2012 · 11 citations · 0 references
Natural SciencesEarth SciencesSoil SciencesRemote SensingSoil ScienceSpectroscopyInfrared Remote SensingInfrared SpectroscopyNear-infrared SpectroscopySoil Nitrogen SensingInfrared Spectroscopic AnalysisNear-infrared SensingNitrogen Content EstimationPlant Nitrogen Status EstimationPredictive Bias AnalysisSoil Nitrogen AssessmentSoil Nitrogen Calibration ModelsSpectral Validation
Moving window partial least square(MWPLS) and Savitzky-Golay(SG) smoothing methods were used to optimize near-infrared(NIR) spectroscopic analysis model of total nitrogen in soil.Thirty-five samples were selected randomly from all 97 soil samples as validation set.The remaining 62 samples were divided into modeling calibration set(37 samples) and modeling prediction set(25 samples) with similarity based on the predictive bias of cross-validation of partial least square(PLSPB) model.The optimal waveband was 1692-2138 nm,order derivative(OD),degree polynomial(DP) and number of smoothing points(NSP) of SG smoothing parameters were 0,6 and 69 respectively,PLS factor was 11,the root mean square error of modeling prediction(M-RMSEP) and the correlation coefficient of modeling prediction(M-RP) were 0.015% and 0.931,respectively,the root mean square error of validating prediction(V-RMSEP) and the correlation coefficient of validating prediction(V-RP) were 0.018% and 0.882,respectively.The results could provide valuable reference for designing specialized NIR instruments.