| Title: | Non-destructive discrimination of homochromatic foreign materials in cut tobacco based on VIS-NIR hyperspectral imaging |
| Author(s): | Liang J; Wang Y; Shi Y; Huang X; Li Z; Zhang X; Zou X; Shi J; |
| Address: | "Agricultural Product Processing and Storage Lab, School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China. International Joint Research Laboratory of Intelligent Agriculture and Agri-Products Processing (Jiangsu University), Jiangsu Education Department, Zhenjiang, China. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China" |
| ISSN/ISBN: | 1097-0010 (Electronic) 0022-5142 (Linking) |
| Abstract: | "BACKGROUND: The 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. RESULTS: The 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. CONCLUSION: The 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. (c) 2023 Society of Chemical Industry" |
| Keywords: | "Humans *Tobacco/chemistry *Volatile Organic Compounds/analysis Hyperspectral Imaging Spectroscopy, Near-Infrared Neural Networks, Computer cut tobacco homochromatic foreign materials hyperspectral imaging technology pattern recognition;" |
| Notes: | "MedlineLiang, Jing Wang, Yueying Shi, Yu Huang, Xiaowei Li, Zhihua Zhang, Xinai Zou, Xiaobo Shi, Jiyong eng 202074/Jiangsu Specially-Appointed Professor/ BK20200103/Natural Science Foundation of Jiangsu Province/ BK20220111/Natural Science Foundation of Jiangsu Province/ BK20220058/Natural Science Foundation of Jiangsu Province/ Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)/ England 2023/02/26 J Sci Food Agric. 2023 Jul; 103(9):4545-4552. doi: 10.1002/jsfa.12528. Epub 2023 Mar 21" |
