摘要
为了研究烟草在制品化学成分的稳定性,在线采集了烘丝出口叶丝的近红外光谱(NIR),采用连续小波变换方法进行光谱预处理,结合主成分分析(PCA)方法研究了样品常规化学成分与NIR的关系;建立了烟草在制品稳定性的表征模型,并通过调整烘丝工序加工参数对模型进行了验证。结果表明:NIR能够对样品常规化学成分所包含的信息进行表征;当显著性水平α=0.05时,B牌号试验卷烟的表征模型对异常样品的识别率为100%,对正常样品的识别率为98%,A,C,D和E牌号卷烟的模型对正常样品的识别率分别为98.7%,99.3%,100%和98.4%。该NIR模型能够对烟草在制品质量进行有效的实时监测。
In order to study the stability of chemical components in tobacco in processing, the near infrared （NIR）spectra of cut tobacco were online collected at the outlet of HXD drier and then pocessed by continuous wavelet transformation. The relationships between routine chemical components and NIR spectra of samples were studied on the basis of principal component analysis（PCA）. The characterization models of tobacco with regard to the stability in processing were developed, then validated by changing the processing parameters of HXD drying. The results showed that the information of tobacco expressed by its routine chemical components could be characterized by NIR spectra. With a significance level of 0.05,the recognition rates to normal samples and abnormal samples for the characterization model of brand B were 98% and 100%, respectively. The recognition rates to normal samples for the models of brand A, C, D, E were 98.7%, 99.3%, 100%, 98.4%, respectively. The NIR model could effectively and real-timely monitor the quality of tobacco in processing.
出处
《烟草科技》
EI
CAS
北大核心
2012年第7期46-49,共4页
Tobacco Science & Technology
基金
川渝中烟工业有限责任公司项目"运用近红外光谱技术评价在制品化学成分稳定性的应用研究"(川渝烟工技烟[2009]368号)
关键词
近红外光谱
烟草在制品
化学成分
模型
实时
Near infrared spectrometry
Tobacco in processing
Chemical component
Model
Real-time
