In the studies on selection and population genetics of forest trees that include the analysis of genotype × environment interaction (GE), the use of biplot graphs is relatively rare. This article describes the models and analytic methods useful in the biplot graphs, which enable the analyses of mega-environments, selection of the testing environment, as well as the evaluation of genotype stability. The main method presented in the paper is the GGE biplot method (G - genotype effect, GE -genotype × environment interaction effect). At the same time, other methods have also been referred to, such as, SVD (singular value decomposition), PCA (principal component analysis), linear-bilinear SREG model (sites regression), linear-bilinear GREG model (genotypes regression) and AMMI (additive main effects multiplicative interaction). The potential of biplot method is presented based on the data on growth height of 20 European beech genotypes (Fagus sylvatica L.), generated from real data concerning selection trials and carried out in 5 different environments. The combined ANOVA was performed using fixed- -effects, as well as mixed-effects models, and significant interaction GE was shown. The GGE biplot graphs were constructed using PCA. The first principal component (GGE1) explained 54%, and the second (GGE2) explained more than 23% of the total variation. The similarity between environments was evaluated by means of the AEC method, which allowed us to determine one mega-environment that comprised of 4 environments. None of the tested environments represented the ideal one for trial on genotype selection. The GGE biplot graphs enabled: (a) the detection of a stable genotype in terms of tree height (high and low), (b) the genotype evaluation by ranking with respect to the height and genotype stability, (c) determination of an ideal genotype, (d) the comparison of genotypes in 2 chosen environments.

The aim of this research was to assess the effect of nitrogen and carbon dioxide as well as of two methods of their application, i.e. the gas blanket method and the flushing method on the oxidation rate of the fully refined rapeseed oil. Both gases effectively reduced the oxidative changes in the tested rapeseed oil, however, carbon dioxide proved to be more effective in protecting the oil against oxidation compared to nitrogen. The peroxide values obtained in the Schaal oven test and the long‐term storage test were, in both methods, significantly lower when using carbon dioxide than when using nitrogen. In the long storing test, carbon dioxide significantly reduced the p‐anisidine value compared to nitrogen, regardless of the method used. The continuous flushing of oil with nitrogen or carbon dioxide protected the oil against oxidation almost completely, even at high temperatures (120°C). The oxygen dissolved in oil does not have any impact on oil oxidation.

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In order to determine the adaptive potential of silver fir in the southeast of Poland, the stability of the height of its five-year-old progeny was analyzed. The study was conducted in two different population groups in a total of four environments, including one ecologically marginal environment. The linear mixed model was used to evaluate the differentiation of populations in terms of height growth. The genotype and genotype-by-environment interaction biplot (GGE) were used to verify the stability of height. The climate of populations origin, in relation to actual fir distribution in Poland, was verified based on principal components analysis (PCA) of bioclimatic parameters. The highest total variability was explained by the genotype-environment interaction effect (GE) (54.50%), while the genotype effect (G) explained 41.27% and only 4.23% was explained by the site effect. The result of height growth variations revealed the Komańcza site as the most representative among study sites, while the Lesko site characterized the highest discriminating ability. The progeny occurring in climatic conditions most different from the average testing conditions showed a heterogeneous growth reaction, only adapting to the marginal environment, while the progeny of the second population in this region as well as the northernmost one was characterized by a mean but stable growth. The westernmost population revealed maladaptation. The assessment of the adaptability of silver fir depends on the broad spectrum of test conditions considering the ecologically marginal environments.

Background: The productive potential of European species of forest tree assumes particular importance in the context of populations adapting to accelerating climatic change. Genotype-environment interaction (G × E) was studied to determine Picea abies (L.) H.Karst. (Norway spruce) inter-population variation, characterising their adaptability to the growing conditions in northeastern Poland. The data were analysed from 22 populations evaluated in four experimental sites based on 5-year height. To identify best-adapted as well as specifically adapted populations, GGE biplots were performed. Findings: Analysis of multi-environment trial (MET) data revealed significant differences between four experimental sites, as well as interactions between populations and sites. However, it proved possible to identify specifically adapted populations achieving high values for the trait at specific sites only, although some performed relatively well across several sites. Conclusions: The productive potential of the Norway spruce populations in northeastern Poland is associated with specific adaptation of given populations to growth conditions at the experimental sites. However, in the set of populations studied can also be found some capable of average but stable growth in all experimental sites.