Table 4.
Analysis of variance applied to the regression model used for the biomass concentration (R2 = 0.97).
| Source | Sum of squares | Degrees of freedom | Mean of square | F-value | Prob>F | Remarks |
|---|---|---|---|---|---|---|
| Model | 6.70 | 5 | 1.34 | 27.09 | 0.000082 | Significant |
| +b1 | 4.45 | 1 | 4.45 | 159.10 | 0.000056 | Significant |
| b11 | 0.72 | 1 | 0.72 | 25.76 | 0.003851 | Significant |
| #b2 | 0.36 | 1 | 0.36 | 13.01 | 0.015430 | Significant |
| b22 | 1.26 | 1 | 1.26 | 44.87 | 0.001121 | Significant |
| b12 | 0.04 | 1 | 0.04 | 1.43 | 0.285591 | Not Significant |
| Residual | 0.39 | 8 | 0.05 | |||
| Lack of fit | 0.26 | 3 | 0.08 | 3.04 | 0.130860 | Not Significant |
| Pure error | 0.14 | 5 | 0.03 | |||
| Total | 7.10 | 13 |
Independent variables:
+
1 = Soybean flour concentration;
#
2 = Temperature.