Strawberry: Strawberry dataset

In moviedo5/fda.tsc: Functional Data Sets for Time Series Classification

Description

Food spectrographs are used in chemometrics to classify food types, a task that has obvious applications in food safety and quality assurance. The classes are strawberry (authentic samples) and non-strawberry (adulterated strawberries and other fruits). Obtained using Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) sampling.

Usage

data(Strawberry)

Format

The variables are as follows:

• df: data.frame with the following variables:

  • class: Corresponding class level of “Strawberry” curves with 2 classes.

  • sample:Factor variable. In TSC database, the first 613 values (sample=train) are used for training sample and the rest of 370 (sample=test) for testing.

• x: fdata class object with with n=983 curves (per row) in 235 discretization points (per column).

Details

As described in Use of Fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purees, see references.

Source

https://csr.quadram.ac.uk/example-datasets-for-download/ and http://timeseriesclassification.com/description.php?Dataset=Strawberry

References

Holland, J. K., Kemsley, E. K., Wilson, R. H. (1998). Use of Fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purees. Journal of the Science of Food and Agriculture, 76(2), 263-269. https://doi.org/10.1002/(SICI)1097-0010(199802)76:2<263::AID-JSFA943>3.0.CO;2-F

moviedo5/fda.tsc documentation built on May 16, 2019, 12:10 a.m.