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.