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How do you analyze test plot data?

Most farmers plant single strips of several hybrids and try to select hybrids for the following year. Single strips are OK for observations but replications can measure variability and give you more reliable results. Consider the following points for analyzing test plot data.

• One location or test is not enough to draw conclusions about the performance of a hybrid or variety but it is a lot better than not planting any test plot at all. However, when combined with information from other unbiased sources, your own test plots become a powerful tool for the selection process, especially when you start accumulating data for several years.

• For analyzing yield data whether from university trials, data from Seed Consultants test plots or third party data, make sure you are looking at data from replicated tests.

• Replications must be randomized which allows every hybrid or variety an equal chance of being on a certain piece of ground or next to a certain treatment as any other. Randomization tends to remove our personal biases and helps us find the real differences.

• In a test, hybrids of similar maturity should be grouped together. Fuller season hybrids generally are taller, have more leaves and higher yield potential than the earlier maturity hybrids. If the hybrids are not properly grouped, shorter and earlier maturity hybrids may be at a disadvantage.

• For reducing variability in the test and improving reliability of data, researchers pick out the most uniform piece of ground in the area.

• Before starting the process of data analysis, you must assume that there is “No difference” among varieties and let the data guide you towards the truth rather than have preconceived notions and try to change or justify the data to get the results you want.

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