Model Update of Total Sugar Content in Tobacco Leaves of Different Years by Near-infrared Spectroscopy Combined with Parameter-free Calibration Enhancement

GENG Ying-rui; SHEN Huan-chao; NI Hong-fei; WANG Hui; WU Ji-zhong; ZHANG Li-li; LI Yong-sheng; HE Wen-miao; CHEN Yong; LIU Xue-song

doi:10.19969/j.fxcsxb.21111803

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Model Update of Total Sugar Content in Tobacco Leaves of Different Years by Near-infrared Spectroscopy Combined with Parameter-free Calibration Enhancement

Experimental Techniques and Methods | 更新时间：2022-07-15

- Model Update of Total Sugar Content in Tobacco Leaves of Different Years by Near-infrared Spectroscopy Combined with Parameter-free Calibration Enhancement
- Journal of Instrumental Analysis Vol. 41, Issue 7, Pages: 1066-1071(2022)
- 作者机构：
  
  1.浙江大学药学院，浙江杭州 310058
  2.浙江大学智能创新药物研究院，浙江杭州 310018
  3.浙江中烟工业有限责任公司技术中心，浙江杭州 310008
- 作者简介：
- 基金信息：
- DOI：10.19969/j.fxcsxb.21111803
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耿莹蕊,沈欢超,倪鸿飞等.近红外光谱结合无参数校正增强实现不同年份烟叶总糖含量模型更新[J].分析测试学报,2022,41(07):1066-1071.

GENG Ying-rui,SHEN Huan-chao,NI Hong-fei,et al.Model Update of Total Sugar Content in Tobacco Leaves of Different Years by Near-infrared Spectroscopy Combined with Parameter-free Calibration Enhancement[J].Journal of Instrumental Analysis,2022,41(07):1066-1071.
耿莹蕊,沈欢超,倪鸿飞等.近红外光谱结合无参数校正增强实现不同年份烟叶总糖含量模型更新[J].分析测试学报,2022,41(07):1066-1071. DOI： 10.19969/j.fxcsxb.21111803.

GENG Ying-rui,SHEN Huan-chao,NI Hong-fei,et al.Model Update of Total Sugar Content in Tobacco Leaves of Different Years by Near-infrared Spectroscopy Combined with Parameter-free Calibration Enhancement[J].Journal of Instrumental Analysis,2022,41(07):1066-1071. DOI： 10.19969/j.fxcsxb.21111803.

摘要

近红外光谱技术因快速、无损等特点，已广泛应用于烟草行业质量快速分析。然而，由于采收时间、环境差异等因素的影响，建立的近红外定量模型在新批次样本中的预测性能通常变差，因此必须对原有模型进行维护和更新。该研究采用半监督无参数校正增强（SS－PFCE）方法，通过约束优化，对主模型的回归系数进行修正。首先建立了2016年烟叶样本总糖含量的原始定量模型，其预测相关系数（,R,p）为0.997 8、预测均方根误差（RMSEP）为0.310 8。采用SS－PFCE方法对模型更新后，分别预测2017年、2018年和2020年样本的总糖含量，3个测试集的,R,p值比未更新模型提高了0.13%、1.32%和4.29%，RMSEP分别下降了15.26%、58.69%和36.53%。与重新建立的定量分析模型相比，更新后的模型具有更优的预测性能，同时大大降低了建模成本。研究表明，SS－PFCE方法可高效地实现不同年份烟叶样本的模型维护，在实际生产中具有重要的应用价值。

Abstract

The near infrared spectroscopy technology has been widely applied to the quantitative analysis in tobacco industry because of its advantages of rapidness and non-destructiveness．However，the accuracy and robustness of the original model may deteriorate when predicting samples with new variations．When samples are obtained from different harvest years and different environmental conditions，new variations will be introduced．Therefore，there is a need to maintain the predictive performance of the original model when it works on a new batch．In this study，a method called semi-supervised parameter-free calibration enhancement（SS－PFCE） was used to update the original model．The regression coefficient of original model was corrected by constrained optimization．The original model for total sugar determination was firstly developed with the tobacco samples of 2016，which showed a predicted correlation coefficient（,R,p） of 0.997 8 and a root mean square error of prediction（RMSEP） of 0.310 8．After updating the model by the SS－PFCE method，the total sugar contents in the samples of 2017，2018 and 2020 years were predicted，respectively．The ,R,p values of the three test sets were improved by 0.13%，1.32% and 4.29%，and the RMSEP were decreased by 15.26%，58.69% and 36.53%，respectively，compared with the non-updated model．Furthermore，the updated model by the SS－PFCE approach offered a better predictive performance than re-modeling method，while significantly reduced modeling costs．The results of this study showed that the SS－PFCE method could maintain the prediction accuracy for tobacco samples of different years efficiently，and it is of great practical application value in industrial production．

关键词

近红外光谱技术模型更新烟叶半监督无参数校正增强（SS－PFCE）

Keywords

near infrared spectroscopymodel updatetobaccosemi-supervised parameter-free calibration enhancement（SS－PFCE）

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