Magni Martens

Consumer perceptions of pork in Denmark, Norway and Sweden

Abstract This study focused on how the consumer perceived the eating quality of pork. Detailed questionnaires were distributed to pork consumers (n=526) in Denmark, Norway and Sweden. Multivariate statistical techniques were applied to investigate differences among the consumers. The consumers ranked flavour as the most important attribute. The most important reason for buying pork was its suitability for many dishes, and the least important reason was for serving pork at social occasions. The major differences among consumers occurred between countries and to a lesser extent within age and genders. Swedish consumers reported a higher consumption frequency and were more satisfied with pork quality (i.e. tenderness and juiciness) compared with Norwegian consumers (more aware of rancidity) and Danish consumers (more aware of tasteless flavour). Consumption frequency was related to texture and off-flavour. Consumers aged 16–35 were less likely to eat pork than those older than 35 years.

Sensory panel consistency during development of a vocabulary for warmed-over flavour

Abstract A sensory vocabulary of 20 terms each with a corresponding reference material was developed over 7 sessions using pork patties derived from the meat of carriers and non-carriers of the RN − gene. Patties were oven-cooked at 150 and 170°C and chill-stored for up to 5 days to facilitate warmed-over flavour development. Generalised Procrustes Analysis (GPA) was used to investigate sensory terms and their individual use by panellists over the sessions. GPA explained variance indicated that the final vocabulary displayed a similar amount of information to that of the initial vocabulary of 42 terms. Individual panellists scale use was found to converge over the sessions. Panel agreement on many odour and flavour terms appeared to be enhanced as term synonyms were removed in vocabulary development. Sample discriminability decreased from sessions 1–4, where term concepts were verbally communicated to the panel. Term reference introduction in session 5 caused a levelling in sample discriminability and a reduction in agreement, most likely related to perceptual confusion. Subsequently, references enhanced both discriminability and agreement. Thus, it may be more useful to introduce reference materials earlier, if not in the first session, of the vocabulary development process.

Sensory colour assessment of fresh meat from pigs supplemented with iron and vitamin E.

Pork muscle samples (M. longissimus dorsi) were obtained from pigs given one of four dietary treatments: (1) control diet; (2) supplemental iron [7-g iron (II) sulphate/kg feed]; (3) supplemental vitamin E (200-mg dl-α-tocopheryl acetate/kg of feed); and (4) supplemental vitamin E+supplemental iron. Muscle cores were packaged in polythene bags and placed in a retail refrigerated display cabinet at 5±1°C, under fluorescent light (1000 LUX) for up to 5 days. Samples were subjected to visual colour evaluation by a trained sensory panel (n=12) at 0, 1, 3 and 5 days. In addition instrumental L*, a* and b* values and drip loss were measured on each day of analysis. All samples became less red and browner over storage time in the refrigerated display cabinet. The vitamin E treated samples were more red and less brown compared with the other samples on successive days in the cabinet followed by the control, iron/vitamin E and iron treatments. The iron/vitamin E treatment was positioned midway between the vitamin E and iron treatments indicating that the vitamin E in the samples was effective in reducing the pro-oxidative effect of iron in inducing the brown metmyoglobin pigment development. Iron supplementation did not significantly (P<0.05) increase M. longissimus dorsi iron tissue levels, but had a detrimental effect on the visual sensory properties of the iron and iron/vitamin E treatment groups with greater metmyoglobin formation. Vitamin E appears to have promoted non-supplemental iron absorption in the vitamin E treated group without the detrimental sensory colour characteristics associated with ferrous sulphate supplementation. Drip loss increased in all samples during the course of the experiment with no significant (P<0.05) differences between the experimental groups. The panellists were able to differentiate the four experimental groups on each day of the study and were more effective in evaluating the colour quality of samples than instrumental assessment, i.e. the Hunter L* a* b* method.

