The dataset of e-nose on beef quality monitoring under an uncontrolled environment

Published: 9 Jan 2019 | Version 1 | DOI: 10.17632/4n23zp92b5.1

Description of this data

This dataset is electronic nose signals for beef quality monitoring which labeled for two classes (fresh and spoiled), three classes (fresh, semi-fresh, and spoiled), four classes (excellent, good, acceptable, and spoiled), and continuous labels for regression analysis. In this experiment, the standard of beef quality refers to meat standard issued by Agricultural and Resource Management Council of Australia and New Zealand (CSIRO Food and Nutritional Sciences, 2003). The experiment was performed in the uncontrolled environment using 7 MOS gas sensors. The dataset is divided into training and testing (50%-50%). The explanation of each sheet as follows:
Two classes:

  1. molen_2class_testing_dwt
  2. molen_2class_testing_raw
  3. molen_2class_training_dwt
  4. molen_2class_training_raw
    Three classes:
  5. molen_3class_testing_dwt
  6. molen_3class_testing_raw
  7. molen_3class_training_dwt
  8. molen_3class_training_raw
    Four classes:
  9. molen_4class_testing_dwt
  10. molen_4class_testing_raw
  11. molen_4class_training_dwt
  12. molen_4class_training_raw
  13. molen_regression_testing_dwt
  14. molen_regression_testing_raw
  15. molen_regression_training_dwt
  16. molen_regression_training_raw
    “training” and “testing” parts imply data training and data testing, respectively.“The prefix “raw” and “dwt” denote raw and reconstructed signals, respectively. The reconstructed signals use fine-tuned discrete wavelet transform based on Information Quality Ratio (IQR) (Wijaya et al., 2016).

Experiment data files

This data is associated with the following publication:

Noise filtering framework for electronic nose signals: An application for beef quality monitoring

Published in: Computers and Electronics in Agriculture

Latest version

  • Version 1


    Published: 2019-01-09

    DOI: 10.17632/4n23zp92b5.1

    Cite this dataset

    Wijaya, Dedy; Zulaika, Enny; Sarno, Riyanarto (2019), “The dataset of e-nose on beef quality monitoring under an uncontrolled environment”, Mendeley Data, v1


Views: 475
Downloads: 12


Computer Science, Electronic Nose, Meat Odor


CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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