Excerpts

Generally, the VIs had a better relationship with Pn at the jointing–booting stage, but the r value became worse as the growth stage advanced; however, it might be that the number of samples was relatively small and therefore no VIs passed the highly significant correlation test ( p < 0.01).

A highly significant positive correlation (P<0.01) was observed between maize root morphology (length: r=0.959, 0.970, and 0.947; surface area: r=0.947, 0.956, and 0.980) and the activities of key antioxidant enzymes (SOD, APX, GR), suggesting that root system development substantially enhances the maize enzymatic antioxidant capacity.

It can be observed from the figure that there is a highly significant correlation (p<0.01) between the number of days of waterlogging and the wheat yield rate.

In the dataset comprising 48 isogenic pairs, the heritabilities for the BS39+SHGD group (PH: 0.70; EH: 0.70) were significantly higher than those of the BS39 group (PH: 0.30; EH: 0.56), with the difference being statistically highly significant (p=0.01).

After 50d of storage, there was a highly significant difference (P<0.01) between the PEHC and the control in terms of good fruit rate, with the PEHC of kiwifruit having a higher good fruit rate than the control. 3.3.2.

3.2 Correlation analysis Correlation analysis of the morphological indicators revealed that there was a highly significant ( p < 0.01) positive correlation among the maximum root length, shoot length, and biomass in all correlation analyses ( Figures 2A–D ).

The significance test ( p > 0.05) was passed by the regions that accounted for 23.75% of the total area, while the highly significant test (( p < 0.01) was passed by the regions that accounted for 54.22% of the total area.

Consequently, in central populations, the HE value of late-opening flowers decreased from 1.65 to 1.45 mm in the S-morph and from 1.53 to 1.27 mm in the L-morph, but the RHE value showed no significant decline in the S-morph ( P > 0.05) and only a marginally significant decrease in the L-morph ( P = 0.011).

The difference was statistically weakly significant ( P = 0.012, Figure 2 ).

Specifically, soil organic carbon ( R2 = 0.6928, P = 0.002) and total nitrogen ( R2 = 0.4876, P = 0.008) exerted highly significant effects on the AOB community structure, whereas AN ( R2 = 0.5005, P = 0.012) also showed a significant impact.

Only the induction of COR6.6 was almost significant ( p < 0.058) under normal growth conditions and was clearly significant under salinity stress conditions ( p < 0.016).

A two-way ANOVA showed a slightly significant genotypic effect (p-value = 0.02), and a much stronger density effect (two-way ANOVA, p-value<0.0001), but no genotype-by-density interaction effect.

During the survey period, community biomass increased in May and June, and decreased from July to September, with a significant trend in August (loss rate 2.61g year -1 ; Supplementary Figure 3 (a); F 1,28 = 28.3, P=0.022; R 2 = 0.18) and September (loss rate 3.97g year -1 ; Supplementary Figure 3 (a); F 1,24 = 24.9, P=0.003; R 2 = 0.34).

For F 1 -infected plants, differences in virus accumulation in leaves were less consistent, with an apparent trend suggesting intermediate levels of accumulation between those of P R and P S ; statistically significant differences ( P < 0.027; Kruskal-Wallis tests) were found among the three accessions at 16 dpi in basal leaves and at 23 and 30 dpi in intermediate leaves ( Figure 1B ).

Afterwards, analysis of variance (ANOVA) followed by Tukey’s honestly significant difference (HSD) post hoc test revealed no effect of the treatments on the richness in soil and only a slight significance in the root ( p ≤ 0.029).

Likewise, soil factors also exerted an insignificant effect on the allometric exponent ( P > 0.05) ( Figure 2b ), while their influence on the intercept approached significance ( P = 0.029) ( Figure 2d ).

A more detailed examination of β diversity through additive partitioning revealed marginally significant differences in the turnover component in TKB (pseudo-F = 3.04, p = 0.031), where ditches and ponds showed greater heterogeneity due to species replacement compared to rivers ( Supplementary Figure S1a ).

When we controlled for phylogeny, we also found marginally significant correlations between four traits (SLA, π 0 , π tlp , and ε) and the 5th percentile of AI (SLA: F =4.93, P =0.033, Figure 6E ; π0: F=3.53, P =0.069, Figure 7E ; π tlp : F =3.31, P =0.078, Figure 7F ; and ε: F =3.24, P =0.08, Figure 7G ).

The interaction between air and root-zone temperature was slightly significant ( P = 0.036) and the plants grown at 20°C root zone temperature produced the lowest final dry weight, in all cases.

The main effect of “time” was also highly significant for all four genes ( p ≤ 0.036).

The differences between microspore viability after 1 week of culture in different media were marginally statistically significant (p = 0.037), with the lowest viability recorded for microspores cultured in NLN-13 alone (33.1 ± 3.6%).

Except for the interaction between Chr7 and Chr8 QTLs, that showed marginal significance ( p = 0.0378), none of the other two or three-way interactions were significant at ( p < 0.05).

For example, the effect of Claroideoglomus on plant shoot biomass was only marginally significant under non-saline conditions ( p = 0.04), but it did not influence plant shoots when hosts experienced salinity stress.

Leaf trait values (i.e., specific leaf area and leaf dry matter content) depended also on the interaction between species identity and the presence of earthworms, although this interaction was only marginally significant for leaf dry matter content ( p = 0.04 and p = 0.10, respectively; Figure 3 ).

Local temperature presented positive trends over time (R 2 = 0.15 and R 2 = 0.2, p<0.04), as vapor pressure (CRU regional data; R 2 = 0.1, p=0.07), AMO and TSA (global variables; R 2 = 0.5 and R 2 = 0.1, p<0.04), while local precipitation presented a negative trend over time (R 2 = 0.11, p=0.04). 3.5 SAVI, lakes and snow-ice cover relationships The cross correlation between SAVI and lake areas showed a positive association between the complete series in the current and subsequent quarters ( Figure S7 ), with SAVI seasonal fluctuations more pronounced than in lakes, as observed in Figures 2B, D .