The dataset of the meat cuts classification based on electronic nose system

Published: 17 December 2019| Version 1 | DOI: 10.17632/kcy29m3zzz.1
Contributor:
Shoffi Sabilla

Description

Data was taken using a proposed electronic nose in 3 processes: flushing, sensing, and cleaning. The flushing process is transporting free air into the sensor chamber to obtain a baseline of free air. The sensing process is the time period when the gas moves from the sample chamber to the sensor chamber. The cleaning process is reverting air in the sensor chamber to the initial free air baseline. Each process has a specific execution time: 60 seconds flushing, 120 seconds sensing, and 180 seconds cleaning. The data distribution for one-time sampling is outlined in a comma separate value (.csv) format with the following column label: • time(s): time of measurement point (millisecond); • TGS 822: Response signal (mV) from TGS 822 sensor; • TGS 2612: Response signal (mV) from TGS 2612 sensor; • TGS 2620: Response signal (mV) from TGS 2620 sensor; • TGS 832: Response signal (mV) from TGS 832 sensor; • TGS 826: Response signal (mV) from TGS 826 sensor; • TGS 2603: Response signal (mV) from TGS 2603 sensor; • TGS 2600: Response signal (mV) from TGS 2600 sensor; • TGS 813: Response signal (mV) from TGS 813 sensor; • Humid: relative humidity (%) in the sensor chamber; • Temp: temperature (C) in the sensor chamber. The dataset was named according to class type. Two pork categories namely pork legs (PL) and pork belly (PB). Two beef category namely beef shank (BS) and beef ribs (BR). Two chicken categories namely chicken breast (CB) and chicken drumsticks (CD). The sample collection date is described as follows: a) Pork legs class (PL) total of 33 data b) Pork belly class (PB) total of 47 data c) Beef shank class (BS) total of 36 data d) Beef ribs class (BR) total of 25 data e) Chicken drumsticks class (CD) total of 51 data f) Chicken breast class (CB) total of 57 data

Files

Institutions

Institut Teknologi Sepuluh Nopember Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember

Categories

Agricultural Science, Chromatography, Machine Learning, Array Signal Processing, Electronic Nose, Gas Chromatography Mass Spectrometry

Licence