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Meyners M.,Procter and Gamble | Castura J.C.,Compusense Inc | Worch T.,Qi Statistics Ltd
Food Quality and Preference | Year: 2016

Methodologies for evaluating panel repeatability in Check-All-That-Apply (CATA) questions are reviewed and developed. First, the limitations with using McNemar's test as suggested elsewhere for the evaluation of repeatability are demonstrated through simple examples. Alternative approaches are then suggested and discussed. These include the binomial test, Gwet's AC1 statistic, and Pearson's χ2 goodness-of-fit test. These methodologies are applied to previously published orange juice data. The advantages of using the binomial test or the Pearson's χ2-goodness-of-fit test are related to their accessibility in most statistical software packages. The advantages of using the Gwet's AC1 statistic or the Pearson's χ2 goodness-of-fit test are related to the fact that tests are easily generalized to more than 2 replications. Pearson's χ2 goodness-of-fit test is widely available in statistical software and generalizable to more than 2 replications, but this test is sensitive to very low expected frequencies. For this reason we suggest using Gwet's AC1 statistic, which does not share this limitation. © 2015 Elsevier Ltd.


Worch T.,Qi Statistics Ltd
Food Quality and Preference | Year: 2013

In product optimization, preference mapping techniques are widely used. Although their advantages and benefits are evident, these methods also show some limitations. For example, in external preference mapping (PrefMap), in general only two dimensions are used in the individual regression models, and there is no evidence that these dimensions are relevant for liking. Moreover, potentially important information which could explain the liking scores and which could be present on the third and higher dimensions of the sensory space is often not considered.For that reason, a new methodology, called PrefMFA, is proposed. This methodology based on Multiple Factor Analysis (MFA) is in between internal and external preference mapping since it takes the dimensions from the "common" product space between external (usually sensory) and the hedonic scores in the individual regressions. An extension to Hierarchical Multiple Factor Analysis (HMFA), when more than one external matrix is available, is also proposed.The PrefMFA methodology is applied to two datasets according to two different strategies of analyses, and the advantages of PrefMFA over PrefMap are shown. More precisely, the help for the interpretation as well as the various criteria proposed by MFA (such as the partial axes representation, the Lg, and the RV coefficients) help to better understand the strength of the underlying relationship between the external information and liking. © 2013 Elsevier Ltd.


Mantilla S.M.O.,University of Adelaide | Collins C.,University of Adelaide | Iland P.G.,iland | Kidman C.M.,University of Adelaide | And 4 more authors.
American Journal of Enology and Viticulture | Year: 2015

Relationships among sensory attributes, compositional measures, and wine quality of Shiraz grapes and wines were evaluated for two seasons, 2009 to 2010 and 2010 to 2011. The sensory profiles of berries and wines were evaluated by descriptive analysis and wine quality was assessed by an expert panel. In this study, berry sensory attributes alone were better predictors of wine sensory and compositional variables than the combination of berry sensory and compositional variables. Partial least squares regression analysis and Pearson’s correlation revealed a negative relationship between seed bitterness and wine savory spice flavor in both seasons. In 2011, pulp detachment from the skin correlated with wine sensory attributes such as rim color, fresh dark berry flavor, savory spice flavor, and wine quality score. Correlations among wine sensory attributes, wine pigmented polymers, and wine total tannins were identified in both seasons. These findings are important for grapegrowers and winemakers as they identify berry sensory attributes that may assist as objective measures in predicting final wine style and quality. © 2015 by the American Society for Enology and Viticulture. All rights reserved.


Jervis S.M.,North Carolina State University | Guthrie B.,Cargill Inc. | Guo G.,Cargill Inc. | Worch T.,Qi Statistics Ltd | And 2 more authors.
Journal of Sensory Studies | Year: 2016

Traditional preference mapping methods can suffer where groups of attributes with larger variances dominate the analysis, thus, detracting attention from attributes of potential importance as drivers of liking. This study compared traditional external preference mapping methods (PLS and PREFMAP) with a new method called PrefHMFA which is designed to control dominance of groups of high variance attributes. Twenty-five sliced whole wheat breads were profiled by descriptive analysis (DA) for flavor, appearance (crust and crumb groups) and texture (oral, hand) attributes. Breads were subsequently presented to adult bread consumers (n=360). Data were also subjected to path analysis (PATH-PLS) and three different preference mapping analyses (PLS and PREFMAP and PrefHMFA). Traditional methods (PLS/PREFMAP) showed broad ideal points. PrefHMFA partial axes showed that the main hedonic dimensions were aligned with higher sensory dimensions. PrefHMFA revealed the greater importance of appearance and hand-perceived texture attributes for liking. Path-PLS confirmed the importance of sensory liking and family drivers of purchase intent for sliced sandwich bread. Practical Applications: External preference mapping is used to relate analytical sensory data to consumer acceptance. Traditional techniques have been criticized since groups of attributes with large variances can dominate the traditional PCA or PLS-based methods. New preference mapping techniques of PrefMFA and PrefHMFA have been suggested to account for attribute dominance. These techniques will aid in determining drivers of liking for commodity-type foods and other product or situations where attribute dominance poses a problem with traditional methods. © 2016 Wiley Periodicals, Inc.


Worch T.,Qi Statistics Ltd | Delcher R.,H.J. Heinz B.V.
Journal of Sensory Studies | Year: 2013

Discrimination tests are sensory methodologies that are often used to determine whether differences between two products are sufficiently large to be perceived by assessors. Two common approaches are often used to analyze discrimination test results: the guessing model and the Thurstonian model. The guessing model is known for requiring only simple calculation and being easy to understand and interpret. However, the guessing model is method-specific and it cannot explain the Gridgeman paradox. The Thurstonian model is recognized for returning more rigorous results as it integrates the decision rules used by the assessors in each protocol (hence, it is not method-specific) but is more difficult to interpret and communicate because the resulting d′ value is a perceptual signal-to-noise ratio. As both approaches are based on fundamentally different assumptions, users tend to consider either one or the other approach for the analysis. However, as both approaches use the same information as input (i.e., the proportion of correct answers PC), a connection between the two approaches can be easily made. By doing so, we can take the best of both worlds and provide guidelines for a powerful and easily interpretable approach. This new approach is presented as a possible alternative solution within a detailed guideline on how to run discrimination tests. © 2013 Wiley Periodicals, Inc.

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