problem that's inherently solvable.  ### A Smarter Way for Co-ops Munich-based startup Greenda has innovated a workflow and data layer designed to sit between farmers and agronomic expertise. It solves this crucial problem for co-ops (and by extension, for our entire food supply system). Here's how it works: Farmers can submit simple photos of a crop issue through a WhatsApp-like app. The system helps structure the incoming information using AI-assisted analysis, while a certified agronomist reviews each case before any recommendation is returned. That's an excellent feature—but what happens on the cooperative side is what makes it interesting. Instead of fragmented incoming messages, co-ops receive structured, traceable cases that can be prioritized, compared, and tracked over time. Agronomists can see where issues are emerging, how severe they are, and where intervention is most urgent. This transforms the workflow from individual troubleshooting into coordinated field management. As Chadi Nemer, CEO of Greenda, puts it: "Greenda's ambition is to be the platform that defines what good looks like for co-ops. Imagine territory-level intelligence that makes it possible to manage 400 plots with the same quality of attention you'd give 40. Zone-level pest maps, early outbreak signals, automated documentation—the kind of system that turns scattered data into actionable insights." ### Why This Matters for the Future of Food The real opportunity here isn't just about saving time or money. It's about building a smarter, more resilient food system. By capturing and analyzing data from thousands of small farms, co-ops can identify emerging threats before they become crises. They can optimize treatment timing to reduce chemical use. And they can share best practices across their entire network. For US readers, this model could easily translate to American agriculture, where similar challenges exist. The technology is scalable, and the benefits are clear: better crop outcomes, lower costs, and a more sustainable approach to farming. So next time you bite into a juicy orange from Spain, remember the hidden intelligence that made it possible. And know that with tools like Greenda, that intelligence is only going to get smarter.