Higher yields, greater efficiency, reduced environmental impact! This may sound like a sales pitch for snake oil, but it could also represent the legitimate objectives for a sustainable farm operation. Increasingly, farmers are generating on-farm research data on a wide range of practical topics. However, the proper methods of setting up on-farm experiments so that the data is statistically valid are not necessarily common knowledge.
The first step in setting up an on-farm trial is to choose the specific topic to be tested. While this may seem simple, it is important that the topic not be too complex. For example, a producer may be interested in how different corn hybrids react to increasing rates of fertilizer at different plant populations and planting dates. While this sounds like an interesting experiment, it is simply too complex for an on-farm trial. With three different options for each factor (e.g. three hybrids, three fertilizer 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.
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. Laying out an experiment in an area of a field known to have a lot of variability weakens the data generated from the experiment. The underlying variability could make it almost impossible to detect treatment differences if they exist. If variability in the field is not accounted for, you would not be able to tell if any yield differences were due to the treatment or simply differences in soil type, drainage, or some other factor unrelated to the treatment. However, if a field has a uniform pattern (i.e. increasing productivity north to south) laying out the plots so that the treatments follow this pattern is acceptable. In the illustration below (Figure 1), the plots should be laid out as shown in the field at left rather than the field at right.
As discussed in our previous Agronomy eUpdate article (Replicated Comparisons vs. Side-by-Side Comparisons), replication is vital, as is randomization of treatments within a replication. Replication and randomization will help you determine if any differences you see are due to chance, error, or variability for which you otherwise can’t account. The actual experimental design will depend on the variables to be studied. Thankfully, Extension personnel in your state will likely be able to help set up the experiment for you.
Figure 2 shows an example of a 36-acre field taken from the Web Soil Survey. This field has two different soil types, although many fields across the North Central Region have much more variability than this. Soil type A is a fairly productive silt loam while soil type B is a much less productive silty clay loam. If the field was simply split vertically down the middle into two different treatments, the results would be very misleading. However, if treatments were laid out in replicated blocks running from left to right, the variability would be nearly equally distributed across treatments, making for a valid comparison.
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. Considering the current economics of production agriculture, producers are finding more value in answering questions using on-farm research methods in their own fields. 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. Following these steps can greatly assist in generating broadly applicable data. If you have interest in doing research on your farm, contact your local extension office.
This article is part two in a four-part series of articles on agricultural research and interpretation by University Extension Educators in the North Central Region.
John Thomas, Cropping Systems Extension Educator, University of Nebraska-Lincoln
Sara Berg, Extension Agronomy Field Specialist, South Dakota State University
Josh Coltrain, Wildcat District Crops and Soils Agent, K-State Research and Extension
Lizabeth Stahl, Extension Educator - Crops, University of Minnesota