Have you ever wondered about on-farm trials? Louis Longchamps, assistant professor of digital agronomy at Cornell University, recently explained how it works as he presented “On-Farm Experimentation and Biologicals” as part of the Soil Health & Climate Resiliency Field Day at Rodman Lott & Son Farms.

Longchamps’s research includes developing methods of precision agriculture at the Farmers DataLab.

“Progress in agriculture – when you look at the long-term, it has happened through endogenous experimentation,” Longchamps said. (Endogenous means “growing or originating from within an organism.”)

He listed the pros of on-farm experimentation – it’s at the scale of production; it’s adapted to the farm; it’s directly relevant to the farmer; it’s contextualized; there’s training while developing; and it provides evidence and is agile.

But it also bears a few cons, such as it’s specific to each site. It can be risky and slow overall. Since the research is particular to one site at one farm, the outcomes may not be as applicable elsewhere.

“Most of the time, we are after information that is general,” Longchamps said. “When you look at the whole landscape of research, it goes from fundamental research through the filter of an on-farm experimentation.”

Louis Longchamps is an assistant professor of digital agronomy at Cornell University. Photo by Deborah J. Sergeant

He added that controlling factors in an on-farm experiment can yield results that promote systemic progress, establish causality and provide generic knowledge that’s trustworthy. But applying this on a working farm can also become too complex and rigid. It can ignore the context of the farm and it requires transfer elsewhere.

“It creates a disconnect between scientific research and the real world,” Longchamps said. And the time and resources can prove taxing.

“Farmers are not too keen on the complex scientific process,” he said, but added that whatever can be done to contextualize data can be helpful.

So how do farms join an on-farm experiment? It begins with engaging farmers – getting the word out about a research project that needs working farms in order to happen.

Once farmers agree to join the project and it’s underway, researchers need to acquire data. This could be soil and/or crop samples. The data recorded from these needs to be “cleaned” and assembled so that researchers can organize it.

The next step is analysis. What does the information mean? How could farmers use it? Then researchers can host workshops to share and discuss the information with other farmers.

Following endogenous experimentation, farmers may misinterpret information. Digital agronomy can assist researchers in completing more complex and far-reaching research. This can yield results that would apply more accurately at more farms since it can include results from similar projects.

Digital agronomy can also help document data, pool data from more farms and use advanced analytics to better understand the facts gathered.

“Farmer-led on-farm experimentation enhanced by digital ag is a new way for farmers and scientists to collaborate and advance agronomy,” Longchamps said. “On-farm experimentation can help find conclusions at the plot scale and find trends and patterns at the network scale.”

He added that the Farmers DataLab is working on ways to minimize the “pain” of on-farm research and maximize the benefits to farmers.

by Deborah Jeanne Sergeant