winetaste {eba}

Wine Tasting Data

Description

Paired comparison judgments for two wine tasting studies: ambilight includes the results of a study on the effect of ambient lighting on the flavor of wine; redwines includes judgments on the sensory quality of red wines.

Usage

data("winetaste")

Format

ambilight A data frame containing 230 observations on 10 variables:

preference, fruitiness, spiciness, sweetness

Paired comparison of class paircomp; judgments for one of the 6 ordered pairs of the blue, red, and white lighting conditions.

age

subject age

gender

factor, subject gender

sensesmell

self-rating of sense of smell and taste.

likewine

self-rating of general liking of wine.

drinkwine

factor, frequency of wine consumption.

redwhite

factor, preference for red or white wine.

redwines A data frame containing 11 observations on 7 variables:

bitterness, fruitiness, sourness, roundness, preference

Paired comparison of class paircomp; judgments for all 10 pairs from 5 red wines: Primitivo di Manduria, Cotes du Rhone, Bourgogne, Shiraz cuvee, Cabernet Sauvignon.

best

factor, Which of the five wines did you like best?

worst

factor, Which of the five wines did you like worst?

Details

The ambilight data are from Experiment 3 in Oberfeld et al. (2009). The redwines data were collected among the members of the Sound Quality Research Unit (SQRU), Department of Acoustics, Aalborg University, Denmark, in 2004. Details of the red wines are available as an attribute of the preference variable (see Examples).

References

Oberfeld, D., Hecht, H., Allendorf, U., & Wickelmaier, F. (2009). Ambient lighting modifies the flavor of wine. Journal of Sensory Studies, 24(6), 797–832. doi: 10.1111/j.1745-459X.2009.00239.x

See Also

eba, eba.order, paircomp.

Examples

requireNamespace("psychotools")
data(winetaste)

## No effect of ambient lighting on flavor (Oberfeld et al., 2009)

m <- lapply(ambilight[, c("preference", "fruitiness",
                          "spiciness", "sweetness")],
            function(x) eba.order(summary(x, pcmatrix = TRUE)))
lapply(m, summary)

u <- sapply(m, uscale, norm = 3)
dotchart(
  u, xlim = c(0.5, 2), pch = 16, panel.first = abline(v = 1, col = "gray"),
  main = "Ambient lighting and the flavor of wine",
  xlab = "Utility scale value (Davidson-Beaver model)"
)
ci <- sapply(m, function(x) 1.96 * sqrt(diag(cov.u(x))))
arrows(
  u - ci, c(16:18, 11:13, 6:8, 1:3), u + ci, c(16:18, 11:13, 6:8, 1:3),
.05, 90, 3)
mtext("Oberfeld et al. (2009)", line = 0.5)

## Sensory quality of red wines

psychotools::covariates(redwines$preference)  # details of the wines

m <- lapply(redwines[, c("bitterness", "fruitiness", "sourness",
                         "roundness", "preference")],
            function(x) eba(summary(x, pcmatrix = TRUE)))
lapply(m, summary)

u <- sapply(m, uscale)
dotchart(
  u[order(u[, "preference"]), ], log = "x",
  panel.first = abline(v = 1/5, col = "gray"),
  main = "SQRU red wine tasting",
  xlab = "Utility scale value (BTL model), choice proportion (+)"
)
points(as.vector(
  prop.table(table(redwines$best))[order(u[, "preference"])]
), 1:5, pch = 3)