I’ll take your 1-mile setback and raise you 3. 

Balancing Science and Assumptions in Food Safety 

First attempts are rarely the best. That applies to just about everything—including writing and food safety practices. This document has been edited many times, and that doesn’t make the first version wrong or useless—it’s simply part of the iterative process of finding the best way to communicate a message. The same principle holds true in food safety. 

In produce food safety, we often manage “known unknowns.” Environmental conditions change constantly, usually beyond the control of the grower. Decisions are made based on the best available information at the time—what we might call educated guesses. While well-intentioned, these guesses can resemble hopeful assumptions more than science-based risk management. 

The solution? Invest in research and data collection to better understand the risks and refine practices accordingly. It’s a natural progression: we start with a best guess, we collect data, we reassess. But what happens when new evidence contradicts that original guess? 

That’s where things get complicated. If the original guess aligns with new data, it’s easier to validate and formalize. But more often, early assumptions fall short. This introduces a challenge: how do we justify changing an accepted industry standard that was originally based on a guess? 

This is the danger of “the first requirement”. By being “first,” it becomes the default, and soon it’s embedded in systems, policies, and contracts. Over time, it gains weight that may outweigh newer, more accurate information. Even if new research data shows the original approach was flawed or incomplete, shifting away from it becomes difficult. As a result, tension grows between established practices and emerging science. 

This situation is particularly visible in the fresh produce sector, where food safety risks are both serious and extremely complex. One example is the management of risks from adjacent land uses—animal operations, composting facilities, and wildlife habitat. These areas are known sources of microbial pathogens like Salmonella and pathogenic E. coli. Setback distances (buffers) are established to manage the potential for contamination, sometimes based on data, but often grounded in the logic that “more distance must be better.” 

But are those distances really effective? Maybe—but maybe not. And each year, the market tendency towards continuous risk reduction is to increase setback distance requirements, reinforcing the idea that more distance must be better. However, growing research shows that while distance matters, it is far from the only factor that matters, and many other factors, often unique to a specific location, are interacting that drive heightened risk.  

Recent work by Dr. Mohit Verma at Purdue University, funded by the Center for Produce Safety, measured fecal indicators, Bacteroidales, in air samples taken in fields near animal operations. The findings showed that setback distance alone could only predict airborne contamination with Bacteroidales from animal operations with 12–54% accuracy. That’s a very wide and uncertain range. The takeaway here isn’t that setbacks are unnecessary—but that setback distances alone are insufficient to effectively manage risk. In short, on the topic of setback distances, the appropriate setback distance is very much “IT DEPENDS!”  

So, what should the industry do? 

We need to listen, understand and appropriately apply the science to drive pragmatic food safety requirements specific to certain locations. Risk is multifactorial. Distance is only one part of the equation. Rather than defaulting to single-variable design requirements, we should be developing strategies that account for the full range of contributing factors for a site. That’s not easy, but it’s necessary. 

When best guesses harden into standards without reassessment, they can slow progress. They consume resources, create ineffective systems to manage, and limit exploration of more sustainable or effective solutions. Continuing to support research, collecting high-quality data, and being willing to revise practices when the evidence points to a better path—this is how we must move forward.  

The true cost of sticking with flawed assumptions is stagnation and creating non-sustainable food safety systems. We owe it to growers, consumers, and the broader food system to stay open to change and invest in better ways to manage risk. Let’s listen to the science and use it to drive targeted, customized risk management solutions appropriate for each situation and site.