Except for MC19, however, there were highly significant ( P ≤ 0.001) correlations between the IR and DR treatments within a site-year and between the Ave_IR and Ave_DR ratings ( r = 0.8, Supplementary Table 3 ).
Excerpts
Varietal differences were highly significant ( P < 0.001) for the majority of all parameters.
Notably, there was a highly significant linear relationship between zinc content in the dry matter of straw (r=0.805, p=<0.001) and milled rice (r=0.726, p=<0.001) with grain yield ( Figure 5 ).
Analysis of variance and broad-sense heritability ANOVA results for all traits and years indicated that genotype was a highly significant factor (p< 0.001) influencing phenotypic variation.
A similar trend was observed between ML and CL, with a highly significant positive correlation (r = 0.69, p < 0.001), reflecting the close association between these parameters at this depth.
Soil TP exhibited a highly significant positive correlation with TN and clay ( P <0.001).
euteiches strains and pea cultivars, as well as their interaction, showed to have a highly significant ( p < 0.001) effect on root dry weight in the growth chamber pot trials ( Table 2 ).
Both Wilk’s Λ and Pillai’s trace were highly significant ( p < 0.001) for each of the single IVs (treatment, exposure time and cultivar), for the two-way interactions (treatment ∗ exposure time, treatment ∗ cultivar, exposure time ∗ cultivar) and the three-way interaction treatment ∗ exposure time ∗ cultivar.
Results and discussion Highly significant differences ( p <0.001) for BSR response among AB-QTL lines were observed disease incidence (DI) in all field seasons, as well as disease rating (DR) and area under the disease progress curve (AUDPC) in the greenhouse with a moderately high broad-sense heritability ( H 2 ) of 0.61 for the tested resistance parameters.
Significant variance components and narrow-sense heritability identified When assessing the 92 populations in the field, population by locations interactions were highly significant ( p ≤ 0.001) for biomass, growth habit and leaf size across years and seasons ( Tables 3 , 4 ).
Variance components across moisture regimes The genotype had a highly significant effect ( p ≤ 0.001, p ≤ 0.01, and p ≤ 0.05) for most of the studied traits except for ASI, SPAD, and KNR under optimal moisture conditions, D50S and EG under drought, and D50 and ASI under waterlogging according to LRT ( Table 2 ).
The results revealed a highly significant difference in genome size between cultivated and wild jujube (U = 22494.0, p < 0.001), with the median genome size of cultivated jujube (3.49 × 10 8 ) being significantly larger than that of wild jujube (3.37 × 10 8 ), and the Common Language Effect Size (CL = 0.355) confirming the practical relevance of this difference.
In most cases, this difference was highly significant ( p < 0.001), with the exception of SNP assay 5 (Wnt-4), SNP assay 9 (Spr-1) and SNP assay 11 (Spr-2) (Figure 4 , Table 5 ).
Yield results showed that all three main effects (hybrids, stand densities, and environments) were highly significant ( p < 0.001), and that the interactions hybrid × stand density and hybrid × environment were also statistically significant for yield ( p < 0.05; Table 4 ).
AMOVA was used to determine that variation among and within groups was highly significant ( P < 0.001), with the clusters capturing 31.5% of the total genetic variations, while 68.3% was explained by individuals within populations ( Table 2 ).
Correlation analysis of vitamin E and chlorophyll components during seed development ( Supplementary Figure S3 ) revealed a highly significant negative correlation across developmental stages (p< 0.001), with correlation intensity varying by genotype.
There was a highly significant difference in cell length between the developmental phases ( X 2 = 234.44; d.f. 2; p < 0.001), which a posthoc Dunn test indicated was significant between each developmental phase (p < 0.001).
ANOVA showed highly significant ( P < 0.001 and P < 0.01) differences among genotypes both for specific locations (Islamabad and Nowshera) and across locations (combined data) ( Table 2 ).
Analysis of variance Pooled analysis of variance demonstrated highly significant effects of genotype, environment, and genotype × environment interaction ( p < 0.001) for all studied characters ( Table 3 ), reflecting substantial genetic variability and pronounced differential responses of genotypes across temperature regimes.
Trait-specific responses of okra genotypes under three PEG 6000 levels The effects of genotypes, treatments, and their interaction were highly significant (p< 0.001) for all the estimated growth, root, and biochemical parameters ( Tables 1 , 2 ).
By August of the second year, the growth differences had become more pronounced, with S1H plants showing highly significant differences in growth compared to plants subjected to the other three treatments (S1N, S2N, S2H) (P<0.001).
Under rainfed conditions, GCA m /sets, GCA f /sets and SCA/sets mean squares were highly significant ( P < 0.001) for all traits except GCA f /sets for BHC, and SCA/sets for HSL, HSW, BHC, and tassel branch length (TBL) ( Table 2 ).
Correlation analysis of quantitative traits Correlation analyses revealed varying degrees of association among oat traits in both cultivation regions, with most trait correlations reaching highly significant levels (P<0.001, Figure 3 ).
3 Results 3.1 Variability of the genotypes for weevil damage parameters All genotypes expressed highly significant differences (P<0.001) for weevil damage at the periphery, cross section, overall total damage, and larvae recovered in pots, whereas adult weevils were not significant (P<0.14).
While all sources of variation exerted a highly significant effect (p < 0.001), the difference among accessions within geographical populations accounted for most of the variation (68.3%), whereas only 6% was explained by the difference among the geographical populations.