Statistica 13

For each of the analyzed factors: additive—addition of linseed oil ethyl esters (C—control or E—experimental), condition—animal living conditions (L—laboratory or O—outdoor cage), and season—season of experiment (S—summer or W—winter), the tables present average values and standard deviation. The obtained data for main effects (additive, conditions, season) were analyzed by analysis of variance ANOVA using Statistica 13.3 (TIBCO Software Inc., Palo Alto, CA, USA). Significant differences between the groups were confirmed by Duncan’s multiple range test. Highly significant differences at the level of p < 0.01 were marked uppercase—A, B and significant differences at the level of p < 0.05 were marked lowercase—a, b.
The obtained data for main effects were analyzed by analysis of variance ANOVA using Statistica 13.3 (TIBCO Software Inc., Palo Alto, CA, USA). Significant differences between the groups were confirmed by Duncan’s multiple range test. Differences with p < 0.05 were considered as significant and p < 0.01 as highly significant.

The most appropriate models to describe the drying kinetics curves were chosen based on the mean relative error (MRE, Equation (1)), standard error of estimate (SEE, Equation (2)), and coefficient of determination (R²). A MRE value of less than 10% was one of the criteria for selecting the best model [76 (link)]. Statistical analyses were conducted using Statistica^® 13.1 (TIBCO Software Inc., Palo Alto, CA, USA), and the Quasi-Newton method was applied. N represents the number of experiments, df the degrees of freedom, XR_exp the experimental moisture ratio, and XR_pre the predicted moisture ratio.
$\mathrm{MRE}=\frac{100}{\mathrm{N}}{\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{N}}\left|\frac{{\mathrm{XR}}_{\exp }-{\mathrm{XR}}_{\mathrm{pre}}}{{\mathrm{XR}}_{\exp }}\right|$
$\mathrm{SEE}=\sqrt{\frac{{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{N}}{\left({\mathrm{XR}}_{\exp }-{\mathrm{XR}}_{\mathrm{pre}}\right)}^2}{\mathrm{df}}}$
The yield and antioxidant activity data were subjected to variance analysis (ANOVA) and their means were compared performing the Tukey test (at a significance level of p < 0.05). Principal component analysis (PCA) was performed using a matrix correlation. In addition, the Euclidean distance and complete binding were used for the hierarchical cluster analysis (HCA) of the samples. The statistical analyses were conducted using Statistica^® 13.1 (TIBCO Software Inc., Palo Alto, CA, USA).