Excerpts

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).

Agronomical traits Differences among lines were highly significant ( p < 0.001) for all evaluated traits, indicating wide phenotypic variation ( Table 2 ).

Results Combined AMMI-analysis revealed highly significant (p <0.001) effects of genotype and environment on grain yield, iron (Fe), and zinc (Zn), together with significant GEI for most traits.

The correlations of reproductive traits of winter wheat in different environments were compared in the figure, from which it can be seen that most of the winter wheat reproductive traits reached the highly significant level (p<0.001).The correlations of S1 stage traits in E1 environment were -0.02-0.67, and the correlations of S2 stage traits in E1 environment were 0.22-0.55; and the correlations of S1 stage traits in E2 environment were 0.37-0.55; and the correlations of S2 stage traits in E3 and E4 environments were 0.37-0.55. correlation was 0.37-0.63 for S1 stage trait in E2 environment and 0.45-0.62 for S2 stage trait in E2 environment; correlation of S1 stage trait in E3 environment was 0.41-0.62 and correlation of S2 stage trait in E4 environment was 0.36-0.62.

Analysis of variance for root and yield traits The ANOVA for root traits under the hydroponics platform ( Table 2 ) revealed highly significant differences among genotypes (p< 0.001), traits (p< 0.001), and genotype × trait interaction (p< 0.001), indicating substantial genetic variability and trait-specific effects.

Highly significant (p < 0.001) elevation of IVTDMD was also recorded in mutant lines Msc3h-013 and Msc3h-158 with a relative advantage of 8% and 10% over EV, respectively ( Figure 4E , Supplementary Table S1 ), followed by Msc3h-121 with a relative advantage of 5% over EV, which was not statistically significant ( Figure 4E , Supplementary Table S1 ).

Species identity effects on stand productivity and biomass partitioning Comparing the pot-level productivity of the 16 (moist treatment) or 11 species combinations (dry treatment) with Two-way ANOVA revealed highly significant effects of the species combination [F (15, 169) = 3.75, p < 0.001] and of the moisture treatment [ F (1, 183) = 38.28, p < 0.001] on RGR total .

Results In this study, the genetic correlations between female flowering (FF) and male flowering (MF) remained consistent across all environments ( Figure 2 ) with a positive correlation (r > 0.82) and highly significant (p<0.001).

Highly significant main effects of PGR type (df = 2, Wald χ2 = 20538.041, P < 0.001; df = 2, Wald χ2 = 75.219, P < 0.001; df = 2, Wald χ2 = 1961.779, P < 0.001) and PGR concentration (df = 3, Wald χ2 = 7854.678, P < 0.001; df = 3, Wald χ2 = 186.271, P < 0.001; df = 3, Wald χ2 = 1570.579, P < 0.001) were detected for callus induction rates.

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.

3.2.2 Grain yield The factorial ANOVA revealed that nitrogen availability was the dominant factor influencing quinoa grain yield, with a highly significant main effect (P < 0.001; Supplementary Table 2 ).

(1) ANOVA revealed highly significant differences in germination rates among treatments (p < 0.001).

Although marginally significant ( p = 0.001), the height of transgenic plants was only 8% lower than that of Columbia compared to ∼40% reduction seen in 3KO plants (Figure 1 E).

The ANOVA revealed a highly significant effect of the genotype on Waudpc ( P < 0.001) ( Table 3 ).

It also revealed three PCs with highly significant differences (p<0.001) and the first three interaction principal component of AMMI, explaining 47%, 26.62%, and 17.88% of the GEI with 19, 17, and 15 degrees of freedom (df), respectively, as well as the fourth PC with significant differences (p<0.05) explaining 7.77% of the interaction with the degree with total cumulative of nearly 100%.

Plant vigor and tuber yield displayed a positive and highly significant correlation (0.69, p<0.001).

Paired statistical tests confirmed that differences between CK and 150 NaCl were all highly significant (p < 0.001).

Highly significant genetic variations ( p < 0.001) were observed for the BSR disease in the field and greenhouse with a moderately high broad-sense heritability ( H 2 ) ranging from 0.66 to 0.73.

Highly significant ( p < 0.001) and positive associations were observed among agronomic attributes, N uptake, NUE, and crop water productivity of upland rice in correlation assessment.

A slight downregulation of AT5G17700 in atml1 mutants (1.9-fold higher expression in Col_WT versus atml1 ) did not reach statistical significance ( p = 1.2 ⋅ 10 -3 , but padj = 1 after multiple testing correction).

On the other hand, inoculated plants expressed a highly significant and positive correlation (R = 0.6, p = p = 0.0014** ) between the inorganic “Pi” content and total P, indicating that PSB isolates likely contribute to a better internal P use efficiency ( Figure 2B ).

Comparative analysis of these two pooled datasets showed a highly significant difference in insect feeding preference, with tissue infiltrated with non-trichome-inducing Agrobacterium strains preferentially eaten (P = 0.002, Student’s t-test) ( Figure 4B ).

Tree-ring width and earlywood width exhibited a decreasing trend from pith to bark ( p = 0.002 and p < 0.001), whereas latewood width remained constant.

Among all accessions, there was significant or marginally significant variation in average A under fluctuating PPFD ( p = 0.002, 1.50-fold variation among accessions, Figure 4A ), average g s under fluctuating PPFD ( p = 0.037, 1.78-fold variation among accessions, Figure 4B ), and average iWUE under fluctuating PPFD ( p = 0.069, 1.22-fold variation among accessions,

Correlation analysis revealed several highly significant negative correlations among the traits: AC and ATC (r=-0.675, p=0.002), AC and ATR (r=-0.984, p<0.001), and AC and ATA (r=-0.638, p=0.003).