Determination of carbaryl in rice by using Fourier transform far-infrared (FT- Far-IR) and terahertz time-domain spectroscopy (THz-TDS) combined with chemometrics was studied and the spectral characteristics of carbaryl in terahertz region was investigated. Samples were prepared by mixing carbaryl at different amounts with rice powder, and then a 13 mm diameter, and about 1 mm thick pellet with polyethylene (PE) as matrix was compressed under the pressure of 5～7 tons. Terahertz time domain spectra of the pellets were measured at 0.5～1.5 THz, and the absorption spectra at 1.8～6.3 THz were acquired with Fourier transform far-IR spectroscopy. The method of sample preparation is so simple that it does not need separation and enrichment. The absorption peaks in the frequency range of 1.8～6.3 THz have been found at 3.2 and 5.2 THz by Far-IR. There are several weak absorption peaks in the range of 0.5～1.5 THz by THz-TDS. These two kinds of characteristic absorption spectra were randomly divided into calibration set and prediction set by leave-N-out cross-validation, respectively. Finally, the partial least squares regression (PLSR) method was used to establish two quantitative analysis models. The root mean square error (RMSECV), the root mean square errors of prediction (RMSEP) and the correlation coefficient of the prediction are used as a basis for the model of performance evaluation. For the Rv, a higher value is better; for the RMSEC and RMSEP, lower is better. The obtained results demonstrated that the predictive accuracy of the two models with PLSR method were satisfactory. For the FT-Far-IR model, the correlation between actual and predicted values of prediction samples (Rv) was 0.99. The root mean square error of prediction set (RMSEP) was 0.008 6, and for calibration set (RMSECV) was 0.007 7. For the THz-TDS model, Rv was 0.98, RMSEP was 0.004 4, and RMSECV was 0.002 5. Results proved that the technology of FT-Far-IR and THz-TDS can be a feasible tool for quantitative determination of carbaryl in rice. This paper provides a new method for the quantitative determination pesticide in other grain samples.