Meanwhile, Δ5-avenasterol showed a trend that was inverse to β -sitosterol, as indicated by the strong negative correlation obtained among those two sterols (r = −0.902, p < 0.01), likewise observed in other monovarietal oils from several countries [ 6 , 32 , 57 , 58 ].
Finally, looking at Pearson’s correlations, there were highly significant correlations between TPC and DPPH ( p < 0.01), whilst flavones (luteolin equivalents) were well correlated to phenolic acids (ferulate equivalents) and flavanols (catechin equivalents) ( p < 0.05).
The difference was considered to be extremely significant when p < 0.01.
Among them, Myristic acid and Linolenic acid showed highly significant negative correlations with bitterness (r = −0.88 and −0.85, respectively; p < 0.01).
Additionally, gas chromatography analysis of five major fatty acids in 196 cultivars confirmed highly significant genotypic variation ( p < 0.01), with an average variation index of 4.55% across fatty acid components [ 15 ].
As shown in the ANOVA, the model was highly significant ( p < 0.01), and the lack of fit was not significant ( p = 0.0577 > 0.05), indicating that the model adequately described the data.
In summary, 1089 correlation pairs were analysed, among which 275 metabolic pairs result in highly significant correlations ( p < 0.01).
As shown in Figure 9 , 8 pairs of indicators showed a highly significant correlation ( p ≤ 0.01), and 8 pairs of indicators showed significant correlation ( p ≤ 0.05).
Among these, the inhibitory effects of SDA and DHA-S against Brocothrix were extremely significant ( p < 0.01).
The Spearman correlation analysis revealed highly significant correlations ( p < 0.01) between several wheat quality characteristics and Daqu quality indices, identifying wheat starch and protein as key factors affecting Daqu quality.
As illustrated in Figure 9 , a * demonstrated a highly significant positive correlation with Δ E (r = 0.791, p < 0.01), suggesting that alterations in the a * values primarily driven by Maillard reaction and phenolic oxidation during drying served as the key contributor to the accumulation of the total color difference (Δ E ).
Highly significant differences ( p < 0.01) were observed in yellowness (b*) values for storage days 60 and 90.
Correlation Analysis As shown in Figure 4 A, a highly significant positive correlation ( p < 0.01) was observed between the immersion time of fresh wet tuber-based vermicelli and both moisture content and free water proportion, with Pearson correlation coefficients exceeding 0.90.
HE staining revealed highly significant differences in muscle fiber area and diameter between H and L groups ( p < 0.01), along with significant differences in muscle fiber density ( p < 0.05), but no significant differences in muscle fiber perimeter.
However, the difference between the conditions was highly significant ( p < 0.01) for the total amount of substances ( Figure 2 c,d).
The interactive effects of frying temperature and thickness have extremely significant effects on the hardness and color difference ( p < 0.01).
At the end of the experiment (28 d), the blood glucose levels of mice in the other four groups, except for the CK group, decreased to a certain extent and showed extremely significant differences when compared with the NC group ( p < 0.01).
In ‘Surkh’, storage interval had a highly significant effect on chilling injury ( p ≤ 0.01), and TG-coated fruit consistently exhibited lower injury; at 20 days of cold storage plus 2 days at 20 °C ± 1 °C, TG-treated fruit recorded an injury score of 3.4 compared with 4.0 in the control ( Figure 2 B).
Analysis revealed that the metabolic cluster composed of reducing sugars (glucose, fructose) and branched-chain amino acids (leucine, valine) exhibited a highly significant directional association with pyrazine generation (Node P; p < 0.01).
A highly significant, linear decrease in pH was observed during fermentation (X 1 = −0.17, X 2 = −0.06, p < 0.01), indicating that each additional day and each increase in temperature significantly decreased the pH values in all kombucha products.
Two-way ANOVA ( Table 3 ) also confirmed a highly significant interaction ( p < 0.01) between harvest period and variety on the thousand-grain weight.
From the p -value, it could be seen that the influence of factors B, C, AC, BC, A2, and C2 was extremely significant ( p < 0.01), the influence of factors A was significant ( p < 0.05), and the influence of factors AB and B2 were no significant ( p > 0.05).
In this sense, a highly significant and strong negative correlation has been observed (−0.839; p ≤ 0.01) between juiciness and pastiness.
This protein component showed a highly significant positive correlation ( p < 0.01) with viscosity, chroma, foam stability, foam volume expansion rate, and foaming capacity.
Differences were considered statistically significant at p < 0.05 and highly significant at p < 0.01.