In this paper, the contents of ethyl acetate and ethyl lactate in base liquor were quantitatively analyzed by near infrared spectroscopy. The characteristic wave bands were selected using interval partial least squares (iPLS), synergy interval partial least squares (SiPLS), genetic algorithm partial least squares (GA-PLS), competitive adaptive reweighted sampling (CARS), and partial least squares (PLS) to establish a model for quantitative analysis of ethyl acetate and ethyl lactate. The results showed that the above four methods had certain optimization effect on the model. The optimization effect of genetic algorithm partial least squares (GA-PLS) and synergy interval partial least squares (SiPLS) were the most obvious. The R² of ethyl acetate and ethyl lactate reached 0.989 7 and 0.991 0, and the Root Mean Squared Error of Prediction (RMSEP) respectively were 0.085 4 and 0.143 4, and the Ratio of performance to standard deviate (RPD) respectively were 8.5 and 8.6, which indicated that the stability and accuracy of the model were improved. The results showed that the near-infrared spectroscopy has a scientific significance for the detection of ethyl acetate and ethyl lactate in the base liquor.