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University of Minnesota Extension

How to do research on your farm

Experiments are hard work and can be difficult to design and analyze. The University of Minnesota conducts many agronomic experiments, as do other public institutions and agricultural companies.

Even with this abundance of information, you may want to conduct your own on-farm experiment/trial. For example, you may:

  • Want to test agronomic practices or products that you can’t find adequate information about.

  • Have a unique condition on your farm that you think would produce atypical results.

  • Have a healthy skepticism and need to see things for yourself. For example, you might want to compare yields of corn hybrids, a foliar fungicide compared to not treating or how two tillage systems affect soybean yield.

Below, we provide some advice for planning and analyzing your experiments.

Conducting your own on-farm experiments


Interpreting your experiment’s results

Just like deciding on and placing your treatments, how you interpret the results can make a big difference in the conclusions’ usefulness.

Here, we’ll assume we’re comparing yield between two or three treatments and that yields follow the normal distribution (the bell-shaped curve). The curve’s shape will determine how easy it’ll be to draw good conclusions from your data.


Spreadsheet for making comparisons

We’ve prepared an Excel spreadsheet for comparing two or three treatments using a two-tailed t-test. With the spreadsheet, you can:

  • Select the precision (80, 90 or 95 percent confidence interval) for your comparison and enter three to eight replicated samples for each treatment. Use real replicates, not the pseudo replicates mentioned earlier.

  • Experiment with different replicate sample averages and variabilities, replicate numbers and confidence intervals.

  • Compare yield, plant populations, percent control for crop protection chemicals and other treatments.

Tips for on-farm research

  • Don’t try to compare too many treatments in one trial. If you’re trying to compare more than three or four treatments, seek help from a statistician.

  • Make sure you have a control treatment. Include a common treatment or untreated plots in your comparison.

  • Avoid placing treatments in locations that would affect treatments differently—for example, consider cropping history and soil factors.

  • Include replications. You need three or more replicates (plots for each treatment) to determine the consistency of results. Multiple samples from the same plot or strip isn’t replication; those are pseudo replications.

  • Randomize the order of your treatment plots or strips in the field. This refers to the planting order of varieties, or which plots receive which varieties.

  • Understand how variability influences your ability to draw conclusions. Do you want to risk calling treatments different when they’re essentially the same? Or do you want to risk not finding real treatment differences?

  • Don’t over-extrapolate and assume the rest of your experiment has to be valid for other fields.

More guidance on conducting research on your farm

Paulo Pagliari, nutrient management specialist, Southwest Research and Outreach Center and Bruce Potter, integrated pest management specialist, Southwest Research and Outreach Center

Reviewed in 2022

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