![]() The dataset has five columns, the ‘Year’, the ‘Genotype’, the fertilisation level (‘N’), the ‘Block’ and the response variable, i.e. ‘Yield’. It provides the results for a split-plot experiment with 15 genotypes and 2 N fertilisation treatments, laid-out in three blocks and repeated in four years (360 observations, in all). Please, look at the dataset ‘kamut.csv’, which is available on github. What could we expect from such an experiment? As usual in agricultural research, the experiment should be repeated in different years, in order to explore the environmental variability of results. Genotypes would be randomly allocated to main plots, while fertilisation systems would be randomly allocated to sub-plots. Genotypes require bigger plots, with respect to fertilisation treatments and, therefore, the most convenient choice would be to lay-out the experiment as a split-plot, in a randomised complete block design. Let’s imagine a field experiment, where different genotypes of khorasan wheat are to be compared under different nitrogen (N) fertilisation systems. A repeated split-plot experiment with heteroscedastic errors
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