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Short Communication

Discrimination of meat patés according to the animal species by means of near infrared spectroscopy and chemometrics

Discriminación de muestras de paté de carne según tipo de especie mediante el uso de la espectroscopia en el infrarrojo cercano y la quimiometria

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Pages 210-213 | Received 22 Apr 2010, Accepted 24 Jul 2010, Published online: 27 Jul 2011
 

Abstract

Commercial meat paté samples, comprised of 100% pork (n = 7), 100% beef (n = 5) meat, and binary mixtures (beef and pork, w/w) (n = 18) were used. Fresh samples were analysed in a scanning spectrophotometer NIRSystems 6500 in reflectance mode (1100–2500 nm). Principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were used to classify samples according to the animal species based on their near infrared reflectance (NIR) spectra. Full cross validation was used as validation method when classification models were developed. Both beef and pork paté samples were classified correctly (100%) while binary mixture samples only achieved 72% of correct classification using SLDA technique. The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method to classify paté samples according to meat type. Nevertheless, NIR spectroscopic methods might provide initial screening in the food chain and enable more costly methods to be used more efficiently.

Se utilizaron muestras de patés de carne comerciales, compuestos de 100% carne de cerdo (n = 7), 100% carne de buey (n = 5) y mezclas binarias (buey y cerdo) (n = 18). Las muestras frescas se analizaron en un espectrofotómetro de escaneo NIRSystems 6500 en modo reflectante (1100–2500 nm). El análisis de componente principal (PCA) y el análisis discriminante lineal progresivo (SLDA) se usaron para clasificar muestras de según las especie animal basándose en sus espectros NIR. La validación cruzada completa se utilizó como método de validación cuando se desarrollaron métodos de clasificación. Las muestras de ambos patés, de buey y cerdo, se clasificaron correctamente (100%), mientras las muestras de mezcla binaria sólo alcanzaron un 72% de clasificación correcta usando la técnica SLDA. Los resultados mostraron la utilidad del espectro NIR combinado con quimometria como un objetivo y método rápido para clasificar muestras de paté según el tipo de carne. Sin embargo, los métodos espectroscópicos NIR podrían proveer una revisión inicial de la cadena de comida y permitir que métodos costosos fuesen usados más eficientemente.

Acknowledgements

The work was supported by the National Institute for Agricultural Research (INIA) – Uruguay.

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