NDVI showed a highly significant positive correlation with PC 1 ( r = 0.32, p < 0.01) and a highly significant negative correlation with PC 2 ( r = -0.50, p < 0.01).
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A four-way ANOVA of the effect of experimental factors on plant physiological parameters, biomass production, N content, and C:N ratio in plant dry matter ( Table 1 ) showed a statistically highly significant effect of species ( p ≤ 0.01) for most parameters, except C:N ratio where the effect was insignificant.
NUE, NR, GS, and RV all showed a highly significant positive correlation with pH and EB ( P < 0.01).
Specifically, taking conventional rice as an example, EF c had the largest impact on the uncertainty of the carbon footprint, with a correlation coefficient r of 0.50**; the correlation reached an extremely significant level ( p <0.01).
AMMI analysis The combined variance analysis of grain yield data of 40 quinoa genotypes in eight environments ( Table 4 ) showed that the effects of G, E, and G×E interaction were highly significant (P ≤ 0.01), indicating a significant difference in average grain yield among environments and genotypes, as well as the fluctuation of the grain yield of quinoa genotypes from one environment to another.
Surprisingly, SbGATA11 showed an extraordinarily significant positive correlation with all genes (p<0.01) except SbGATA15 ( Figure 8B ).
The analysis showed highly significant ( p < 0.01) genotypic variance among the testcrosses for all the traits indicating that genetic variation among testcross hybrids was abundant.
LAI exhibited a highly significant correlation with OSR in the wavelength ranges of 454–702 nm and 718–950 nm ( p< 0.01), with a particularly strong correlation observed at 750–922 nm ( Figure 4A ).
According to the analysis of variance ( Table 2 ), the interaction terms of X 1 X 2 , X 1 X 4 , X 1 X 5 , X 2 X 3 , X 2 X 5 , X 3 X 4 , X 4 X 5 and X 1 X 2 2 X 3 were extremely significant (p ≤ 0.01), indicating that their interaction can significantly affect the mycelial growth of H. erinaceus .
Meanwhile, in terms of significance, except for T2D1N2 and T0D3N1, which showed significance (p< 0.05), all other cases showed highly significant (p< 0.01).
infestans , the r value was 0.94, the linear equation was y = 0.5089x - 8.014 (R 2 = 0.88, p = 0.006), the difference was highly significant (p < 0.01).
Statistical significance of the effects was indicated as follows: highly significant (** P < 0.01), significant (* P < 0.05), and marginally significant (+ P < 0.1).
This upward trend was highly significant, with an increment of 0.0034 year −1 ( P < 0.01) ( Figure 2 ).
All differences were highly significant (P<0.01) under one-way ANOVA analyses.
Moreover, the correlation heat map analysis ( Supplementary Figure 7 ) results showed that Botrytis had significant positive correlations ( P <0.05) with Candidatus_ Rhabdochlamydia , Hymenobacter and Mucilaginibacter , while it showed highly significant negative correlations ( P <0.01) with Arenimonas and Saccharomonospora .
A significant negative correlation was identified between TP and CAT (P< 0.05), while a highly significant positive correlation was found between nitrate N and PRO (P< 0.01).
The results of the response surface test proved that the nozzle height, forward velocity, and swing frequency all had a highly significant effect on the uniformity coefficient of fertilizer spreading in the longitudinal and transversal directions ( P <0.01).
The single effect of nitrogen and water application on plant height had a highly significant effect ( p <0.01) ( Figure 3A ).
The regression coefficients were highly significant ( P < 0.01 or P < 0.001) for all harvest dates, showing a positive effect of far-red fraction on light use efficiency.
Variance components due to the inbred line × P condition interaction were also highly significant ( P < 0.01) for all traits.
The results showed highly significant (p< 0.01) annual grain yield gains of 118, 63, 46, and 61 kg ha −1 year −1 under optimum, low N, managed drought, and random stress conditions, respectively.
The analysis of variance (ANOVA) analysis results showed that interspecific ionomic variations were extremely significant ( p < 0.01), irrespective of whether it is for macroelements or microelements.
Highly significant differences (P < 0.01) were detected in WD, MOR, MOE, SSG, CP, LC, HC, CC, FL, FW, and FP.
3.4 Interactive effect of AMF and salt concentration on indicators Salt concentration had a highly significant impact on all indicators ( P < 0.01, Table 3 ).
Irrigation and N application treatments had a highly significant (P < 0.01) effect on LAI at each growth stage in both 2021 and 2022.