All experiments were conducted with three replicates, and mean comparisons were performed using Duncan’s test (‘*’ indicates p < 0.05, significant; ‘**’ indicates p < 0.01, highly significant).
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SO 4 2− and Cd showed highly significant associations ( p < 0.01), suggesting that these factors play a key role in shaping microbial structure ( Figure 5 A).
Among these, 11 transcripts exhibited a highly significant correlation ( p -value ≤ 0.01), while the other 30 were significantly correlated ( p -value ≤ 0.05).
The analysis revealed that FRK enzyme activity showed highly significant positive correlations with multiple glycolytic intermediates and energy metabolites, including pyruvate ( p < 0.01), NADPH ( p < 0.01), NADH ( p < 0.01), ATP ( p < 0.01), and F6P ( p < 0.01).
The correlation between the number of seeds and the cell width in the middle of the mesocarp was positively correlated (0.57) in CK treatment, while the correlation decreased in A1 and A2 treatments, but it showed extremely significant positive correlation ( p < 0.01) and significant positive correlation ( p < 0.05) under A3 and A4 treatments, respectively.
Correlation Analysis of Forage Yield Quality, Soil Physicochemical Properties, and Soil Enzyme Activities Under Different Fertilization Treatments As shown in Figure 5 a, aboveground biomass of artificial grassland exhibited highly significant correlations ( p < 0.01) with soil physicochemical properties and microbial biomass carbon, nitrogen, and phosphorus.
Correlation analysis confirmed that the activity of SOD and catalase (CAT) showed a highly significant positive correlation with growth indicators (r > 0.8, p < 0.01) and a highly significant negative correlation with malondialdehyde (MDA) content (r < −0.8, p < 0.01), indicating that antioxidant defense is the core pathway.
The results showed that the estimated variances of genotype, environment, and genotype-by-environment interaction were all highly significant ( p < 0.01).
Highly significant positive correlations ( p ≤ 0.01) were found between the following trait pairs: DBH and GD; DBH and RL; RL and LN; RL and LW; LL and LW; LL and LWR; LL and LA; and LW and LA.
A comparison of soil metal distributions between GC and WC systems showed that Cd concentrations had no significant change between cultivation systems ( p > 0.05), while Pb showed highly significant differences ( p < 0.01) across the two cultivation systems due to anthropogenic input.
The differences in these physiological indicators were highly significant (all p < 0.01). 2.3.
Effects of Organic Fertilization on System Productivity Organic fertilization practices had a highly significant effect on maize equivalent yield (MEY) across the rotation system ( Figure 1 a; p < 0.01).
When the p -value was below 0.05, the variances were considered significant (*), and highly significant differences were denoted when p < 0.01 (**). 5.
In full-light drought conditions (T 1 , T 2 ), dry matter accumulation and photosynthetic capacity were affected, with drought duration (D n ) showing highly significant negative correlations ( p < 0.01) with most physiological parameters ( RWC , LDW , G s , T r ).
Correlation Analysis Between Nutrient Contents and Stoichiometric Characteristics of Different Components of Main Shrubs and Herbs in Karst Forests As shown in Figure 5 , for the stoichiometric characteristics of shrub leaves, the positive correlation groups were as follows: C content was significantly ( p < 0.05) positively correlated with C/K (r = 0.54); there were significant ( p < 0.05) or extremely significant ( p < 0.01) positive correlations between N content and P (r = 0.68), Ca (r = 0.62), and Mg (r = 0.60) contents, as well as between P content and Ca (r = 0.67) and Mg (r = 0.46) contents; K content was extremely significantly ( p < 0.01) positively correlated with K/P (r = 0.73); Ca content was significantly ( p < 0.05) or extremely significantly ( p < 0.01) positively correlated with Mg (r = 0.79), N/K (r = 0.61), and Ca/Mg (r = 0.47).
Further analysis of fruit quality showed highly significant positive correlations (between peel L* value and peel b* value, r = 0.98, ** p < 0.01), a highly significant negative correlation (between pH value and aroma compounds, r = −0.97, ** p < 0.01), and a highly significant positive correlation (between total phenols and tannins, r = 0.99, ** p < 0.01).
Effects of Different Degrees of Salinization on Ecosystem Carbon Exchange and Resource Use Efficiency While year and salinization significantly affected NEE ( p < 0.05) without a significant interaction, both factors along with their interaction had highly significant effects on ER and GEP ( p < 0.01, Table 1 ).
Association analysis between three phenotypic traits (DBH, annual height increment, and branch number) and SNPs identified 25 highly significant SNP loci ( p < 0.01).
Moreover, Spearman’s rank correlation analysis demonstrated highly significant positive correlations ( p < 0.01) among all pairs of methods ( Table 4 ).
The Mantel test results demonstrated a significant or highly significant correlation between gd and ggd (R 2 = 0.1942, p < 0.01), gd and pre (R 2 = 0.2018, p < 0.01), gd and vapr (R 2 = 0.3297, p < 0.01), gd and sra (R 2 = 0.3849, p < 0.01), and gd and tmin (R 2 = 0.0536, 0.01 < p < 0.05).
Compared to the control (CK), the M treatment induced a highly significant accumulation ( p < 0.01), with a relative abundance approximately 3.4-fold higher.
Joint ANOVA and Genetic Parameters Joint ANOVA for the treatments (environmental indices (E) and genotypes (G)) displayed highly significant differences ( p < 0.01) for all studied traits, and the interactions were significant for 12 traits and insignificant for 8 traits (DH, RWC, E, POD, Pn, Gs, PPO, and CAT) ( Table 2 ).
The needle soluble sugars showed highly significant positive correlations ( p < 0.01) with the root soluble sugars, root starch, root NSCs, and stem starch.
The highly significant correlations ( p < 0.01) with yield were ZRs, leaf N content, leaf K content, PWP and SPAD, and the significant correlations ( p < 0.05) with yield were IAA, GA, and Pn.
chinense identified 406 pairs of variables, among which 284 pairs showed highly significant correlations ( p < 0.01) and 347 pairs revealed significant correlations ( p < 0.05) ( Figure 5 ), indicating extensive interactions among fruit quality traits.