A SIMPLE ALTERNATIVE TO GENERALIZED PROCRUSTES ANALYSIS: APPLICATION TO SENSORY PROFILING DATA

A statistical method for analyzing sensory profiling data obtained by means of fixed vocabulary or free choice profiling is discussed. The most interesting feature of this method is that it involves only simple statistical treatment and can therefore be performed using standard software packages. The outcomes of this method are compared to those of Generalized Procrustes Analysis on the basis of two data sets obtained, respectively, by means of fixed vocabulary and free choice profiling. A significance test is also discussed in order to assess whether the overall configuration of the products is meaningful. This significance test is based upon a simulation study involving the permutation procedure.     

IDENTIFYING ASSESSOR DIFFERENCES IN WEIGHTING THE UNDERLYING SENSORY DIMENSIONS

In a previous paper Kunert and Qannari (1999) discussed a simple alternative to Generalized Procrustes Analysis to analyze data derived from a sensory profiling study. After simple pretreatments of the individual data matrices, they propose to merge the data sets together and undergo Principal Components Analysis of the matrix thus formed. On the basis of two data sets, it was shown that the results slightly differ from those obtained by means of Generalized Procrustes Analysis.
In this paper we give a mathematical justification to this approach by relating it to a statistical regression model. Furthermore, we obtain additional information from this method concerning the dimensions used by the assessors as well as the contribution of each assessor to the determination of these dimensions. This information may be useful to characterize the performance of the assessors and single out those assessors who downweight or overweight some dimensions. In particular, those assessors who overweight the last dimensions should arouse suspicion regarding their performance as, in general, the last dimensions in a principal components analysis are deemed to reflect random fluctuations.     

DETECTION AND INTERPRETATION OF VARIATION WITHIN AND BETWEEN ASSESSORS IN SENSORY PROFILING

In this paper we discuss methods that can be used to evaluate the performance of sensory panels. In particular we concentrate on detection of variation within and among panelists. A systematic presentation of some simple, graphically oriented tools will be given. Interpretation aspects of the tools will be emphasized. The methods will be illustrated by computations from a sensory experiment based on 4 sausage products. The example demonstrates how the tools can be used to evaluate the reproducibility of the assessors and also how they can be used to detect different types of individual differences among the assessors.     

USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS

Natural selection shapes patterns of genetic variation among individuals, populations, and species, and it does so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of the action of selection, even beyond traditional model organisms. However, even with nearly complete genomic sequence information, our ability to detect the signature of selection on specific genomic regions depends on choosing experimental and analytical tools appropriate to the biological situation. For example, processes that occur at different timescales, such as sorting of standing genetic variation, mutation-selection balance, or fixed interspecific divergence, have different consequences for genomic patterns of variation. Inappropriate experimental or analytical approaches may fail to detect even strong selection or falsely identify a signature of selection. Here we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and identify major biological factors to be considered in studies of selection. As data-gathering technology continues to advance, our ability to understand selection in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data. Our aim is to bring critical biological considerations to the fore in population genomics research and to spur the development and application of analytical tools appropriate to diverse biological systems.     

INDIVIDUAL AND SUBSTANCE DIFFERENCES IN THE DISCRIMINABILITY OF OPTICAL ISOMERS

An analysis of the discriminability of 10 enantiomeric pairsof substances revealed both significant individual differencesamong the 31 Ss and significant differences in discriminabilityof the substances. Since a significant S by substance interactionwas found, a factor analysis was applied to the data. Two factorswere found. It was suggested that different protein bindingsites would account for the results. ^* Supported in part by a grant from the Research Committee,University of California, Los Angeles.     

A SIMPLE PROCEDURE TO DETECT NISIN IN CHEESE

SUMMARY: A suitable amount of agar medium inoculated with a test organism sensitive to nisin ( Lactobacillus lactis or Streptococcus cremoris ) is poured on a cheese cylinder placed in a Petri dish. After a convenient incubation time the presence of a clear zone around the cheese cylinder will indicate the presence of nisin.
The method is applicable both to natural and processed cheese and can also be used for other antibiotics that may be present in cheese.     

