Higher yields, greater efficiency, reduced environmental impact! This may sound like a used-car dealership sales pitch, but it could represent the objectives that make an operation sustainable.

“Increasingly, farmers are generating on-farm research data which encompasses a wide-range of practical topics. However, setting up those experiments so that the data is statistically valid is not necessarily common knowledge,” said Sara Berg, SDSU Extension Agronomy Field Specialist.

Berg is among a research team made up of extension staff from Kansas State University, University of Minnesota and University of Nebraska Lincoln who are reviewing techniques and developing best management practices for on-farm research trials. Other extension staff include: Josh Coltrain, Kansas State University; Lizabeth Stahl, University of Minnesota and John Thomas, University of Nebraska Lincoln.

“On-farm research can be a valuable tool for farmers. As new products and technology emerge in our ever-changing field, new questions and methods arise,” Berg said. “Considering the current economics of production agriculture, producers are finding more value in answering questions using on-farm research methods in their own fields.” 

The team’s research found that choosing a topic of interest, setting up the test on a uniform field area and using proper experimental design and replication, are key parts of a successful on-farm experiment.

Start with topic of interest

Based on their research, the first step in setting up an on-farm trial is to choose a topic of interest.

“While this may seem simple, one important factor that must be considered is that the topic cannot be too complex,” Berg explained.

For example, a producer may be interested in how different corn hybrids react with increasing rates of fertilizer at different planting populations and planting dates.

“While this sounds like an interesting experiment,” Berg said, “the complexity is simply too great for an on-farm trial.”

She explained further. “With three different options for each factor (e.g. three hybrids, three rates, etc.) there would 81 different treatment combinations in a single replication. In this case choosing one of the factors to study (i.e. plant population) would be recommended,” she said.

Best location for trial

The next step is to choose an area of a field with limited variability.

“To successfully do this, prior knowledge of the field is a must,” said Josh Coltrain, Kansas State University Crops and Soils Educator. “Laying out an experiment in an area of a field with preexisting variability weakens the data generated from the experiment.”

The underlying variability, Coltrain explained, could make it almost impossible to detect treatment differences if they exist. 

“If variability in the field is not accounted for, producers could end up conducting the study but not be able to tell if any yield differences were due to differences in soil type, drainage, etc., or the treatment,” he said.

The best location for test plots is in fields that are uniform or have a uniform pattern.

Replication & Randomization

Replication and randomization of treatments within a replication is vital.

“Replication and randomization help you determine if any differences you see might be due to chance, error or variability you can’t account for,” Berg said. “The actual experimental design however, will depend on the variables to be studied.”

For help in determining the best plot layout, contact SDSU Extension staff. Berg and the team recently published an article discussing these findings in depth [read this article].