Non-destructive Detective of Glucose Contect in Lingwu Jujube by Vis/NIR Hyperspectral Imaging Technology

CHENG Li-juan; LIU Gui-shan; WAN Guo-ling; HE Jian-guo

doi:10.3788/fgxb20194008.1055

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Non-destructive Detective of Glucose Contect in Lingwu Jujube by Vis/NIR Hyperspectral Imaging Technology

Luminescence Applications and Interdisciplinary Fields | 更新时间：2020-08-12

- Non-destructive Detective of Glucose Contect in Lingwu Jujube by Vis/NIR Hyperspectral Imaging Technology
- Chinese Journal of Luminescence Vol. 40, Issue 8, Pages: 1055-1063(2019)
- 作者机构：
  
  宁夏大学农学院,宁夏银川,750021
- 作者简介：
- 基金信息：
  
  Supported by National Natural Science Foundation of China(31560481,75002108A1651)
- DOI：10.3788/fgxb20194008.1055
  CLC： S123;O657.3
- Received：14 August 2018，
  
  Revised：02 November 2018，
  
  Published Online：08 November 2018，
  
  Published：05 August 2019
- 稿件说明：
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程丽娟, 刘贵珊, 万国玲等. 可见/近红外高光谱成像技术对长枣中葡萄糖含量的无损检测[J]. 发光学报, 2019,40(8): 1055-1063

CHENG Li-juan, LIU Gui-shan, WAN Guo-ling etc. Non-destructive Detective of Glucose Contect in Lingwu Jujube by Vis/NIR Hyperspectral Imaging Technology[J]. Chinese Journal of Luminescence, 2019,40(8): 1055-1063
程丽娟, 刘贵珊, 万国玲等. 可见/近红外高光谱成像技术对长枣中葡萄糖含量的无损检测[J]. 发光学报, 2019,40(8): 1055-1063 DOI： 10.3788/fgxb20194008.1055.

CHENG Li-juan, LIU Gui-shan, WAN Guo-ling etc. Non-destructive Detective of Glucose Contect in Lingwu Jujube by Vis/NIR Hyperspectral Imaging Technology[J]. Chinese Journal of Luminescence, 2019,40(8): 1055-1063 DOI： 10.3788/fgxb20194008.1055.

摘要

利用可见/近红外高光谱成像技术结合化学计量学方法建立长枣中葡萄糖含量的预测模型，为灵武长枣中的葡萄糖含量快速无损检测提供了一种科学方法。采用可见/近红外（400~1 000 nm）高光谱采集灵武长枣的光谱数据，利用HPLC测量长枣中的葡萄糖含量；样本经过剔除异常值、样本集划分后对原始光谱采用6种预处理；对优选出的最佳预处理方法使用7种方法降维处理，建立全波段和特征波长的PLSR、MLR预测模型。结果表明，SG（7）为最佳预处理方法，

=0.826 5，

=0.791 0；利用CARS、IRF、SPA、BiPLS、UVE、IRF+CARS、BiPLS+CARS分别选出18，61，7，51，15，33，27个特征波长；PLSR-IRF+CARS模型最优，

=0.835 3，

=0.832 2。实验结果证明高光谱成像技术对长枣中的葡萄糖含量的快速无损检测是可行的。

Abstract

The Vis/NIR hyperspectral imaging technique combined with chemometrics method was applied to build a glucose contect prediction model

which provided a scientific method for the rapid non-destructive detection of glucose content in Lingwu long jujube. The spectral data were acquired by Vis/NIR hyperspectral imaging(400-1 000 nm). Simultaneously

high-performance liquid chromatography was used to detect the glucose content; after eliminating abnormal sample data and dividing into sample set

the 6 pretreatment methods were used to process original spectrum. Then the characteristic wavelength was selected from the pretreatmented spectral data by 7 methods

and the PLSR and MLR prediction models were established based on full wavelength and feature wavelength

respectively. The results show that the SG(7)method is the optimal pretreatment method; and the number of the characteristic wavelengths by CARS

IRF

SPA

BiPLS

UVE

IRF+CARS and BiPLS+CARS are 18

respectively; the IRF+CARS model was the best among the models developed

and its

=0.835 3

=0.832 2. So it is feasible to predicte glouse content of Lingwu long jujube based on hyperspectral imaging technique.

关键词

Keywords

references

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