USE OF COMPUTER VISION SYSTEMS TO DETECT PSE DEFECT IN PORK MEAT

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USE OF COMPUTER VISION SYSTEMS TO DETECT PSE DEFECT IN PORK MEAT

Journal Title: Żywność. Nauka. Technologia. Jakość - Year 2011, Vol 18, Issue 6

Abstract

The objective of the research study was to determine the possibility of using computer vision systems (CVS) to detect a PSE defect in pork meat. The research material comprised 42 pork longissimus dorsi muscles obtained under the industrial conditions. Based on the measurements of pH and colour lightness (L*), the raw material studied was classified into three quality groups: normal meat (RFN, i.e. reddish- pink, firm, non-exudative), PSE meat (pale, soft, exudative), and meat that did not meet any criteria of being classified into any of the two quality groups as above (NZ). The meat samples analyzed were photo- graphed and their images were analyzed in order to determine the values of colour components of the three models: RGB, HSV, and HSL. Based on the results obtained, it was found that CVS could be applied to detect a PSE defect in pork meat. For this purpose, the colour components of V (from the HSV model), L (from the HSL model), and R, G, B (from the RGB model) appeared to be most useful.

Authors and Affiliations

Marta Chmiel, Mirosław Słowiński, Paweł Cal

Keywords

PRZYDATNOŚĆ WYBRANYCH PARAMETRÓW OZNACZANYCH 45 MIN POST MORTEM W MIĘŚNIU LONGISSIMUS LUMBORUM DO OCENY JAKOŚCI WIEPRZOWINY

Celem przeprowadzonych badań było określenie przydatności takich parametrów, jak: zawartość kwasu mlekowego i glikogenu, pH45 oraz przewodność elektryczna (EC2) w mięśniu Longissimus lumborum (LL) do oceny jakości wiep...

Wpływ metody pakowania i przechowywania na właściwości fizykochemiczne mięsa królików żywionych mieszankami paszowymi wzbogaconymi olejem rybnym i witaminą E

EP ID EP163331
DOI 10.15193/2011/79/047-054
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