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Development of class model based on blood biochemical parameters as a diagnostic tool of PSE meat.
- Source :
-
Meat science [Meat Sci] 2017 Jun; Vol. 128, pp. 24-29. Date of Electronic Publication: 2017 Feb 01. - Publication Year :
- 2017
-
Abstract
- A fast, sensitive and effective method based on the blood biochemical parameters for the detection of PSE meat was developed in this study. A total of 200 pigs were slaughtered in the same slaughterhouse. Meat quality was evaluated by measuring pH, electrical conductivity and color at 45min, 2h and 24h after slaughtering in M. longissimus thoracis et lumborum (LD). Blood biochemical parameters were determined in blood samples collected during carcass bleeding. Principal component analysis (PCA) biplot showed that high levels of exsanguination Creatine Kinase, Lactate Dehydrogenase, Aspertate aminotransferase, blood glucose and lactate were associated with the PSE meat, and the five biochemical parameters were found to be good indicators of PSE meat Discriminant function analysis (DFA) was able to clearly identify PSE meat using the five biochemical parameters as input data, and the class model is an effective diagnostic tool in pigs which can be used to detect the PSE meat and reduce economic loss for the company.<br /> (Copyright © 2017 Elsevier Ltd. All rights reserved.)
- Subjects :
- Abattoirs
Animals
Aspartate Aminotransferases blood
Biomarkers blood
Blood Glucose analysis
China
Creatine Kinase blood
Crosses, Genetic
Discriminant Analysis
Electric Conductivity
Food Inspection
Hydrogen-Ion Concentration
L-Lactate Dehydrogenase blood
Lactic Acid blood
Meat classification
Muscle, Skeletal chemistry
Pigments, Biological analysis
Principal Component Analysis
Sus scrofa blood
Food Quality
Meat analysis
Meat-Packing Industry methods
Models, Biological
Muscle, Skeletal growth & development
Sus scrofa growth & development
Subjects
Details
- Language :
- English
- ISSN :
- 1873-4138
- Volume :
- 128
- Database :
- MEDLINE
- Journal :
- Meat science
- Publication Type :
- Academic Journal
- Accession number :
- 28167402
- Full Text :
- https://doi.org/10.1016/j.meatsci.2017.01.012