Statistical Analysis

A central composite rotatable design (Table 1) and the dependent and independent variables' model relationships (Table 3) were designed using Minitab®19 (USA). The data on the physicochemical, textural, rheological, and proximate composition were analyzed using a one-way analysis of variance (ANOVA) technique. The statistical data were analyzed using the commercial statistical package IBM SPSS (SPSS INC., Chicago, IL, USA). Cheese preparation and analytical measurements were executed in triplicate, and mean values and standard deviations were used in the calculations. Means were related using the least significant difference, and a probability of p ≤ 0.05 was considered statistically significant.

The model equation of independent and dependent variables and its estimated cheeses' estimated constant values.

^*Significant terms; p-values: *p < 0.05, **p < 0.01, and ***p < 0.005.

Response variable value = Constant + C1 × Pressure + C2 × Time + C3 × Pressure² + C4 × Time² + C5 × Pressure × Time + Residuals (all models are significant at p < 0.001).