Predicting Beef Carcass Fatness Using an Image Analysis System.
carcass fatness
image analysis
prediction
young bulls
Journal
Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614
Informations de publication
Date de publication:
05 Oct 2021
05 Oct 2021
Historique:
received:
14
09
2021
revised:
30
09
2021
accepted:
01
10
2021
entrez:
23
10
2021
pubmed:
24
10
2021
medline:
24
10
2021
Statut:
epublish
Résumé
The amount and distribution of subcutaneous fat is an important factor affecting beef carcass quality. The degree of fatness is determined by visual assessments scored on a scale of five fatness levels (the SEUROP system). New technologies such as the image analysis method have been developed and applied in an effort to enhance the accuracy and objectivity of this classification system. In this study, 50 young bulls were slaughtered (570 ± 52.5 kg) and after slaughter the carcasses were weighed (360 ± 33.1 kg) and a SEUROP system fatness score assigned. A digital picture of the outer surface of the left side of the carcass was taken and the area of fat cover (fat area) was measured using an image analysis system. Commercial cutting of the carcasses was performed 24 h post-mortem. The fat trimmed away on cutting (cutting fat) was weighed. A regression analysis was carried out for the carcass cutting fat (
Identifiants
pubmed: 34679918
pii: ani11102897
doi: 10.3390/ani11102897
pmc: PMC8532829
pii:
doi:
Types de publication
Journal Article
Langues
eng
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