Table 1.
Accession list containing some basic information.
Table 2.
Agro-morphological trait values.
Fig 1.
Dendrogram obtained from agro-morphological traits of 84 oat landraces using Ward’s algorithm with three major clusters marked by dashed line.
Fig 2.
Principal components analysis results based on agro-morphological traits.
Bi-plots of the first two principal components F1 and F2. a) PCA including bi-plots based on agro-morphological traits; b) PCA plot with accessions coded by high or low yield; c) PCA plot with accessions coded by high or low thousand seed weight.
Table 3.
Values of Pearson’s correlation coefficient among the agro-morphological traits.
Table 4.
ISSR Primers statistics.
Fig 3.
Dendrogram obtained from ISSR data of 91 oat landraces using Ward’s algorithm.
Fig 4.
The principal coordinate analysis results based on ISSR data.
Bi-plots of the first two principal coordinates F1 and F2. a) based on pair-wise Nei genetic distances among accessions, b) based on Nei genetic distance calculated between all individual plants.
Fig 5.
Inference of the population structure of Avena sativa landrace collection based on ISSRs using a mode-based Bayesian clustering carried out using the Structure software [35].
The plots were generated based on the Q-matrix consensus permuted across ten replications for k = 2, 3 and 5, using the CLUMPP software [37]. The H’ value indicates the similarity coefficient between ten runs of each k. Each vertical thin bar represents an individual within an accession that is marked by a black border and number. Each number represents a single accession and is consistent with the numbers in Table 1. The assignment of each individual to different gene pools is shown for k = 2, 3 and 5.
Fig 6.
Results of the optimal subpopulation model investigation by plotting ΔK of the data over ten runs, as implemented in Structure Harvester [36].
Table 5.
Results of the Mantel test.