ppls (version 2.0.0)

cookie: Near-Infrared (NIR) Spectroscopy of Biscuit Doughs

Description

This dataset contains measurements from a quantitative NIR spectroscopy experiment designed to evaluate the feasibility of using NIR spectra to estimate the chemical composition of unbaked biscuit doughs.

Usage

data(cookie)

Format

A list of 2 data-frames of 72 observations:

NIR

NIR reflectance spectrum values from 1100 to 2498 nm on 700 columns.

constituents

Percentage of fat, sucrose, dry flour and water in the 72 samples.

Details

Two sets of samples were prepared with variations in a standard biscuit recipe to produce a broad range for each of the four ingredients of interest: fat, sucrose, dry flour, and water.

The first 40 samples correspond to a calibration (training) set, and the remaining 32 samples form a validation (prediction) set. Sample 23 (training) and sample 21 (test) are known outliers.

Each sample is represented by an NIR reflectance spectrum composed of 700 values measured between 1100 and 2498 nanometers, at 2 nm intervals. The last 4 columns represent the percentage of each constituent.

References

• P.J. Brown, T. Fearn, and M. Vannucci (2001). Bayesian Wavelet Regression on Curves with Applications to a Spectroscopic Calibration Problem. Journal of the American Statistical Association, 96, pp. 398–408.

• B.G. Osborne, T. Fearn, A.R. Miller, and S. Douglas (1984). Application of Near-Infrared Reflectance Spectroscopy to Compositional Analysis of Biscuits and Biscuit Dough. Journal of the Science of Food and Agriculture, 35, pp. 99–105.

Examples

data(cookie) # load data
X <- cookie$NIR       # NIR spectra
Y <- cookie$constituents     # constituent values
Xtrain <- X[1:40, ]; Ytrain <- Y[1:40, ]   # calibration set
Xtest <- X[41:72, ]; Ytest <- Y[41:72, ]   # validation set