Panel level

It must be pointed out that a TMA strength improvement of 100% on the MUF resin without methylal (this is achieved by addition of 20% methylal on resin solids) corresponds in the actual wood particleboard to an increase of IB strength of 33%. This means that of all the compounds shown above only the acetals, such as methylal and ethylal, as well as the similarly structured imine/iminomethylene bases discussed above (for which the effect on strength is more marked) are capable of marked improvements in IB strength at the actual wood panel level. 

The subjects used between 4 and 12 attributes (mean 6.4) for a total at the panel level of 45 attributes, 27 of which were semantically different 1 for odour, 1 for aspect, 19 for aroma, 2 for taste and 4 for texture. Obviously, the dominance of flavour attributes reflected these subjects culture in olfaction and hence their inclination to describe flavour. Subjects from different fields of expertise might for instance yield more texture attributes. For this reason, in most of our studies, we try to recmit panellists with complementary expertise. 

The inputs of both the hierarchical and the partitioning algorithms are the overall dissimilarities obtained at the panel level. We will also outline strategies of analysis where the input data are the individual (i.e. subjects) dissimilarity matrices. In this strategy of analysis, the aim is to obtain what is usually referred to as a consensus partition. That is, a partition that agrees as much as possible with the partitions given by the subjects. 

Periods where sweet sensation is dominant for one product at panel level (4 panellists x 2 replications in this... 

The calculation of each index is derived from the usual sum of square decomposition used in ANOVA, but applied to dominance rates. For instance, the discrimination index at panel level is simply the sum of square of the product effect (see the original paper for more details on the other indexes). However, the authors do not follow the F-test approach to test the significance for these indexes, since TDS data (or the residuals from any standard ANOVA model) are not normally distributed. They rather follow the permutation test approach proposed by Meyners and Pineau (2010) and Meyners (2011) and extend it to the scope of their indexes. The reader can refer to the original paper for more details about the testing procedure. 

Since the ideal product has both a sensory and a hedonic dimension - the ideal being defined as a product with particular sensory characteristics that would maximize liking - checking for the consistency of the ideal data should be done both from the sensory and the hedonic point of view. These consistencies are checked both at the consumer and at the panel level. 

Consumers are consistent from a sensory point of view if they rate their ideal product with similar sensory characteristics to the product they like most. The evaluation of sensory consistency (at the panel level) is done by evaluating whether the ideal information provided is making the link between the perception and the appreciation of the products. Such evaluation is done by double projection as supplementary of the sensory profiles (supplementary entities) and the hedonic scores (supplementary variables) within the ideal space (Fig. 14.3). 

Figure 14.3 Evaluation of the sensory consistency of the ideal products at the panel level. Panel (a) represents the consumer ideal space with projection as illustrative of the products profiles (in grey). Panel (b) shows the corresponding variables representation with projection as illustrative of the hedonic scores (in grey).

The committee recommends a three-level assessment approach to determine appropriate in-market surveillance strategies. Level I assessments include monitoring the toll-free line or Internet website (passive surveillance). Level 2 assessments include in-market panels to review existing data (both published and proprietary). The same selection and composition recommendations presented earlier also hold with regard to in-market panels. Level 3 assessments include conducting retrospective and/or follow-up studies (active surveillance). 

A review of the relevant scientific literature by an expert panel (level 2 assessment) indicates that new evidence exists linking the ingredient, metabolites, secondary effectors, or source to the growth and development of organ systems whose functions become apparent after the period of maximum exposure to infant formula, have known long-term direct consequences, or a link to developmental outcomes that could result in cumulative adverse effects over time. 

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