Reduced-sodium Vienna sausage: Selected quality characteristics, optimized salt mixture, and commercial scale-up production.

Sodium reduction influences the quality of processed meat products that, in turn, affect consumer acceptance. The objective of this study was to develop and evaluate the texture, color, and sensory acceptability of reduced-sodium Vienna sausage. A three-component mixture design (0-65% NaCl; 35-100% KCl; 0-20% glycine [Gly]) was performed to obtain an optimal salt mixture based on 14 sausage formulations. Mixture response surface plots revealed the optimal reduced-sodium Vienna sausage containing 20.13-65.00% NaCl, 35.00-60.15% KCl, and 0.00-20.00% Gly (this salt mixture constituted 1.35% of the formulation). One optimal laboratory-scale sausage, formulated with 21.43% NaCl, 59.71% KCl, and 18.86% Gly, was further selected for commercial scale-up production (a 25-kg batch). Both laboratory-scale and scale-up products were comparably acceptable (5.9-6.6 vs. 5.9-6.7) for overall liking, flavor, saltiness, and texture, and contained 315.4-333.5 mg sodium/100 g, hence having >25% sodium reduction compared to the control (569.5 mg/100 g) according to US Food and Drugs Administration regulation. This study demonstrated the feasibility of a scale-up production of acceptable reduced-sodium Vienna sausage formulated with a salt mixture of NaCl/KCl/Gly. PRACTICAL APPLICATION: Processed meat products are one of the major sources of daily dietary sodium in the form of sodium chloride. Recently, there is an increased demand by consumers for healthier meat products. Of particular interest is finding solutions for sodium reduction in meat products while maintaining sensory properties and consumer acceptance. This study demonstrated that a mixture of KCl and Gly could be used as partial NaCl substitution in the commercial scale-up of Vienna sausages without drastically compromising sensory acceptability.

Comparing Friedman versus Mack-Skillings data analyses on duplicated rank data: a case of visual color intensity.

BACKGROUND: In duplicated ranking tests, panelists either rank duplicates separately (2SS) or jointly in a single session (1SS). This study compared data analyses of duplicated yellow color intensity rank data using Friedman versus Mack-Skillings (M-S) tests. Panelists (n = 75) ranked an orange juice set twice - a similar-samples set (100%, 95% versus 90%); samples other than the 100% juice were prepared by dilution with water. Rank sum data were obtained from (a) intermediate ranks from jointly re-ranked scores of 2SS for each panelist, and (b) joint rank data of all panelists from the two replications in 1SS. Both (a) and (b) were analyzed using the M-S test. The median rank data (c) for each panelist from two replications were analyzed using the Friedman test. RESULTS: Comparing M-S with the Friedman tests, the former generally produced higher test statistics and lower P-values than the latter. However, when considering the pattern of post hoc pairwise significant differences, both tests yielded similar conclusions. CONCLUSION: This study demonstrated that, in a duplicated ranking test with three samples that were very similar in color, separating the two replications into two complete individual ranking tests or serving sessions (2SS) may prevent sensitivity loss due to fatigue that is otherwise experienced when evaluating all samples together in a single session (1SS). We expected to find the M-S test to be more sensitive than the Friedman test; however, this hypothesis was not supported by the post hoc (Tukey's honest significant difference (HSD)) multiple comparison test results under the specific test conditions in this study. © 2019 Society of Chemical Industry.

Influence of Package Visual Cues of Sweeteners on the Sensory-Emotional Profiles of Their Products.

Substantial evidence suggests influence of color, physical state, and other extrinsic features on consumer perception and acceptability of food products. In this study, 560 subjects evaluated liking and emotional responses associated with 5 sweeteners (sucralose, stevia, saccharin, aspartame, and sucrose) under 2 eliciting conditions: control (brand name only) and informed (brand name/packet image), to assess impact of the packet color. For a given condition, 5 identical tea samples each labeled with a sweetener type were rated for sweetness and overall liking (9-point) and emotions (5-point). Nonsignificant interactions between eliciting condition and sweetener type were found for liking attributes and emotions (except peaceful), indicating their independent effects. However, overall differences existed among sweetener types and eliciting conditions based on both hedonic and emotional responses (MANOVA, P < 0.05), suggesting modulating effects of packet color on sweetener type in the sensory-emotion space. The sensory-emotion profile for sucrose was separate from that of nonnutritive sweeteners, with statistically significant Mahalanobis distances among sample centroids. Increases in positive emotion intensities contrasted with a decrease in negative emotion intensities were observed for some sweeteners moving from the control to informed condition. Sweetness liking was strongly correlated with the emotion satisfied (sucralose, saccharin) only in the control condition, whereas it was strongly correlated with the emotions pleased and satisfied (stevia), disgusted (aspartame), and satisfied (sucrose) only in the informed condition. Overall, results suggested that sensory liking and emotions during the consumption experience are related not entirely to the type of sweetener, but also the color of the packet.

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data.