plspm (version 0.2-2)

orange: Orange Juice dataset

Description

This data set contains the physico-chemical, sensory and hedonic measurements of 6 orange juices.

Usage

orange

format

A data frame with 6 observations and 112 variables. The variables refer to three latent concepts: 1) PHYCHEM=Physico-Chemical, 2) SENSORY=Sensory, and 3) HEDONIC=Hedonic. llll{ Num Variable Description Concept 1 glucose Glucose (g/l) physico-chemical 2 fructose Fructose (g/l) physico-chemical 3 saccharose Saccharose (g/l) physico-chemical 4 sweet.power Sweetening power (g/l) physico-chemical 5 ph1 pH before processing physico-chemical 6 ph2 pH after centrifugation physico-chemical 7 titre Titre (meq/l) physico-chemical 8 citric.acid Citric acid (g/l) physico-chemical 9 vitamin.c Vitamin C (mg/100g) physico-chemical 10 smell.int Smell intensity sensory 11 odor.typi Odor typicity sensory 12 pulp Pulp sensory 13 taste.int Taste intensity sensory 14 acidity Acidity sensory 15 bitter Bitterness sensory 16 sweet Sweetness sensory 17 judge1 Ratings of judge 1 hedonic 18 judge2 Ratings of judge 2 hedonic ... ... ... ... 112 judge96 Ratings of judge 96 hedonic }

source

Laboratoire de Mathematiques Appliques, Agrocampus, Rennes.

References

Tenenhaus, M., Pages, J., Ambroisine, L., and Guinot, C. (2005) PLS methodology to study relationships between hedonic jedgements and product characteristics. Food Quality and Preference, 16(4), pp. 315-325. Pages, J., and Tenenhaus, M. (2001) Multiple factor analysis combined with PLS path modelling. Application to the analysis of relationships between physicochemical, sensory profiles and hedonic judgements. Chemometrics and Intelligent Laboratory Systems, 58, pp. 261-273. Pages, J. (2004) Multiple Factor Analysis: Main Features and Application to Sensory Data. Revista Colombiana de Estadistica, 27, pp. 1-26.

Examples

data(orange)
  orange