摘要
该文研究了基于可见-近红外光谱技术的螺旋藻粉类别无损检测方法。采用簇类独立软模式法(SIMCA)建立可见-近红外光谱模型。全波段光谱所建立的模型得到了93.33%的预测集正确率。文章提出了基于间隔偏最小二乘法(iPLS)和连续投影算法(SPA)的组合光谱变量选择方法进行有效波长的选择。该方法从全波段675个变量中选择了5个最优的有效波段,并且得到了96.67%的预测集正确率。和基于全波段光谱、可见光波段光谱和近红外波段光谱进行SPA运算相比,基于iPLS的SPA运算可以有效减少计算时间。研究表明可见-近红外光谱可以用于对螺旋藻粉类别进行无损检测,同时iPLS-SPA是一个有效的光谱变量选择方法。
The feasibility of using visible and near infrared(Vis-NIR)spectroscopy was evaluated for nondestructivetesting of Spirulina powders.Soft independent modeling of class analogy(SIMCA)was used to establish Vis-NIR spectral calibration model.A correct answer rate(CAR)of 93.33%for the discrimination of three varieties was obtained on full-spectrum.A hybrid variable selection algorithm based on interval partial least squares(iPLS)and successive projections algorithm(SPA)was proposed for the effective spectral variable selection.Five optimal effective variables were selected by that hybrid algorithm from 675 variables of full-spectrum.The CAR of 96.67%for the prediction set was obtained.Compared with the SPA based on the full-spectrum,visible spectra or NIR spectra,SPA based on could reduce the calculation time.The results show that it is possible for the nondestructive testing of Spirulina powders using Vis-NIR spectroscopy,and iPLS-SPA is an effective spectral variable selection algorithm.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2009年第S2期330-334,共5页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家支撑计划(2006BAD10A09
2006BAD10A0711
2006BAD10A0403)
863中国高技术研究发展计划(2007AA10Z210)
国家自然科学基金(30671213
30771669)
关键词
近红外光谱
光谱分析
判别分析
无损检测
螺旋藻粉
near infrared spectroscopy,spectroscopic analysis,discriminant analysis,nondestructive testing,Spirulina powders
