Growers can use strip trials on their own farms to test how a particular practice or product performs in a local environment. A strip trial could test, for example, the difference between 60 pounds and 120 pounds of nitrogen fertilizer per acre, or between acres treated or untreated with fungicide. A strip trial could also be used for preliminary evaluation of a novel product.
The primary purpose of the on-farm demonstration is to give the grower an opportunity to try a new management practice or product on a limited acreage to find response areas, both negative and positive, within the particular field. This information can then be used to help decide whether it may be worthwhile to try this new practice or product on a larger proportion of the farm, and to target it at acres with the greatest likelihood of success.
Strip trials are just as they sound. They are long strips of treated/untreated crop within a field, created using a grower’s own field scale equipment. Growers are encouraged to get assistance from an agronomist or extension agent to ensure that proper planning principles and methods are used. This results in a trusted evaluation of a particular practice, method or idea. “Within a field” is important. Many people will treat half the farm with something and make decisions based on those results. Trials side by side within the same field will provide a more accurate comparison.
Keep it simple. Strip trials should be based on only two or three treatments: one that illustrates a new practice or product, one that demonstrates a normal practice, and perhaps a third evaluating an alternative strategy with a similar cost. All else should be equal. If more than two treatments are compared, it will likely make the trial more complicated to plan and properly manage so growers should be realistic about what they can handle. For example, a grower looking at the benefit of a foliar micronutrient could simply have an untreated check versus a strip with the foliar product. Adding a third treatment investing a similar amount in their most limiting macronutrient might provide useful information, but it will require setting up the trial earlier in the season, additional calibrations, or changing blends when fertilizing in spring.
This is not a scientific study. One strip in one field cannot produce statistically significant numbers. There is no replication. Therefore, one cannot judge statistically whether or not there are any real differences between treatments. But while the results might not meet the rules of statistical analysis, growers can use strip trials to get a gut feeling about a product. Strip trials repeated in a field (2-3 treated strips vs 2-3 untreated strips) then again at a few locations across the farm or over a few years will increase the level of confidence in the results. If the strip trial is conducted at enough sites, statistic analysis can be performed on the results.
Choose a uniform field. To achieve the goals of field experimentation, it is crucial to choose a field that is uniform in slope, drainage, and fertility, and that has soil representative of the area. Uniform plots will minimize the natural variation so that any differences that do show up between strips can be attributed directly to the treatments.
Longer plots are better. Studies have shown that field variation (experimental error) is reduced dramatically as plot length is increased. On-farm tests will produce more reliable results as plot length increases from 250 to 750 feet or more. To ensure the best results, plot treatments should be as long as practical within that particular field. As for strip width, it is ideal if the treated width is wider than the intended harvest width. This will ensure that the area harvested keeps fully within the treatment area.
Mark the strips. Use flags and, if available, GPS coordinates to mark each strip. That way you’ll be able to monitor strips through the growing season and harvest strips accurately.
Take it to yield and harvest fairly. Visual comparisons early in the season are not a reliable predictor of yield trends, so it is important to follow through on measuring final yields accurately. When harvesting trials, make sure that all treatments are equal as far as area harvested (width, length, etc.) is concerned. For example in the picture (Figure 1) below, the treatment has standing canola on both sides of the swath ensuring that the full width of the swather was used over the length of the test area. If the length of some plots must be shortened due to odd field shape or problems like flooded out areas, then area harvested must be accurately recorded and all data reported on a per unit area basis (e.g. bushels/acre). Make sure the combine is empty before harvesting each treatment. Weigh each treatment separately, and use a measurement of each strip size to calculate bushels per acre. Weigh wagons are ideal for accurate comparisons. Yield maps can be useful to show variation in the yield trend along the length of the strip and highlighting areas where the difference was greatest, but if using yield monitors, it is important that they are properly calibrated.
Perform an economic analysis. A higher fertilizer rate or a fungicide treatment may produce higher yield, but it also needs to increase profitability. Economic significance occurs when the value of the average treatment effect is greater than the cost of the treatment. To evaluate a return on an investment, one needs to know the average treatment response, expected crop price, and the cost of the treatment. Profitability margins can be calculated using these parameters. Keep in mind that the reliability of this economic comparison will be questionable if based on a single comparison or strip trial, but the accuracy of the average trend will improve as the number of reps or trials conducted increases. Click here for a worksheet to calculate the contribution margin for each treatment and make an economic comparison.
Consider non yield factors. Yield alone may not be the deciding factor in whether a treatment is beneficial for a particular farm or not. Does it reduce operation risk? Does it make yield more predictable? Does it reduce lodging and improve harvestability? Does it improve quality, and thus price? Does it delay maturity and thus increase fall frost risk? These and other factors may influence a decision to use or not use a new product or technique.