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Deep frying oils are subjected to high temperature and prolonged heating that may lead to a series of quality and safety problems for fried foods. This study evaluated the quality of deep frying oils collected from a local college canteen ( n= 132) with Fourier transform mid-infrared (FT-IR) and Fourier transform near-infrared (FT-NIR) spectroscopy. Partial least squares (PLS) regression was used to correlate spectral data with free fatty acids (FFA) and peroxide (PO) values of frying oils. The coefficient of determination ( R2), standard error of prediction (SEP), and the RPD (ratio of the standard deviation of data set to the SEP) were used as indicators for the predictability of the PLS models. The FT-IR and FT-NIR methods exhibited similar predictability for the FFA values (FT-IR: R2= 0.954, SEP = 0.14, RPD = 4.48; FT-NIR: R2= 0.948, SEP = 0.14, RPD = 4.38). Although the predictability of the FT-IR method for the PO values was not as satisfactory as that of the FT-NIR method (FT-IR: R2= 0.893, SEP = 6.17, RPD = 2.93; FT-NIR: R2= 0.953, SEP = 4.15, RPD = 4.36), both FT-IR and FT-NIR methods could be used as simple and rapid approaches to determining the quality of deep frying oils. [ABSTRACT FROM AUTHOR]