期刊论文

Research on Optimal Predicting Model for the Detection of Internal Quality by Hyperspectral Technology

中文

农机化研究

1003-188X

2015

7

56-60

10.3969/j.issn.1003-188X.2015.07.013

湖南省科技厅科技计划项目（2014NK3004）；

本校为第一机构

以油茶籽中油酸、亚油酸、棕榈酸为研究对象，寻求一种油茶籽脂肪酸成分含量的最佳预测模型。首先，利用高光谱成像系统以线扫描方式获取其反射光谱图像，选择感兴趣区域（ ROI ）；然后，对原始光谱进行平滑与多元散射校正（ MSC ），通过相关性分析和逐步回归分析，得到能反映油酸、亚油酸、棕榈酸含量变化的最佳优化波段；进而对最优波段采用偏最小二乘回归（ PLS ）方法、主成分回归（ PCR ）方法及径向基神经网络（ RBF ）方法组建预测模型。比较这3种方法的建模效果，经外部验证表明：径向基神经网络建立的预测模型效果最好，其油酸、亚油酸、棕榈酸的交叉验证相关系数 R分别为0．9403、0...

To construct optimal predicting models based on the content of aliphatic acid of camellia seed, the research was concerned with oleic acid, linoleic acid, and palmitic acid.This approach was composed of four major procedures:line-by-line reflection spectrum scanning to select the region of interest ( ROI) by hyperspectral imaging system;smoot-hing the original spectrum and analyzing by multiplicative scatter correction ( MSC ); identifying the sensitive optimized waveband, which can reflect the variation of the content of oleic acid, linoleic acid, palmitic acid by correlation analysis and ste...