Electronic nose dataset for pork adulteration in beef

Riyanarto Sarno; Shoffi Izza Sabilla; Dedy Rahman Wijaya; Dwi Sunaryono; Chastine Fatichah

doi:10.1016/j.dib.2020.106139

Electronic nose dataset for pork adulteration in beef

Data Brief. 2020 Aug 7:32:106139. doi: 10.1016/j.dib.2020.106139. eCollection 2020 Oct.

Authors

Riyanarto Sarno¹, Shoffi Izza Sabilla¹, Dedy Rahman Wijaya², Dwi Sunaryono¹, Chastine Fatichah¹

Affiliations

¹ Department of Informatics, Institut Teknologi Sepuluh Nopember, Jalan Raya ITS, Keputih, Sukolilo, Surabaya, East Java, Indonesia (60111).
² School of Applied Science, Telkom University, Jalan Telekomunikasi Terusan Buah Batu, Bandung, West Java, Indonesia (40257).

Abstract

This article provides a dataset of several weight combinations from the adulteration of pork in beef using an electronic nose (e-nose). Seven combinations mixtures have been built, they were 100% pure beef, 10% mixed with pork, 25% mixed with pork, 50% mixed with pork, 75% mixed with pork, 90% mixed with pork, and 100% pure pork. By using this combination, a minimum of 10% of a mixture of pork or beef can be detected. In each experiment cycle, data were collected for 120 s using an e-nose. The availability of this dataset can enable further research about meat adulteration, Halal authentication, etc. For several cases, food adulteration is one of the main concerns in food science, for example, due to economic, religious reasons, etc. This dataset can also be utilized as the data source for several interesting topics such as signal processing, sensor selection, e-nose development, machine learning algorithms, etc.

Keywords: Electronic nose; adulteration; beef; pork; signal processing.