USE OF INDIVIDUAL DIFFERENCES SCALING FOR SENSORY STUDIES: SIMULATED RECOVERY OF STRUCTURE UNDER VARIOUS MISSING VALUE RATES AND ERROR LEVELS

The use of Individual Differences Scaling in sensory studies has been limited because the number of pairwise comparisons in a complete design can be prohibitively large. This study examines the effect of different levels of error and missing data on recovery of true structure by Individual Difference Scaling for the normal range of assessors and stimuli (8–16) used by sensory workers. Recovery was very good for a missing value rate of 20%. It was good for 40% provided that the number of stimuli was high, but deteriorated sharply at 60% missing data. The effect of superimposing random error on to the true structure indicated that a large error rate gave poor recovery. It is concluded that up to 40% of the distances in a complete design could be excluded, provided that replicate measurements indicated error levels were not severe.     

INTERINDIVIDUAL DIFFERENCES IN NEUROBEHAVIORAL PERFORMANCE IN RESPONSE TO INCREASING HOMEOSTATIC SLEEP PRESSURE

Neurobehavioral function deteriorates with increasing homeostatic sleep pressure during wakefulness. It has been claimed that some individuals exhibit a quicker rate of such deterioration than others, thus being more vulnerable than others to the detrimental impact of increasing homeostatic sleep pressure. Evidence supporting the claim, however, has been limited by methodological issues. To overcome these limitations, the current study used a 12-calendar-day, 28-h forced desynchrony (FD) protocol (sleep:wake period?=?1:2) to study individual differences in the rate of change in neurobehavioral performance with increasing homeostatic sleep pressure. Neurobehavioral performance was assessed with a psychomotor vigilance task and a serial addition subtraction task. A significant performance decline on both tasks was revealed within as short as 17?h of wakefulness. The rates of decline of individual performance trajectories were, however, not different from the group average rate. This suggests that individuals are not differentially vulnerable to the detrimental impact of increasing homeostatic sleep pressure. (Author correspondence: xuan.zhou@unisa.edu.au)     

THE EVOLUTION OF RESISTANCE TO HERBIVORY IN IPOMOEA PURPUREA. I. ATTEMPTS TO DETECT SELECTION

In this study, we looked for evidence of directional or stabilizing/disruptive selection on plant size and on the level of damage (resistance) caused by four types of herbivores in the annual morning glory Ipomoea purpurea. Selection was estimated by standard phenotypic regression analysis and by regression on breeding values. The phenotypic regression analysis revealed directional selection for all five characters (i.e., plant size and resistance to four types of herbivores) and indicated that plant size and resistance to corn-earworm damage were subject to stabilizing selection. By contrast, the analysis using breeding values revealed directional selection only for plant size and resistance to corn earworms, while none of the characters examined indicated stabilizing or disruptive selection. These results suggest that intermediate levels of damage in I. purpurea are, in general, not maintained by stabilizing selection. Rather, they may reflect either 1) a transient state that exists while directional selection pushes the population toward complete resistance (or, in one case, total absence of resistance) or 2) the evolution of susceptibility to damage by genetic drift.     

SENSORY SPECIFIC SATIETY IN LEMONADE USING A JUST RIGHT SCALE FOR SWEETNESS1

Lemonade samples varying in sucrose concentration (4-15%) were evaluated by either a sip procedure (subjects tasted 10 mL samples) or a drink procedure (subjects consumed 60 mL samples) using a “just right” scale. The order of tasting the four lemonade samples was also balanced among subjects. Neither the amount of lemonade consumed during the test nor the sex of the subjects had an effect on the scores assigned to the samples or the just right sucrose concentration determined by linear regressions. The less pleasant samples (those scored farther from the just right point) showed sensory specific satiety evidenced by a shift away from the just right point on repeated tasting. Samples rated more pleasant or closer to the just right point did not show evidence of sensory specific satiety.