Fig. 5

PCA biplot of the samples of 4 genotypes ( ‘Braeburn’, ‘Kanzi’, ‘Jonagold’, ‘Conference’), showing the location and grouping of the samples in terms of their microstructural characteristics, the measured variables which should be interpreted as vectors with their origin in (0,0). Correlation loadings () situated between the circles (70 and 100 % explained variance limits) are considered most important for explaining the variability with respect to the principal components shown. Correlation loadings based on literature data () for effective oxygen diffusion are added to the biplot. Variables with loadings situated in proximity of each other are correlated. Loadings that make a 90° angle are said to be mostly uncorrelated. Loadings with an 180° angle are inversely related. In this case, an increased porosity is associated with a lower number of cells and voids, with increased respective volumes. Although ‘Conference’ samples have low porosity, they are characterized by a high number of voids, with a high degree of branching. Microstructural shape determinants such as elongation of cells and voids and anisotropy of the tissue are related to each other, but mostly unrelated to other microstructural descriptors. The first 2 PC’s explained 77 % of the total X-variance