Journal ArticleDOI
Multivariate analysis of flavour terms used by experts and non-experts for describing teas
TLDR
In this paper, three multivariate methods of analysis were applied to the problem of selecting the most important descriptions of tea from a list of 11 relevant ones, and the value of using more than one method of multivariate analysis is stressed.Abstract:
Three multivariate methods of analysis were applied to the problem of selecting the most important descriptions of tea from a list of 11 relevant ones. Principal component analysis gave useful information with data from homogeneous groups of experts but not with data from an heterogeneous group of non-experts. When cluster analysis was used to give homogeneous groups of non-experts from the heterogeneous one then principal component analysis again gave useful and similar information. Stepwise discriminant analysis gave different results from that of principal component analysis, a quite logical solution. The value of using more than one method of multivariate analysis is stressed.read more
Citations
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Effect of training procedure on the performance of descriptive panels
C.J. Wolters,E.M. Allchurch +1 more
TL;DR: In this paper, the authors discuss some theoretical problems with respect to the criteria mentioned in the literature for measuring panel performance and describe an experiment in which four panels, differing in training background, were used to profile the same 16 samples of orange juice.
Journal ArticleDOI
Relating sensory properties of tea aroma to gas chromatographic data by chemometric calibration methods
TL;DR: In this paper, stepwise multiple linear regression analysis (MLR), principal component regression (PCR), and partial least squares (PLS) regression analyses were comparatively applied to the sensory scores and the 77 GC peaks.
Journal ArticleDOI
Development of a preliminary sensory lexicon and standard references of ewes milk cheeses aided by multivariate statistical procedures
TL;DR: In this article, a new descriptive and discriminative language and a set of standard references for evaluating the main sensory characteristics of ewes milk cheeses have been developed and two multivariate statistical procedures, stepwise discriminant analysis (SDA) and principal component analysis (PCA), were applied during the development and selection of the sensory attributes.
Journal ArticleDOI
Volatile compounds of rehydrated French beans, bell peppers and leeks. Part II. Gas chromatography/sniffing port analysis and sensory evaluation
TL;DR: In this paper, the odour profiles of rehydrated diced French beans, red bell peppers and leeks were characterized by gas chromatography/sniffing port analysis (GC/SP) of volatile compounds released in a mouth model system and by descriptive sensory analysis.
Journal ArticleDOI
Classification of tea samples by their chemical composition using discriminant analysis.
TL;DR: Multivariate analysis in combination with pattern recognition procedures has been applied to samples of green and black tea for classification purposes.
References
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Journal ArticleDOI
Stepwise Discriminant Analysis of Gas Chromatographic Data as an Aid in Classifying the Flavor Quality of Foods
TL;DR: In this paper, a stepwise discriminant analysis for classifying food samples (known independently to differ in flavor) is illustrated by computer analysis of gas chromatograms from roasted coffee and potato chips.
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MEAT TEXTURE: I. Subjective Assessment of the Texture of Cooked Beef
TL;DR: In this article, a panel of 12 tasters were selected for discrimination and consistency over a series of training sessions during which a descriptive score sheet was developed through repeated discussion, and eight characteristics were decided upon to describe the texture of roast beef; seven on scales (resistance, wetness, juiciness, cohesiveness, hardness, overall texture, chew count) and one qualitative (adjectival descriptions).
Journal ArticleDOI
Numerical Classification Method for deriving Natural Classes
TL;DR: The current approach in numerical taxonomy is directed towards the so-called “minimum-variance” solution, for which it is argued that a population should be partitioned into cluster subsets by minimizing the total within group variation.
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COLLECTION AND CLASSIFICATION OF WORDS FOR DESCRIPTION OF FOOD TEXTURE: III: Classification by Multivariate Analysis.
TL;DR: A correlation matrix was computed from the rating score matrix of texture profiles of 79 foods, which yielded eight orthogonal factors and the most important dimensions were hard, soft, cold, warm, oily and juicy.