The genotype-phenotype relationship in multicellular pattern-generating models - the neglected role of pattern descriptors

BackgroundA deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model. A pattern descriptor is a variable that describes and quantifies a certain qualitative feature of the pattern, for example the degree to which certain macroscopic structures are present. There is today no general procedure for how to relate a set of patterns and their characteristic features to the functional relationships, parameter values and initial values of an original pattern-generating model. Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters. The approach is illustrated on an existing model for Delta-Notch lateral inhibition over a two-dimensional lattice.ResultsBy combining computer simulations according to a succession of statistical experimental designs, computer graphics, automatic image analysis, human sensory descriptive analysis and multivariate data modelling, we derive a pattern descriptor model of those macroscopic, emergent aspects of the patterns that we consider of interest. The pattern descriptor model relates the values of the new, dedicated pattern descriptors to the parameter values of the original model, for example by predicting the parameter values leading to particular patterns, and provides insights that would have been hard to obtain by traditional methods.ConclusionThe results suggest that our approach may qualify as a general procedure for how to discover and relate relevant features and characteristics of emergent patterns to the functional relationships, parameter values and initial values of an underlying pattern-generating mathematical model.

Sensory profiling data studied by partial least squares regression

Abstract The statistical analysis of a descriptive sensory profiling data set distributed at the sensometrics meeting is presented. The data set is analysed with focus on the sensory differences between products (cooked potatoes). The data analytical strategy involves a descriptive statistical analysis to obtain an overview of the distribution and standard deviations of the scores for each sensory attribute. Subsequently, three-way analysis of variance (AVOVA) of the data gives a statistical measure of the reliability of the sensory attributes supplemented by principal component analysis, which visualise the main tendencies of systematic variation. Discriminant and ANOVA partial least squares regressions are used to relate the sensory structure to product design structure and vice versa. Statistical reliability and predictive validity of the product differences are obtained by ANOVA and cross-validation. Similar data structures are observed in the various multivariate models. Texture, taste and flavour attributes differentiated the potato samples, with the texture attributes being most reliable. It is emphasised that an appropriate interpretation of the profiling data should also include knowledge of the experimental background.

Three-Block Data Modeling by Endo- and Exo-LPLS Regression

In consumer science it is common to study how various products are liked or ranked by various consumers. In this context, it is important to check if there are different consumer groups with different product preference patterns. If systematic consumer grouping is detected, it is important to determine the person characteristics which differentiate between these consumer segments, so that they can be reached selectively. Likewise it is important to determine the product char- acteristics that consumer segments seem to respond differently to. Consumer preference data are usually rather noisy. The productspersons data table (X1) usually produced in consumer preference studies may therefore be supplemented with two types of background information: a productsproduct- property data table (X2 )a nd ap ersonperson-property data table (X3). These additional data may be used for stabilizing the data modeling of the preference data X1 statistically. Moreover, they can reveal the product-properties that are responded to differently by the different consumer segments, and the person-properties that characterize these different segments. The present chapter outlines a recent approach to analyzing the three types of data tables in an integrated fashion and presents new modeling methods in this context.

Combined Procrustes analysis and PLSR for internal and external mapping of data from multiple sources

Abstract Generalised Procrustes analysis (GPA) is a method for producing a group average from rotated versions of a set of individual data matrices followed by bi-linear approximation of this group average for graphical inspection. Partial Least Squares Regression (PLSR) is a method for relating one data matrix to another data matrix, via bi-linear low-rank regression modelling. The merger of these methods proposed aims to produce an average (e.g. a sensory group panel average), which balances an “intersubjective”, internal consensus between the individual assessors’ data against an “objective” external correspondence between the sensory data and other types of data on the same samples (e.g. design information, chemical or physical measurements or consumer data). Several ways of merging GPA with PLSR are possible, of which one is selected and applied. The proposed “GP–PLSR” method is compared to a conventional GPA followed by an independent PLSR, using a data set about milk samples assessed by a group of sensory judges with respect to a set of sensory descriptor terms, and also characterised by experimental design information about the samples. The GP–PLSR gave a more design-relevant group average than traditional GPA. The proposed algorithm was tested under artificially increased noise levels.