As harvest progresses across the Eastern Corn Belt, seed companies, universities, and growers will have the chance to compile and analyze data from yield testing. One of the most important decisions a farmer will face all year is deciding what variety to plant and in which field to plant it. To ensure that the best possible decision is made next spring, it is important to spend some time looking at yield data. While reviewing data is critical, knowing how to determine whether it is accurate and useful is equally important. Below are some tips for using data to make sound planting decisions next spring.
Look for replicated data
Don’t rely on yield results from one strip plot on a farm or from a single plot location. Look for data from randomized tests that are repeated multiple times and across multiple locations. Replications in testing increase the reliability of the data and helps to remove variables that can skew results.
For strip plot data, was a “tester” used?
Strip plots planted on farms can cover large areas of a field. In many fields in the Eastern Corn Belt there are several soil types. If a plot crosses several soil types how can you be sure it is accurate? By planting a “tester” variety at regular intervals within the plot, you can calculate adjusted yields based on the variability of the tester yield across the plot. The use of a tester minimizes the effect soil type variability has on the plot results to ensure more accurate data.
Look for consistency
According to Bob Nielsen, Purdue Extension Agronomist, “Documented consistency in yield performance is still the key to success in selecting hybrids that will perform well in your farming operation.” When choosing a variety based on plot data, it is important to look for consistent performance—across several plot locations and between multiple years. Choose varieties that consistently performed well in 2016 and 2017, in multiple locations, and different growing conditions.
On published data look for foot notes that indicate the least statistically significant yield difference, or LSD. In many plots, the performance of the top 5 or 10 varieties may not be statistically different. Although there are small differences in yield, statistical analysis of the data indicates that all varieties within the LSD have an equal chance of winning the plot.
While plot data can be very useful in making decisions, some plot data is significantly more accurate and reliable. The key to getting the most out of yield data is having the ability to sort through the large amounts of information to identify the data that most accurately and reliably represents varietal performance.