The aim of the present study was to develop a near-infrared reflectance(NIR) spectroscopy rapid method for evaluation of beef quality. Partial leastsquares (PLS) prediction model for the physic-chemical characteristics such asmoisture, fat, protein, pH, color and WBSF in beef was established with goodveracity. One hundred fourteen samples from five different parts of beef carcass(tenderloin, ribeye, topside, shin, striploin) were collected from meat packerafter 48 h aging. Spectra were obtained by scanning sample from 950 to 1 650 nmand pretreated the model by MSC, SNV and first derivative. Predictive correlationcoefficients of physic-chemical parameters in beef were 0.947 2(moisture), 0.9245(fat), 0.934 6(protein), 0.620 2(pH), 0.820 3(L), 0.864 6(a*), 0.753 0(b*) and0.475 9(WBSF) respectively. Root mean square errors of calibration (RMSEC) were0.313 3(moisture), 0.221 0(fat), 1.243 2(protein), 0.744 6(pH), 1.778 3(L*),1.394 2(a*), 1.763 9(b*) and 1.0743(WBSF). They were externally validated withadditional 30 beef samples. Statistics showed that there was no significantdifference between predicted value and those obtained with conventionallaboratory methods. The results showed that NIRS is a rapid, effective techniquefor evaluating beef quality. The predictions for chemical characteristics gavehigher accuracy than prediction for physical characteristics.(2004DA1251840802)资助