Contamination of annual ryegrass with perennial ryegrassby physical seed mixing or gene flow can result in a significant reduction in forage production.Therefore, this study aimed to develop a suitable technique using near-infrared spectroscopy (NIRS) for discriminating and quantifying adulteration of annual ryegrass seeds with perennial ryegrass. A partial least squares regression for discriminating analysis using visible and NIR region was developed using a calibration set(n=120), including 60 samples each of pure annual ryegrass seeds and those contaminated with perennial ryegrass at levels ranging from 10 to 990 g/kg. An independent validation set, consisting of 40 pure samples and 39 adulterated samples, was used to validate the calibration model.In all, 105 samples were used to develop the quantitative analysis model; with each sample subsequently spiked (10–990 g/kg; standard deviation: 294.2 g/kg). A discriminant analysis model developed with mathematic pretreatment 1,4,4,1 in NIR region (1100–2500 nm) successfully discriminated annual ryegrass adulterated with perennial ryegrass seed. A quantitative model developed with mathematic pretreatment 1,4,4,1 in NIR region (1100–2500 nm)also accurately predicted the adulteration with a standard error of cross validation of 76.91 g/kg and a ratio of performance deviationof 3.82. These results demonstrate the usefulness of NIRS combined with chemometrics as a rapid method for discrimination and quantification of perennial ryegrass in adulterated annual ryegrass seedsamples.