[Application of near infrared spectral fingerprint technique in lamb meat origin traceability]

Near infrared spectra of 99 lamb meat samples from three pasturing areas and two farming areas of China were scanned and analyzed to seek a cheap, rapid and effective method for lamb meat origin traceability. Two chemometric methods including linear discriminant analysis based on principal component analysis (PCA+LDA) and partial least squares discriminant analysis (PLS-DA) were used to develop the discriminate models. It was showed that there were significantly differences among the lamb meat samples from five regions based on NIR spectra after second derivative (Savitzky-Golay, 9 point) and multiplicative scattering correction (MSC) transformation in the whole wavelength. The discrimination of two models was best for classification of pasturing area and farming area, with both correctly classified by 100%. The correct classification rate of samples from five different regions using PCA+LDA model was 91.2%, higher than using PLS-DA model (76.7%). These results demonstrate that near infrared reflectance spectroscopy (NIRS) combined with chemometric analysis can be used as an effective method to classify lamb meat according to its geographical origin.