Abstract
Evaluation data from germplasm collections obtained across many years is often very unbalanced and sparse. For making efficient use of these data, it is desirable to compute summary statistics such as means. The simple arithmetic mean is not a useful measure, because due to the unbalancedness it may yield biased and thus misleading information. Some form of adjustment for diverging environmental effects is therefore needed. In this paper we advocate the use of a simple and well known least squares method to compute adjusted means. The method is exemplified using a published example on wheat (Triticum aestivum L.).
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Piepho, H. Model-based mean adjustment in quantitative germplasm evaluation data. Genetic Resources and Crop Evolution 50, 281–290 (2003). https://doi.org/10.1023/A:1023503900759
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DOI: https://doi.org/10.1023/A:1023503900759