Authentication Nursel Söylemez Milli · Meat species identification · DNA methods · proteomics · rapid screening · 2 min read
Meat species identification is essential for protecting consumers against economic fraud, ensuring compliance with labelling regulations, meeting religious and cultural dietary requirements and safeguarding public health. Substitution of high-value meats with cheaper species, undeclared addition of pork or poultry, and the use of meat from unauthorized species are among the most common forms of meat fraud. The European horsemeat scandal of 2013 clearly demonstrated the vulnerability of complex supply chains and accelerated the development of more sensitive and rapid identification methods.
DNA-based techniques remain the most established approaches. Conventional and real-time PCR targeting mitochondrial genes, such as cytochrome b, cytochrome c oxidase I and 12S/16S rRNA, provide high specificity and sensitivity. Multiplex PCR allows several species to be detected simultaneously. Droplet digital PCR has been increasingly used for absolute quantification of species in meat mixtures, offering high precision and tolerance to inhibitors. DNA barcoding and next-generation sequencing-based metabarcoding enable untargeted identification of multiple species in a single analysis, which is particularly useful when the potential adulterant is unknown. Bioinformatics tools also play an important role in the design of species-specific primers and probes.
Protein-based approaches are gaining importance, especially for processed products in which DNA may be degraded. Liquid chromatography–tandem mass spectrometry allows the detection of species-specific marker peptides with high specificity and can be used for quantification. MALDI-TOF mass spectrometry provides rapid protein and peptide fingerprints, and myoglobin and other muscle proteins have been investigated as species markers. Immunoassays remain useful for routine screening because of their simplicity and low cost.
Spectroscopic methods, such as near-infrared, mid-infrared, Raman and hyperspectral imaging, combined with chemometrics, provide rapid and non-destructive analysis with minimal sample preparation. These approaches are suitable for screening large numbers of samples, although they generally have higher detection limits than molecular methods.
Sensor-based systems and machine learning represent a newer direction. Electronic noses and gas sensor arrays capture the volatile fingerprint of meat samples, and classification algorithms can be trained to distinguish species and detect mixtures. Low-cost metal oxide sensors with temperature modulation have shown potential for portable species recognition and halal screening. Machine learning is also being applied to spectral and mass spectrometry data to improve classification accuracy.
Each technique has specific advantages and limitations in terms of sensitivity, quantification capability, cost, speed and applicability to processed products. Consequently, a tiered strategy is increasingly recommended, in which rapid screening methods are used to identify suspicious samples and confirmatory molecular or mass spectrometry methods are applied for verification.
Future developments are expected to focus on portable and on-site devices, untargeted multi-species detection, harmonized quantification approaches, certified reference materials and the integration of analytical data with digital traceability systems. Such advances will strengthen the ability of authorities and industry to ensure the authenticity of meat products.