A Path-Length Correction Method on Biochemical Parameter Nondestructive Measuring of Folium
ZHANG Qian-xuan, ZHANG Guang-jun*, LI Qing-bo
Key Laboratory of Precision Opto-Mechatronics Technology, Ministry of Education, School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
Abstract：Vis/NIR spectroscopy technology is capable of analyzing the content of biochemical parameter in folium rapidly and nondestructively. In the process of spectrum analysis, the variations in path-length between different samples exist, with the random light scattering and leaf thickness perturbations, which influence the precision of quantitative analysis model. In order to resolve this problem, an improved path-length correction method based on Extended Multiplicative Scattering Correction is presented. In this paper, firstly the theory of EMSC algorithm is deduced. EMSC method incorporates both chemical terms and wavelength functions to help realize the efficient separation of path-length and interest concentration. Secondly two experiments were implemented to demonstrate the validity of the method. In Experiment 1, sixteen samples of different thickness but almost the same chlorophyll content were selected, and how the path-length affects the spectrum was compared, after EMSC preprocessing, the variable coefficient of spectrum could approach the repeatability error of spectrometer. In Experiment 2, thirty-two samples of different thickness and chlorophyll content were selected. PLS model established using cross validation was employed to evaluate the efficiency of the presented algorithm. Before the preprocessing, the root mean squared error of prediction is 3.9 SPAD with 5 principal components. After preprocessing, the predicted root mean squared error is 2.2 SPAD with 12 principal components. The results indicate that the improved EMSC preprocessing method could exactly eliminate the spectrum difference caused by the path-length variations between different foliums, enhance the sensitivity of concentration and spectral data, and increase the precision of calibrated model.
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