Paired preference tests and placebo placement: 1. Should placebo pairs be placed before or after the target pair?

One type of paired preference test uses the 'target' pair of stimuli under consideration to record the measured preferences (prefer A, Prefer B, 'no preference') and a second putatively identical control pair, the 'placebo' pair (AA or BB) to indicate 'false' preferences, unrelated to the target pair, elicited by the effects of the testing situation. From the literature there is disagreement regarding whether it is important to place a placebo pair before or after its corresponding target pair, to elicit a greater proportion of 'no preference' responses. This is important, because the higher the frequency of 'no preference' responses in the placebo pair, the more powerful will be the chi-squared style analysis, which determines whether the target pair displays a significant preference or not. It has been hypothesized that placing the placebo pair after the target pair would elicit more 'no preference' responses in the placebo, because the consumers would have had a chance to experience the difference in sensory characteristics of the two stimuli in the target pair. Using a related samples design, the hypothesis was confirmed although the difference between placebos placed before and after the target was not always significant. It was hypothesized that this lack of significance was caused by greater variance among the items being assessed, making it more difficult to decide whether a putatively placebo pair, in the context of the experiment, was really 'identical'. Psychological adjustments in the consumers were discussed in terms of difference and preference tau criteria. A boost in the proportion of 'no preferences' was observed for the placebo pair built into the triadic preference test, this was explained by the experimenter gaining some control over the consumers' preference tau criteria.

Paired preference tests and placebo placement: 2. Unraveling the effects of stimulus variance.

From the literature on paired preference testing, there has been disagreement regarding whether a placebo pair would have a significantly higher frequency of 'no preference' responses if it were to be placed for assessment after its corresponding target pair rather than before. This can be important, because the higher the frequency of 'no preference' responses in the placebo pair, the more powerful will be any chi-squared related analysis, which determines whether the target pair indicates a significant preference or not. In the first paper in this series, it was shown, that indeed a placebo placed after the target pair induced a higher proportion of consumers to respond with a 'no preference'. However, the response was uneven. For some stimuli, the response was strong and significant, for others it was weaker and not significant. It was hypothesized that the weak response could be due to greater variance among the individual stimuli in the placebo sample to be tasted. The effect was confirmed using a priori chosen high and low variance stimuli. Further evidence was obtained from predictions for preference tau criterion levels and frequency of preference changes between two target pairs. All these indicated that the weaker response of some stimuli was due to a higher level of variance among the individual stimuli.

The Salt Flip: Sensory mitigation of salt (and sodium) reduction with monosodium glutamate (MSG) in "Better-for-You" foods.

We tested the hypothesis that reduced-salt versions of four "better-for-you" dishes enhanced with monosodium glutamate (MSG) through a "Salt Flip" in an amount that still substantially reduced total sodium matched the consumer acceptance of normal-salt versions. Three versions each-standard recipe with normal salt, reduced salt, and reduced salt with MSG, of four dishes-roasted vegetables (RV), quinoa bowl (QB), savory yogurt dip (SD), and pork cauliflower fried rice (CR) were evaluated by 163 consumers for overall liking and liking of appearance, flavor, and texture/mouthfeel on the nine-point hedonic scale, preference, adequacy of flavor, saltiness, and aftertaste on just-about-right (JAR) scales, likeliness to order, and sensory characteristics by check-all-that-apply. For each dish, the MSG recipe was liked the same (or significantly more for SD, P < 0.05) than the standard recipe, and better than the reduced salt recipe for QB and CR. The same was true of likeliness to order. MSG recipes of QB and SD were significantly preferred to the standard recipes, with no difference for RV and CR. MSG recipes were consistently described as "delicious," "flavorful," and "balanced." Penalty-lift analysis showed that "delicious," "flavorful," "balanced," "fresh," and "savory"; and "bland," "rancid," and "bitter," were positive and negative drivers of liking, respectively. Two of three uncovered preference clusters, accounting for 68% of consumers, consistently liked MSG recipes, and the same or more so than standard recipes. We conclude that MSG can successfully be used to mitigate salt and sodium reduction without compromising consumer acceptance of better-for-you foods. PRACTICAL APPLICATION: The Salt Flip offers a promising dietary sodium reduction strategy through the addition of monosodium glutamate (MSG) to reduced-salt, savory, better-for-you foods that does not compromise consumer acceptance of their sensory profile.

The 9-point hedonic scale: Using R-Index Preference Measurement to compute effect size and eliminate artifactual ties.

214 consumers used the verbal 9-point hedonic scale to assess 4 types of flavor coated peanuts and 4 types of flavored teas. They used the traditional ANOVA/LSD analysis to provide mean values derived from the 9-point hedonic scale along with measures of significant difference. However, these data did not provide effect sizes. They did not give direct measures of the strength of preference between the various products, which was the main interest. Accordingly, effect sizes were computed. For this, each consumer had also ranked their preferences as they made their ratings on the 9-point hedonic scale. From these, R-Index values were computed to provide the percentages of consumers, who preferred each product to every other product. These direct measures of effect size completed the analysis begun by the ANOVA analysis of the set of mean scores. Also, the measures were nonparametric and avoided issues of the validity of a parametric statistical analysis. They also avoided the problem with the traditional analysis when products in the same scale category are attributed the same scores, when they are not equally liked. Experiment 2, using 207 consumers indicated that this problem was only serious enough to reduce the power of the traditional analysis, compared with the R-Index Preference Measurement, when the number of products being tested approached a dozen say, for product optimization.