Likewise, there was a highly significant difference in dry biomass at all tested separation distances (p-value<0.0001) ( Figure 5C ).
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Firstly, using geographic origin as a trait, a highly significant association was found ( AI = 8.8954, P < 0.0001; PS = 69.3392, P < 0.0001) ( Table 2 ).
All main effects such as genotype, trial, and their interaction, were highly significant ( p < 0.0001) for all studied traits.
Discussion Highly significant differences ( p ≤ 0.0001) were observed between the accessions for all of the studied traits (Table 1 ).
wheat landraces Ethiopian tetraploid wheat association analysis yellow rust resistance 90 K wheat SNP array Highly significant differences were observed among accessions and accessions by environments ( P < 0.0001) in ANOVA analyses for stripe rust response in the field tests, but no significant difference was detected among environments.
The measure of population differentiation, F ST , among the subgroups was 0.15 highly significant at P < 0.0001.
Influence of light treatment on plant height was highly significant ( p < 0.0001).
The first component explained the largest portion of the variance, accounting for 41.144% with an eigenvalue of 9.463224, and was highly significant (chi-square = 30699.3, p < 0.0001).
The association between phaseolin type and cluster membership was highly significant and nearly complete (χ 2 = 174.72; df = 1; P < 0.0001; Cramér's V = 0.93).
As shown in Supplementary Table 1 , there were extremely significant differences in phenotype between different environmental conditions ( P < 0.0001).
The analysis of variance for stem rust reaction showed highly significant differences ( P < 0.0001) among accessions included in the whole collection, the durum sub-sample and Q2 group.
Accessions with different polymorphisms at bPb-9668 and bPb-0003 showed highly significant differences in salinity tolerance ( P < 0.0001, Figure 5A ; Supplementary Table S2 ).
Nonetheless, a highly significant and negative correlation between free-ABA and total anthocyanins was observed for both irrigation treatments ( r = −0.76, p ≤ 0.0001) in the 2 years.
Percent total protein decreased in maize seed endosperms transformed with the soybean ferritin transgene The mean percentage total protein differences between PCR positive and negative maize seed endosperm samples were highly significant ( P < 0.0001) (Table 4 ).
A highly significant variation ( P < 0.0001) among the genotypes for both WSC accumulation and remobilization per GDD was found in all environments.
The regressions implicating altitude and latitude of provenances were highly significant ( P < 0.0001), resulting in R 2 ranging between 0.21 and 0.51 (Table 2 ).
The highly significant slopes ( P < 0.0001) between the linear relationships ranged from 0.7 to 1.1, with the weakest relationships apparent for Q. robur (average slope of 0.8 for all methods), likely caused the relatively low amount of detect vessels and its variance between methods.
This correlation is highly significant for the 24 non-agricultural strains ( r 2 = 0.47, P = 0.0002) while it was not significant for the 31 agricultural strains ( r 2 = 0.03, P = 0.33), suggesting that the relationship between aggressiveness and sclerotial production differ among these two populations of strains.
Precisely, PAL was more correlated with the non-reducing sugars ( R 2 =0.9767, p =0.0002) than reducing and total soluble sugars, while anthocyanin exhibited a highly significant correlation with non-reducing sugars ( R 2 =0.969, p =0.0004) and total soluble sugars ( R 2 =0.9686, p =0.0004) compared to the reducing sugars.
Indeed, ABA3 expression kinetics obtained after infection by prtE and outC are not significantly or weakly significantly different from that obtained after buffer inoculation ( p -value = 0.0830 and 0.0411, respectively) in contrast to the highly significant differences between the WT strain ( p -value = 0.0004) or the hrcC mutant ( p -value = 0.0006) and the buffer ( Figure 3 and Supplementary Table S2 ).
Results Correlation Between Physiological and Thermal Variables The correlation between physiological (GFS, starch, frost hardiness and water content) and thermal (minimum, average and maximum temperature averaged over the last 1–30 days before harvest) variables were all highly significant ( P < 0.0005; Table S1 ).
Results obtained from PLS-DA ( Figure 2A ) revealed that metabolic features formed distinct clusters (15 cells in each group), and this difference was highly significant ( p = 5 × 10 -4 ; permutation test in Metaboanalyst 3.0).
Considering that the measured plastidial proteome contains approximately 1,500 proteins ( Zybailov et al., 2008 ), such overlap is 8.5 times more than expected by chance and highly significant (Fisher exact test, p -value = 0.0006).
The differences in FLA value between alleles OsFLA6 AA and OsFLA6 GG were highly significant (Welch's t -test; P = 6.06E−04) ( Figure 3E ).
Under R → RB → R and the reverse sequence, RB → R → RB, fitting the g s data to a linear mixed-effects model ( Tables S8 and S9 ) showed a highly significant effect of light (R-RB-R, p=0.0007;RB-R-RB, p=0.0060), but the main effect of species (R-RB-R, p=0.3455; RB-R-RB, p=0.8859) and its interaction with light (R-RB-R, p=0.2055; RB-R-RB, p=0.7486) were not significantly different.