The nondestructive and rapid acquisition of rice field phenotyping information is very important for the precision management of rice growth process.In this paper,the phenotyping information(LAI,leaf chlorophyll content(Cab),canopy water content(Cw),dry matter content(Cdm))of rice inversion based on hyperspectral remote sensing technology of unmanned aerial vehicle(UAV).Firstly,the improved Sobol global sensitivity analysis(GSA)method is used to analyze the input parameters of the PROSAIL model in t he spectral band range of 400-1100nm,which is obtained by hyperspectral remote sensing of UAV.The results show that Cab mainly affects the band of 400-780 nm,and the Cdm mainly affects 760 nm to 1000 nm band.The Cw mainly affects the band of 900 to 1100 nm,while LAI affects the whole band.The canopy of rice hyperspectral data of 400-1100nm were acquired by using the M600 UAV remote sensing platform,and the radiance calibration was converted to the canopy emission rate.In combination with PROSAIL model,PSO algorithm was used to retrieve rice phenotyping information by constructing the cost function.The results showed that :(1)Cab retrieval accuracy of R2=0.833,RMSE=9.69%,LAI inversion accuracy of R2=0.816,RMSE=10.12%and inversion accuracy of Cdm was R2=0.793,RMSE=10.84%,Cw inversion accuracy of R2=0.665,RMSE=13.25%.As the hyperspectral band in this study used in the 1000nm or so larger noise,Cw inversion accuracy was not particularly high.(2)Because the same band will be affected by multiple parameters at the same time,there will still be the problem of inversion by this method in inversion of phenotyping information.(3)This study adopted rice phenotyping information inversion method to rice hyperspectral information acquisition field of UAV based on the phenotypic information retrieval accuracy by field spectral radiometric accuracy of great influence.In this study,the UAV remote sensing and PROSAIL model were combined to invert the phenotyping information of rice field,which was of good mechanism,high universality and easy implementation.This study can provide a theoretical basis for non-destructive and rapid inversion of rice biochemical parameters using UAV hyperspectral remote sensing.