Effect of coating on energy use efficiency of hybrid rice with different direct seeding methods Analysis of variance in Table 6 shows that coating has extremely significant effects on energy output, net energy, energy use efficiency, and energy productivity, and that the direct seeding method-coating treatment interactions show extremely significant effects on those indicators.
In contrast, RSb (RS3) showed highly significant inter-generational differences with a broad-sense heritability below 0.5.
For instance, the expression of CPK gene in Medicago lupulina also showed an increasing trend in karst areas ( Zhang et al., 2019 ).
Root nitrogen accumulation demonstrated a highly significant positive effect on aboveground nitrogen accumulation.
For all the tested luciferases, their half-lives exhibit a decreasing trend with their enzyme concentrations increasing.
Additionally, treatment effects were found to be highly significant for all traits, demonstrating the strong influence of environmental conditions on fiber quality ( Figure 6C ).
The relative abundance of r-strategist bacteria showed a trend of O > O+M > CK ( Figure 5B ).
Differences at p < 0.05 and p < 0.01 were considered significant and highly significant, respectively.
Highly significant positive correlations were detected between several leaf gas exchange measurements at morning and biochemical parameters such as E, g s , and A with the content of carotenoids, Ci with leaf starch, A and g s with antioxidant activity ABTS, and A/gs with phenolics.
The correlation matrix and pairwise scatter plots in Figure 3 revealed highly significant positive associations among drought-responsive traits.
Correlation between leaf functional traits and yield The contents of chlorophyll a ( R 2 = 0.948 p < 0.01) and b ( R 2 = 0.818 p < 0.01), total chlorophyll ( R 2 = 0.948 p < 0.01), and carotenoids ( R 2 = 0.802 p < 0.01) showed highly significant positive correlations with yield ( Figure 5 ).
Despite this marginal significance, qRPH11 consistently explained a substantial proportion of phenotypic variance, with PVE values ranging from 13.07% to 33.89% across the two models.
Furthermore, the plant height, TDM, and TFM of all provenance areas showed a decreasing trend under the T3 treatment at each experimental stage, except for the TFM of the Gansu provenance at 1d AF, the TDM of the Gansu provenance at 1d AF and 5d AF, and the TDM of the Hebei provenance at 1d AF ( Table 1 ).
Specifically, the expression level of CHS gene in YS was approximately 3 times that in GS, exhibiting an extremely significant phenotype-specific difference.
As shown in Figure 8 , the canopy coverage information shows an increasing trend with the advancement of growth stage, and variations in canopy coverage are observed among different varieties of lettuce at different growth stages.
The following counts represent total DEGs per pairwise comparison, including genes that may be significant in other comparisons.
Linear regression analysis indicated a positive trend in yield with increasing duration of weed-free periods, whereas a clear negative trend was observed under weed competition.
3.8 Analysis of significantly differential metabolites Based on the criteria of Variable Importance in Projection (VIP > 5) and significance testing (p< 0.05), we identified 16 highly significant differential metabolites from the metabolomic data of red-leaf cotton.
The distribution of measured SBW is shown in Figure 4 , and SBW exhibited a decreasing trend with increasing planting density. 2.3 Feature construction 2.3.1 Remote-sensing image preprocessing Image mosaicking was performed in Agisoft Metashape Professional (v1.8.0; Agisoft LLC, St.
Phenotypic variation Analysis of variance (ANOVA) revealed highly significant differences among the 96 forage pearl millet inbreds and four check cultivars for agro-morphological, physiological, and root architectural traits, indicating substantial genetic variability in the experimental material ( Table 1 ).
Among these, the relative abundances of Mucoromycota and Ascomycota were notably influenced by altitude: the former exhibited an increasing trend with rising altitude, while the latter showed a decreasing trend.
The size of the medicinal rhizomes showed a decreasing trend with increasing altitude, suggesting that high altitudes may inhibit the growth of medicinal parts.
The results showed that rank exhibited highly significant correlations with nicotine, reducing sugars, total sugars, and sugar-nicotine ratio, and that spectra exhibited highly significant correlations with nicotine.
At the same irrigation frequency, soil salinity showed a decreasing trend with increasing irrigation volume.
However, the NDVI showed a decreasing trend in UB_YRB from 2011 to 2020, which differed from the steady rising trend in MB_YRB and LB_YRB. 4.1.2 Spatial changes of multi-year NDVI Based on the 20-year NDVI dataset, the spatial distribution of the average NDVI calculated by ArcGIS10.2 is given in Figure 4 .