The aim of this study was to compare different methods for analyzing
data from a field breeding experiment with check plots where soil
variability was controlled with the use of statistical and geostatistical
methods. The analyzed data were obtained from field experiments
investigating the yield of camelina Camelina sativa L. Crantz and crambe
Crambe hispanica ssp. abyssinica Hochst. ex R.E. Fr. Prina seeds in the
temperate climate of north-eastern Poland. Analysis of variance models
with a completely randomized design, a randomized block design, and
analysis of covariance were compared. In the vast majority of cases, the
values of statistical information criteria demonstrated that the best
model was the analysis of covariance where the theoretical seed yield
from the check plot, interpolated with a geostatistical method, was the
covariate. The results of this study can be useful for testing new cultivars
in large-scale commercial farms with variable soil conditions to identify
the optimal genotype for the local environmental and climatic
conditions.