食品科学2017，Vol.38Issue(8)：191-197,7.DOI:10.7506/spkx1002-6630-201708030
基于不同波段的枸杞多糖及总糖高光谱成像检测
Detection of Polysaccharides and Total Sugar in Chinese Wolfberry Based on Hyperspectral Imaging in Different Wavebands
摘要
Abstract
Hyperspectral imaging technology was used to detect the contents of polysaccharides and total sugar as two important quality indicators for rapid evaluation of Chinese wolfberry.For this purpose,the optimal spectral waveband was explored.Firstly,the original spectra were preprocessed using three commonly used methods,namely multiplicative scatter correction,Savitzky-Golay smoothing and standard normal variate,and comparison of the results obtained showed that multiplicative scatter correction was selected to eliminate the scattering effect.Then the average spectral reflectance value was extracted for use as characteristic parameters from hyperspectral images in the effective wavebands,the visible wavebands,the near-infrared wavebands and the full wavebands based on the correlation coefficients and the spectral characteristics in different waveband ranges.Finally,BP neural network models were established based on different characteristic parameters to predict the contents of polysaccharides and total sugar in Chinese wolfberry.The results showed that the prediction model based on the full bands was the best one.The correct prediction rate of the model for polysaccharide content was 97.59％ with a correlation coefficient of 0.997 4 and a root mean square error of 0.077 7.The correct prediction rate of the model for total sugar content was 100％ with a correlation coefficient of 0.996 8 and a root mean square error of 0.250 6.Therefore,it is feasible to detect the contents of polysaccharide and total sugar in Chinese wolfberry by hyperspectral imaging technology.关键词
高光谱图像/BP神经网络/枸杞/多糖/总糖Key words
hyperspectral imaging/BP neural network/Chinese wolfberry/polysaccharide/sugar分类
数理科学引用本文复制引用
于慧春,王润博,殷勇,刘云宏..基于不同波段的枸杞多糖及总糖高光谱成像检测[J].食品科学,2017,38(8):191-197,7.基金项目
河南省科技创新杰出青年资助项目(624420017) （624420017）
河南省科技攻关项目(172102210256 （）
172102310617) （）
