Non‐destructive discrimination of homochromatic foreign materials in cut tobacco based on VIS‐NIR hyperspectral imaging

Author:

Liang Jing12,Wang Yueying3,Shi Yu12,Huang Xiaowei12,Li Zhihua12,Zhang Xinai12,Zou Xiaobo12,Shi Jiyong12ORCID

Affiliation:

1. Agricultural Product Processing and Storage Lab, School of Food and Biological Engineering Jiangsu University Zhenjiang China

2. International Joint Research Laboratory of Intelligent Agriculture and Agri‐Products Processing (Jiangsu University) Jiangsu Education Department Zhenjiang China

3. College of Biosystems Engineering and Food Science Zhejiang University Hangzhou China

Abstract

AbstractBACKGROUNDThe presence of foreign materials (FM) not only reduces the commercial value of tobacco and the quality of cigarette products, but also affects the aroma and flavor of cigarettes. Existing tobacco deblending equipment has received little study with respect to homochromatic FM. In the present study, visible‐near infrared (VIS‐NIR) hyperspectral imaging technique combined with chemometrics were used to identify and visualize the homochromatic FM on the surface of thining tobacco. A comparison with conventional vision method was made to analyze the feasibility of the method. The importance of detecting FM in cut tobacco was further demonstrated by first studying the volatile organic compounds produced in cigarette mixed FM smoke and their effects on human health before conducting hyperspectral experiments.RESULTSThe results indicated that solid‐phase microextraction and gas chromatography mass spectrometry could detect volatile organic compounds in mainstream cigarette smoke that were not cigarette components and affected consumer health. Then, spectral features of the samples were extracted from hyperspectral images for building identification models to distinguish FM from cut tobacco. The visual RGB values of cut tobacco and FM were also used for the analysis of the recognition models. The results showed that the accuracy, precision and recall reached 100.00% using the back propagation artificial neural network classification model based on the principal component analysis raw wavelengths. The visualization results based on the optimal model produced clearer localization than conventional computer vision method.CONCLUSIONThe present study revealed that the VIS‐NIR hyperspectral imaging technology had advantage in the detection and localization of FM on the surface of thinning tobacco, which provided a foundation for improving the quality and safety of cut tobacco production. © 2023 Society of Chemical Industry.

Funder

Natural Science Foundation of Jiangsu Province

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Wiley

Subject

Nutrition and Dietetics,Agronomy and Crop Science,Food Science,Biotechnology

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Applications of hyperspectral imaging technology in the food industry;Nature Reviews Electrical Engineering;2024-03-26

2. Research on Tobacco Foreign Object Detection Based on Deep Learning of Texture Features;2023 4th International Conference on Information Science and Education (ICISE-IE);2023-12-15

3. Tobacco Impurities Detection with Deep Image Segmentation Method on Hyperspectral Imaging;2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC);2023-11-14

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