Sensory, rheological, chemical and spectroscopic analysis of potatoes.

A dataset containing 9 blocks of measurements on 26 potatoes. Original dataset can be found at http://models.life.ku.dk/Texture_Potatoes. This version has been pre-processed as follows (corresponding to Liland et al. 2016):

• Variables containing NaN have been removed.

• Chemical and Compression blocks have been scaled by standard deviations.

• NIR blocks have been subjected to SNV (Standard Normal Variate).

Usage

data(potato)

Format

A data.frame having 26 rows and 9 variables:

Chemical

Matrix of chemical measurements

Compression

Matrix of rheological compression data

NIRraw

Matrix of near-infrared measurements of raw potatoes

NIRcooked

Matrix of near-infrared measurements of cooked potatoes

CPMGraw

Matrix of NMR (CPMG) measurements of raw potatoes

CPMGcooked

Matrix of NMR (CPMG) measurements of cooked potatoes

FIDraw

Matrix of NMR (FID) measurements of raw potatoes

FIDcooked

Matrix of NMR (FID) measurements of cooked potatoes

Sensory

Matrix of sensory assessments

References

• L.G.Thygesen, A.K.Thybo, S.B.Engelsen, Prediction of Sensory Texture Quality of Boiled Potatoes From Low-field1H NMR of Raw Potatoes. The Role of Chemical Constituents. LWT - Food Science and Technology 34(7), 2001, pp 469-477.

• Kristian Hovde Liland, Tormod Næs, Ulf Geir Indahl, ROSA – a fast extension of Partial Least Squares Regression for Multiblock Data Analysis, Journal of Chemometrics 30:11 (2016), pp. 651-662.