摘要
Abstract
[ Objective] To obtain the testing model of starch content of near infrared spectrum in corn with high accuracy and strong robustness. [Method] The corn near Infrared spectra whose wavelength range was 1 300 -2 298 nm was preprocessed by first derivative and Savitz-ky-Golay smoothing. The preprocessed spectra was selected for calibration set respectively adopting RS (random sampling), KS(Kennard Stone) , Duplex and SPXY(sample set partitioning based on joint x-y distance) method. After the spectra being selected for calibration set, PLS(Partial Least Squares) ,iPLS (interval PLS) and siPLS (synergy interval PLS) were respectively used to set up the calibration model base on each calibration set of RS,KS, Duplex and SPXY method. [ Result] The NIR calibration model of corn starch content established by SPXY -siPLS method was optimal,r of calibration set was 0. 991 1 ,RMSECV was 0. 107 3,r of prediction set was 0. 994 4,RMSEP was 0. 081 4. [Conclusion] The NIR calibration model of corn starch content established by SPXY-siPLS method could not only decrease the variable numbers of modeling and shorten the operation time, but also improve the prediction ability and precision.关键词
近红外光谱/样本挑选/偏最小二乘/区间偏最小二乘/联合区间偏最小二乘Key words
Near infrared spectra/ Calibration set selecting/ Partial Least Squares/ Interval PLS/ Synergy interval PLS分类
轻工纺织
