Application of Interval Random Frog Combined with Sucessive Projections Algorithm to Detecting Nitrogen Content in Rubber Tree Leaves
Journal Title: 河南科技大学学报（自然科学版） - Year 2019, Vol 40, Issue 5
Abstract
The non-destructive detection method of nitrogen content in rubber tree leaves based on visible/near infrared spectroscopy was studied.A total of 176 rubber tree leaf samples were collected, and the visible/near infrared data from 350 ～ 2 500 nm was used as experimental data.Firstly, a novel interval random frog (iRF) algorithm was used to select the wavelength interval combination with smallest root mean square error of crossvalidation (RMSECV) . Secondly, the successive projections algorithm (SPA) was used to further select the characteristic wavelength. Thirdly, the selected characteristic wavelength was taken as the input variable to establish a partial least squares (PLS) model.The results show that the wavelength selection is carried out by two-step strategy.The 714 variables from full-spectrum 2 151 are selected by rough selection of iRF algorithm.Then the 20 optimal variables further was selected from the 714 variables refined selection by SPA algorithm, which reduces the information redundancy, and significantly reduces the number of variables of 99. 07%. The root mean square error of calibration (RMSEC) , correlation coefficient of correlation (Rc) , root mean square error of prediction (RMSEP) and correlation coefficient of prediction (Rp) are respectively 0.091 3%, 0.956 5, 0.123 8%, and 0.901 8 which have lower root mean square errors and higher correlation coefficients than PLS, iPLS, iRF, and SPA. Therefore, iRF-SPA can be used as the strategy for wavelength selection to detect the nitrogen content of rubber tree leaves.
Authors and Affiliations
Wei CHEN, Chuang LI, Rongnian TANG
Keywords
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- EP ID EP594626
- DOI 10.15926/j.cnki.issn1672-6871.2019.05.009
- Views 84
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