Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis |
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Authors: | H. -P. Piepho |
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Affiliation: | (1) Faculty of Agriculture, University of Kassel, Steinstrasse 19, 37213 Witzenhausen, Germany |
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Abstract: | Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets. |
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Keywords: | Two-way classification Genotype x environment interaction Additive main effects multiplicative interaction Best linear unbiased prediction Predictive accuracy Cross validation |
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