fruits {ade4} | R Documentation

## Pair of Tables

### Description

28 batches of fruits -two types- are judged by two different ways.
They are classified in order of preference, without ex aequo, by 16 individuals.
15 quantitative variables described the batches of fruits.

### Usage

    data(fruits)

### Format

`fruits` is a list of 3 components:

typ
  is a vector returning the type of the 28 batches of fruits (peaches or nectarines).
jug
  is a data frame of 28 rows et 16 columns (judges).
var
  is a data frame of 28 rows et 16 measures (average of 2 judgements).

### Details

`fruits$var` is a data frame of 15 variables:

1{_}taches
  : quantity of cork blemishes (0=absent - maximum 5)
2{_}stries
  : quantity of stria (1/none - maximum 4)
3{_}ab{_}muc
  : abundance of mucron (1/absent - 4)
4{_}ir{_}for
  : shape irregularity (0/none - 3)
5{_}allong
  : length of the fruit (1/round fruit - 4)
6{_}su{_}rou
  : percentage of the red surface (minimum 40% - maximum 90%)
7{_}ho{_}lot
  : homogeneity of the intra-batch coloring (1/strong - 4)
8{_}ho{_}fru
  : homogeneity of the intra-fruit coloring (1/strong - 4)
9{_}pubes
  : pubescence (0/none - 4)
10{_}vert
  : intensity of green in red area (1/none - 4)
11{_}fonc
  : intensity of dark area (0/pink - 4)
12{_}col{_}mu
  : intensity of the mucron color (1=no contrast - 4/dark)
13{_}impres
  : kind of impression (1/watched - 4/pointillé)
14{_}col{_}dom
  : intensity of the predominating color (0/clear - 4)
15{_}calib
  : grade (1/<90g - 5/>200g)

### Source

Kervella, J. (1991) Analyse de l'attrait d'un produit : exemple d'une comparaison de lots de pêches. Agro-Industrie et méthodes statistiques. Compte-rendu des secondes journées européennes. Nantes 13-14 juin 1991. Association pour la Statistique et ses Utilisations, Paris, 313–325.

### Examples

    data(fruits)
    par(mfrow = c(2,2))
    pcajug <- dudi.pca(fruits$jug, scann = FALSE)
    s.corcircle(pcajug$co)
    s.class(pcajug$li, fac = fruits$type)

    pcavar <- dudi.pca(fruits$var, scann = FALSE)
    s.corcircle(pcavar$co)
    s.class(pcavar$li, fac = fruits$type)

    par(mfrow = c(1,1))
    plot(coinertia(pcajug, pcavar, scan = FALSE))

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