The impact of big data on agriculture is growing and growing as farmers gain the ability to make more precise and efficient decisions.  The latest example comes via a paper from the University of Illinois at Urbana-Champaign that describes a new algorithm designed to help farmers efficiently pick crops.

The aim is to enable farmers to efficiently manage the workforce that is still largely required to pick crops by hand, such as strawberries and other perishables.

“One of the aspects that I’m interested in is the fact that there are humans involved in picking,” the researchers say. “Just like Internet browsing history differs from person to person, along similar lines, a workers’ ability to harvest strawberries is different. This brings up the question: how do you think about data in that industry? Because the human variability has a huge effect.”

Bringing data to the field

So getting data from the field can be crucial in understanding exactly what’s happening, and whether certain parts are producing higher or lower quality harvest.  The challenge is acquiring that data without requiring the workers themselves to perform data entry work.  The solution was to monitor each worker using the GPS that is built into their smartphone.  An algorithm was then used to harvest that data and predict the number of completed boxes for each worker.

The team hope that the work will lead to much more precise methods of harvesting, and it has already produced some interesting insights.  For instance, they believe data will allow workers to be coordinated more effectively so there aren’t bottlenecks at the quality control points.

“At the moment, we’re just trying to track,” they say. “You can’t manage what you can’t measure. We’re trying to measure what is going on in the field actually in the field, not at the edge of the field where data is currently being collected. If you know moment by moment how much is being harvested, you can better schedule, rearrange harvest crews or re-task.”

This kind of efficiency saving could be crucial in an industry where margins are wafer thin.  Suffice to say, there is a lot of work required before the project gets to that point, and the team plan to refine it further in the coming months.  They are confident however that the agriculture industry is beginning to appreciate the role data can play in their work.

Check out the video below to learn more about the project.