Pregled bibliografske jedinice broj: 1136829
Complementing Digital Image Analysis and Laser Distance Meter in Beer Foam Stability Determination
Complementing Digital Image Analysis and Laser Distance Meter in Beer Foam Stability Determination // Fermentation, 7 (2021), 3; 113, 11 doi:10.3390/fermentation7030113 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1136829 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Complementing Digital Image Analysis and Laser
Distance Meter in Beer Foam Stability Determination
Autori
Habschied, Kristina ; Glavaš, Hrvoje ; Nyarko, Emmanuel Karlo ; Mastanjević, Krešimir
Izvornik
Fermentation (2311-5637) 7
(2021), 3;
113, 11
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
image analysis ; laser distance meter ; beer foam
Sažetak
The aim of this research is to investigate the possibility of applying a laser distance meter (LDM) as a complementary measurement method to image analysis during beer foam stability monitoring. The basic optical property of foam, i.e., its high reflectivity, is the main reason for using LDM. LDM measurements provide relatively precise information on foam height, even in the presence of lacing, and provide information as to when foam is no longer visible on the surface of the beer. Sixteen different commercially available lager beers were subjected to analysis. A camera and LDM display recorded the foam behavior ; the LDM display which was placed close to the monitored beer glass. Measurements obtained by the image analysis of videos provided by the visual camera were comparable to those obtained independently by LDM. However, due to lacing, image analysis could not accurately detect foam disappearance. On the other hand, LDM measurements accurately detected the moment of foam disappearance since the measurements would have significantly higher values due to multiple reflections in the glass.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Interdisciplinarne tehničke znanosti, Prehrambena tehnologija
Napomena
This article belongs to the Special Issue Machine
Learning in Fermented Food and Beverages
POVEZANOST RADA
Ustanove:
Prehrambeno-tehnološki fakultet, Osijek,
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Profili:
Kristina Mastanjević
(autor)
Hrvoje Glavaš
(autor)
Krešimir Mastanjević
(autor)
Emmanuel Karlo Nyarko
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Emerging Sources Citation Index (ESCI)
- Scopus