Models of Estimating Sugar Beet Nitrogen Using Hyperspectral
This paper analyzes the beet canopy spectra under four pretreatment were used partial least squares regression ( PLSR) and principal component regression ( PCR) to establish beet nitrogen content estimation model , compare differ-ent methods of pretreatment and different regression estimation accuracy impact on PLSR , the first order derivative of the spectral data processing model established best accuracy ( RMSE=2.34g/kg, RE=19.6%), smoothing, estimation model followed by MSC and SNV established;for PCR toHe said precision spectral data smoothing model established best (RMSE=2.34g/kg,RE=19.4%).Overall, there are some different pre-treatment model to estimate the accuracy of differences , but the two regression PLSR and PCR methods to estimate the nitrogen content of beet little effect model .
国家科技期刊平台
NSTL
万方数据
维普
