Journal: Scientific Reports

Article Title: Genetic variation and heritability of agronomic traits in a native perennial forage species from drylands: breeding potential of Festuca pallescens

doi: 10.1038/s41598-025-90875-7

Figure Lengend Snippet: Correlation plot showing only significant relationships among the analyzed variables, with p-values < 0.01. Correlations are represented with a color scale ranging from blue (strong positive correlations) to red (strong negative correlations). Red labels represent phenological variables, while green labels correspond to morphological variables. Pearson’s r coefficients are displayed in bold inside the plot. Non-significant correlations (p ≥ 0.01) are excluded from the plot. SP = seed production; F1 , F2 and F5 = pheno-phases of the reproductive cycle in days from the 1 st of July; RC = duration of the reproductive cycle; V = estimated crown volume and T = tiller production. GS = growing season.

Article Snippet: We calculated the 95% confidence intervals for these distributions using the ‘quantile’ (Type-8) function in RStudio ; this quantile type is approximately median unbiased, regardless of the variable’s distribution .

Techniques:

Journal: Scientific Reports

Article Title: Genetic variation and heritability of agronomic traits in a native perennial forage species from drylands: breeding potential of Festuca pallescens

doi: 10.1038/s41598-025-90875-7

Figure Lengend Snippet: Q ST Distributions and confidence intervals for F. pallescens traits. Each plot shows a simulated Q ST distribution with a 95% confidence interval (blue dotted line) and observed Q ST (red dotted line) for all variables measured on the half-sib trial of F. pallescens . SP = seed production; F1 , F2 and F5 = pheno-phases of the reproductive cycle; RC = duration of the reproductive cycle; V = estimated crown volume and T = tiller production. Only the first year of measurements is shown, following years behaved similarly.

Article Snippet: We calculated the 95% confidence intervals for these distributions using the ‘quantile’ (Type-8) function in RStudio ; this quantile type is approximately median unbiased, regardless of the variable’s distribution .

Techniques: