Excerpts

In contrast, at the ecosystem scale, the difference in WUE Eco between the two sites was highly significant (P < 0.001) ( Figure 4d ), with the mean WUE Eco value in the MPA being significantly higher than that in the SMAH.

Subsequent meta-analysis for seedling emergence across field and GH environments showed that each term or interaction was highly significant ( P < 0.001) in contributing to the total phenotypic variation in both the field and GH conditions ( Table 5 ).

As shown in Table 3 , the SP contents of the SD, MD, MID, and CK were 215.94, 157.71, 200.52, and 300.52 on Day 70, respectively, with highly significant differences between the groups ( p < 0.001).

This efficiency was highly significant (p< 0.001) compared to manual counting, which required 76.1 (± 1.24) seconds for 100 maize seeds and over 93.59 (± 1.84) seconds for 100 smooth pigweed seeds.

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 ).

The effect of “rust infection” was statistically highly significant [repeated measures ANOVA: F (1,10) = 19.815, P = 0.001], as was the interaction of time and rust infection [repeated measures ANOVA: F (4, 40) = 10.665, P < 0.001].

indica showed reduced expression of the FtHCT gene, significantly lower expression of the FtCCOAOM and FtC3H1 genes (p < 0.01), and a highly significant reduction in the expression of the FtCAD6 gene (p < 0.001) compared with the control ( Figure 6B ).

Pearson’s correlations of DArT and GBS markers significant for FT, GY, PH, and Gpt revealed highly significant correlations (P-value ≤ 0.001) between markers identified on common chromosomes (1B, 2D, 5A, and 6A) for the same traits ( Figure 5 ; Supplementary Table S6 ).

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.

Marker RAC875_c8642_231 (M2) had a highly significant positive effect ( P < 0.001) with 43.3 μg g -1 DW ( Figure 4 ).

Location main effect was found to be highly significant ( p < 0.001), confirming its importance in cultivar placement.

AMOVA results showed that the genetic differences between and within populations were extremely significant ( P < 0.001), at 6.01 and 93.99%, respectively, indicating that the genetic differences mainly came from within populations.

Despite these variations, all correlations remained highly significant ( p < 0.001), confirming that the 4K panel captures the fundamental relatedness structure.

Global PERMANOVA revealed that the experimental groups collectively explained a highly significant proportion of ionomic variance (R2 = 0.490, P = 0.001), with homogeneous within-group dispersions confirmed prior to interpretation (Beta-dispersion test, P = 0.753).

Projected GLA values showed highly significant Pearson’s correlations ( p < 0.001) with fresh and dry biomass of wheat plants measured at the end of the experiment, r = 1 and r = 0.98, respectively, thus confirming the reliability of image-based shoot biomass assessment.

For both dry and fresh SLW, a trait that generally tracks well with leaf thickness, the irrigation regime effect was highly significant ( P < 0.001) for the Pima population but nonsignificant ( P > 0.05) for the upland population.

Results Treatment Effects on Plant Traits Including cultivar group and N-level as fixed effects, N-level main effects were highly significant ( p < 0.001) for most traits (Table 2 ).

No significant difference was detected among environments because highly significant correlations ( P < 0.001) were detected among all four field trials ( Supplementary Table S3 ).

SOD activity reached the highest level at the maximal Hg concentration (265.71 ± 7.82 U g –1 min –1 ), and the difference in SOD activity among different Hg treatments was highly significant ( F = 28.755, P < 0.001).

The AMOVA analysis on the 29 accessions ( Table 2 ) prior to grouping revealed a highly significant ( P < 0.001) differentiation among the accessions accounting for 5.4% of the total variation.

Akaike information criterion (AIC) values of segmented regression models for all three factors were significantly lower than those of linear models, and likelihood ratio tests were highly significant ( Supplementary Table 5 , P < 0.001).

cyanus seed number was lower in the two heated treatments relative to the two unheated ones in both years (precipitation had no effect in either additional water treatment); this was highly significant in 2014 (LRT = 30.125, p < 0.001) but non-significant in 2015 ( Table 1 , Figure 4A , and Supplementary Table 6 ).

In this analysis, 19.5% of the total variation was observed among the geographical regions, which is a highly significant differentiation (F CT = 0.20, P < 0.001).

The sowing time × cultivar interaction was highly significant in 2022 ( F = 13.9, p < 0.001) and 2024 ( F = 6.9, p < 0.001), but was weaker in 2023 ( p = 0.049).

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 ).