Statistical analysis of data from the acceptance test and instrumental texture was performed by ANOVA and Tukey’s Honestly Significant Difference (HSD) Test of Means (p ≤ 0.05) using SAS software version 9.4 (Statistical Analysis System, Raleigh, NC, USA). Data from purchase intention were plotted in frequency histograms for each sample [29 (link)]. Data from CATA and Projective Mapping were analyzed using XLSTAT software version 2023 (Addinsoft, Paris, IF, France). Cochran’s Q test (p ≤ 0.05) and correspondence analysis (CA) were also performed for data from CATA and correlated to acceptance test data.
Furthermore, data from CATA and acceptance tests were correlated by employing Partial Least Squares (PLS) regression analysis [24 (link)]. The overall impression was considered the dependent variable (Y-matrix), while CATA parameters were the independent variables (X-matrix) [40 (link)]. Data from Napping were analyzed using Multiple Factor Analysis (MFA) and Hierarchical Cluster Analysis (HCA) [38 (link),41 (link)].
Furthermore, data from CATA and acceptance tests were correlated by employing Partial Least Squares (PLS) regression analysis [24 (link)]. The overall impression was considered the dependent variable (Y-matrix), while CATA parameters were the independent variables (X-matrix) [40 (link)]. Data from Napping were analyzed using Multiple Factor Analysis (MFA) and Hierarchical Cluster Analysis (HCA) [38 (link),41 (link)].
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