摘要
为选择适宜的光谱预处理方法,考察了标准归一化(SNV)、多元散射校正(MSC)、导数计算和连续小波变换(CWT)处理对烟叶样品总糖、总氮、烟碱近红外光谱模型预测结果的影响。结果表明:①SNV和MSC可将不同强度的背景校正,而导数计算和CWT可将光谱的背景扣除;②背景校正和背景扣除均对预测结果具有一定程度的改善作用,但将二者结合改善作用更明显。
In order to select a suitable method for preprocessing,the effects of standard normal variate（SNV）,multiplicative scatter correction（MSC）,derivation calculation（DC） and continuous wavelet transform（CWT） on the prediction results of NIR spectra models for the contents of total sugar,total nitrogen and nicotine in tobacco were investigated.It was found that： 1） SNV and MSC could correct the background at different intensities,while DC and CWT could remove the background from NIR spectra;and 2） the prediction results could be improved to a certain extent by either background correction or background removal,and would be better by combining the two.
出处
《烟草科技》
EI
CAS
北大核心
2010年第1期44-46,59,共4页
Tobacco Science & Technology
关键词
烟叶
近红外光谱
定量分析
背景校正
背景扣除
Tobacco leaf
Near infrared spectroscopy
Background correction
Background removal
