The impact of each factor on the model is considered highly significant ( p ≤ 0.0001), and according to the F-values, the order of the influence of extraction conditions on LRM-ELN yield is as follows: A (concentration of PEG6000) > B (relative centrifugal force) > C (incubation time), indicating that the concentration of PEG6000 is the key factor affecting the yield.
Excerpts
The resulting regression equation is as follows: (1) Y = 80.03 + 11.13 A − 0.6750 B − 9.75 C − 0.125 AB + 1.93 AC − 3.43 BC − 7.41 A 2 − 1.76 B 2 − 11.61 C 2 According to the analysis of variance results ( Table 3 ), the model was highly significant ( p < 0.0001), while the lack-of-fit term was not significant ( p = 0.1019 > 0.05), indicating that the model was well-fitted.
As presented in Table 4 , the model was highly significant ( p < 0.0001) with a non-significant lack of fit ( p = 0.0913).
Analysis of variance (ANOVA) and significance testing ( Table S6 ) indicate both regression models are highly significant ( p < 0.0001) with a non-significant lack of fit.
Fer-1 demonstrated a marked restoration of cell viability with a highly significant statistical difference (F(3,8) = 59.18, p < 0.0001; Figure 2 D).
First, the sucrose concentration decreases in a very highly significant way ( p < 0.0001) over time (from 57.4 g/L ± 0.09 at D0 to 25.2 ± 2.85 g/L at D14), with a highly significant decrease ( p < 0.01) in sucrose content between D7 (44.2 ± 3.92 g/L) and D11 (24.9 ± 2.22 g/L).
Specifically, the interaction effect was highly significant ( p < 0.0001), indicating that the combined influence of MTG concentration and incubation time is critical for understanding their impact on leakage properties.
First, for all the descriptors, the panelist effect was highly significant ( p < 0.0001).
The regression model was highly significant ( p < 0.0001) and the lack of fit was not significant ( p = 0.1535 > 0.05), with a goodness of fit R 2 = 0.9879 and the difference between R 2 Adj and R 2 Pre being less than 0.2, indicating that the model had good fit.
The analysis also quantified the influence of parameters on TPPs yield through standardized coefficients: liquid-to-solid ratio (X 3 ) and ultrasonic temperature (X 4 ) were highly significant ( p < 0.0001), followed by ultrasonic time (X 1 ) ( p = 0.005) and ultrasonic power (X 2 ) ( p = 0.0049).
In all cases, the values of p were highly significant ( p < 0.0001).
The model showed that X 2 , X 3 , X 1 2 and X 2 2 had a significant effect on the tyrosinase-inhibiting activity ( p < 0.05) and that X 3 2 had an extremely significant effect on the same ( p < 0.0001).
As shown in Table 4 , the model exhibited highly significant differences ( p < 0.0001), with the lack-of-fit term yielding a p of 0.3237 (>0.05).
Statistical tests, including the likelihood ratio and Pearson chi-square, were highly significant ( p < 0.0001).
The Y 1 regression model had a highly significant ( p < 0.0001) effect on the primary term B, a significant ( p < 0.05) effect on A, C, AC., and B.C., and a non-significant ( p > 0.05) effect on AB., A 2 , B 2 , and C 2 .
kudriavzevii ITMLB97, the best correlation models were those produced from inulin ( Q 2 = 0.93) and BS-juice ( Q 2 = 0.93), which had a highly significant effect ( p < 0.0001) on the MIR profiles.
The ANOVA results for protein content in this group showed a highly significant F-value of 284.19 ( p < 0.0001), demonstrating that there are statistically significant differences among the samples in this group.
As shown in Table 2 , the model selected by the test was highly significant ( p < 0.0001).
A highly significant seasonal effect was observed for casein content, with summer samples showing higher concentrations (1.26 ± 0.14%) compared to autumn samples (1.04 ± 0.18%) ( p < 0.0001).
The data indicate that the regression model is highly significant ( p < 0.0001), while the error term is not significant ( p > 0.05).
Conversely, treatment with 20 μg/mL oleacein reduced the mean lifespan by 34% relative to control S-base and DMSO; this was an effect that was highly significant (LogRank p > 0.0001).
The difference was highly significant ( p < 0.0001).
However, purge loss in cured pork sausages was highly significant with the addition of ligands ( p < 0.0001; Table 2 ), with cysteine treatment showing higher purge loss than histidine and nicotinamide treatments ( p < 0.05; Table 3 ).
The results indicate that the overall model is highly significant ( p < 0.0001), demonstrating that the constructed model possesses high statistical significance.
The model is extremely significant ( p < 0.0001) following the data processing and analysis, suggesting that the multiple regression equation accurately fits the experimental data and is statistically significant.