The fatty acid concentrations in maiz grain were analyzed with a set of 294 samples including normal inbred lines,high-oil inbred lines and high-oil recombinant inbred lines (RIL).The method of partial least squares (PLS) regression with internal cross validation was employed to develop the measuring models of near-infrared reflectance spectroscopy (NIRS) for concentrations of four major fatty acids,palmitic,stearic,oleic and linoleic acids,as well as oil concentration in maizE_grain.The NIRS models were accurate for oleic acid,linoleic acid and oil concentrations.The determination coefficients of these models in cross validation were 0.89,0.88 and 0.91,respectively;the determination coefficients in external validation were 0.86,0.84 and 0.92,respectively;and the ratio of standard deviation (SD) to root mean square error of validation (RMSEV) in both calibration and external validation sets (RSC(P)) was higher thaN₂.5.But the models for palmitic and stearic acid concentrations were not accurate enough with determination coefficients in cross validation and external validation lower than 0.80,and RSC(P) lower thaN₂.5.Further practical validation showed that the predicted results by using NIRS models for oleic acid,linoleic acid and oil concentrations were accurate and reliable,which will be a useful approach to the measurement of a large number of breeding samples during genetic improvement of oil quality and quantity in maize.