Post-Slaughter Age Classification and Sex Determination in Deboned Beef Using Lipofuscin Autofluorescence and Amelogenin Gene Analysis
Beef meat quality and value are influenced by the breed, sex, and age of slaughtered animals. This study aimed to evaluate lipofuscin pigment autofluorescence as a method for age classification in beef meat samples and to determine the sex of market-obtained meat using PCR-based amelogenin gene amplification. Deboned beef meat samples from <i>M. longissimus</i> dorsi and <i>M. biceps femoris</i> were collected from 67 slaughtered cows with known age and sex. Additionally, 48 market samples were tested for sex identification and age classification using the same methods. Lipofuscin deposition was first observed at 1.5 years, and autofluorescence analysis effectively distinguished between meat from younger animals (1.5-2.2 years) and older ones (3-13 years), with a statistically significant difference (<i>p</i> < 0.001). Lipofuscin levels and excitation intensity increased with age, and no differences were found between the two muscles analyzed. The sex determination results were fully consistent with the records, and 55.2% of animals aged 3 years and older were identified as female. These findings demonstrate the reliability of lipofuscin autofluorescence for binary age determination in beef and support the potential of combining age and sex classification to identify meat derived from older dairy cows in the marketplace.
Authors
- Büşra Cumhur
- Oğuz Kul (ORCID: https://orcid.org/0000-0002-1282-650X)
- Mustafa Yenal Akkurt (ORCID: https://orcid.org/0000-0002-8139-0252)
- Bengi Çınar Kul (ORCID: https://orcid.org/0000-0002-8955-0097)
- Tuğçe Anteplioğlu (ORCID: https://orcid.org/0000-0001-7033-0759)
- Ufuk Kaya (ORCID: https://orcid.org/0000-0002-4805-0993)
Institutions
- Ankara University (TR)
- Kırıkkale University (TR)
- Mustafa Kemal University (TR)
Publication Details
- Journal
- Veterinary Sciences
- Published
- 2025-06-17
- DOI
- https://doi.org/10.3390/vetsci12060593
- Primary Topic
- Identification and Quantification in Food
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ankara Universitesi