Abstract: The NIRs combined with principal component analysis(PCA)were firstly employed to conduct the qualitative analysis on three different kinds of coconuts,three brands of coconut drinks,and three brands of coconut powders in this work. The results revealed that the different coconut products could be clearly identified,and the accuracy rates for all of the above qualitative analyses were up to 100%. Moreover,the NIR spectra combined with partial least squares(PLS)was used to quantitative analysis of the content of raw juice in coconut beverage. To ensure the robustness and accuracy of the used model and eliminate the noise and baseline drift,six kinds of pretreatment methods were employed to optimize the NIR spectra. The results showed that the model after centralized preprocessing exhibited the best performance,in which the determination coefficient of prediction(R_p²),the root mean square prediction error(RMSEP),determination coefficient of calibration(R_c²),and root mean squared error of calibration(RMSEC)were 0.9942,0.0435,0.9932,and 0.0519,respectively. This study showed that the NIR spectroscopy could provide a new idea for the rapid and nondestructive detection of the qualities of commercially available coconut products.