The Contrast of Selecting Wavelength Capability of SPA and GA for Soil EC Detecting Model

International Conference on Manufacturing Technology, Materials and Chemical Engineering

机械制造;材料科学;化学工业

Bai, Tiecheng^1,2 ; Chen, Youqi^3 ; Benoît, Mercatoris^1

Gembloux Agro-Bio Tech, University of Liège, Gembloux

25030, Belgium^1

College of Information Engineering, Tarim University, Alaer

843300, China^2

Institute of Agricultural Resources and Regional Planning, CAAS, Beijing

100081, China^3

关键词: Detecting methods;    Determination coefficients;    Electrical conductivity;    Prediction model;    Root mean square errors;    Sensitive wavelengths;    Spectral reflectances;    Successive projections algorithms (SPA);   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/392/4/042037/pdf
DOI  :  10.1088/1757-899X/392/4/042037

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

The electrical conductivity(EC) of the soil was an important index to evaluate soil salinity. Spectral detecting method was an effective method. The objectives of this study were to compare choosing ability of the successive projections algorithm (SPA) and Genetic Algorithm (GA) methods for sensitive wavelengths and establish hyper spectral inversion model. Firstly, 140 soil samples were taken back to the laboratory and measured the EC (soil: water=1:5, EC1:5) and spectral reflectance(900-1700nm). Secondly, the SPA and GA were used to select sensitive wavelengths for reducing the complexity of the model, then PLSR method was used to establish detecting model. Finally, the determination coefficient (R2), root-mean-square error (RMSE), ratio prediction to deviation (RPD) and the number of wavelengths selected were used to evaluate different kinds of methods. The experimental results showed the prediction models after using SPA were better than GA method because SPA had lesser band number and time, higher R2 and RPD, smaller RMSE(band number=5, R2=0.9707, RPD=8.4445 and RMSE=0.31178). Thus, it was validated the SPA method can be used to select sensitive wavelengths to improve the model accuracy of soil EC.