Statistica software for windows version 13

The statistical analysis was performed using the Statistica software for Windows, version 13.3 (Statsoft, Krakow, Polska). The effect of the ripening time on the chemical properties and microbiological quality was tested using one-factor (ripening period: 0, 2, 4 weeks) and two-factor (ripening period: 0, 2, 4 weeks; breed: Pul, ZS) analyses of variance (ANOVA with fixed and orthogonal factors). Duncan post hoc tests were used to compare the means at p < 0.05.

The results of fiber, physicochemical, and structural analyses were subjected to one-way analysis of variance (ANOVA) with Duncan’s post hoc test at a 95% confidence level in the SPSS Statistics 25 software (IBM-SPSS Inc., Chicago, IL, USA).
Values obtained by the consumer acceptance test were analyzed by the Kruskal–Wallis test (test H) in the STATISTICA software for Windows, version 13.3 (StatSoft Inc., Tulsa, OK, USA).
Data obtained from the Napping^® sensory analysis (positions in the sensory space) were treated through a geometric analysis using SensoGraph in order to obtain proximity graphs from the Napping^® data. Python implementation [33 ] of the SensoGraph method proposed in [34 (link)] was used to analyze the (x,y) coordinates provided by the tasters. This method comprises three steps: first, a clustering technique from Computational Geometry called the Gabriel graph is applied to each tablecloth so that only pairs of samples without third samples nearby are connected. Second, a global similarity matrix is created, whose i,j entry is 1 if samples i–j are connected and 0 otherwise. Third, a graph-drawing algorithm uses that matrix to provide the 2D positioning of the samples.

Statistical analysis was performed using Statistica software for Windows, version 13.3 (StatSoft),. The mean, median, standard deviation (SD), and interquartile ranges (IQR) were determined for all variables. The Shapiro–Wilk test was used to check the normality of the data distribution. Student’s t-test or Mann-Whitney test was applied to compare quantitative variables, whereas categorical variables were compared by the chi-square test or Fisher’s exact test. Correlations between parameters were evaluated using Pearson’s test or Spearman’s rank correlation test as appropriate. Moreover, a multiple regression analysis was used to identify the predictors of TBS. P-value <0.05 was considered statistically significant