Packaged food detection method based on the generalized Gaussian model for line-scan Raman scattering images

Authors: LIU, ZHENFANG - Jiangnan University; HUANG, MIN - Jiangnan University; ZHU, QIBING - Jiangnan University; Qin, Jianwei - Tony Qin; Kim, Moon

Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/12/2019
Publication Date: 4/14/2019
Citation: Liu, Z., Huang, M., Zhu, Q., Qin, J., Kim, M.S. 2019. Packaged food detection method based on the generalized Gaussian model for line-scan Raman scattering images. Journal of Food Engineering. 258:9-17.
DOI: https://doi.org/10.1016/j.jfoodeng.2019.04.005

Interpretive Summary: Safety and quality inspection of packaged dry food powders is important for both food industries and regulatory agencies. Using existing methods to authenticate ingredients or detect contaminants, it is difficult to accurately evaluate the packaged food material without destroying the packaging. In this study, a nondestructive detection method for evaluating dry powders packaged in plastic films was developed based on a line-scan Raman scattering spectroscopy technique. Pure samples of melamine, sodium nitrite, maleic anhydride, and white granulated sugar were covered by food-grade plastic sheets of polyethylene, polypropylene and high-density polyethylene. Raman scattering images of the plastic-covered samples were acquired. Analysis and modeling found that the Raman signals of the food and the plastic films could be separately identified from the spectral image data. The method can be used for nondestructive safety and quality analysis of packaged dry foods through plastic packaging materials. The technique would benefit food processors and regulatory agencies interested in enforcing safety and quality standards for packaged foods.

Technical Abstract: Packaged food safety has gained increasing attention worldwide. Existing analytical methods pose difficulties in accurately measuring food quality without 32 destroying the packaging. In this study, a nondestructive detection method for packaged 33 food was proposed based on the generalized Gaussian model for Raman scattering images. The Raman peaks of the scattering image were extracted, and the attenuation information of the peaks far from the laser point were imported into the established generalized Gaussian model. Food-grade polyethylene sheets with thicknesses of 1, 2, and 3 mm were used as packaging materials for comparison experiments. The proposed model can accurately separate the Raman peak of the subsurface material when 1 mm-thick polyethylene was used as the packaging. Food-grade plastic sheets of polyethylene, polypropylene and high-density polyethylene were covered with pure substances such as melamine, sodium nitrite, and maleic anhydride. This model was considered suitable for most food-grade plastic packaging, and the subsurface materials did not influence the separation effect. Finally, evaluation of premium white granulated sugar demonstrated that the model effectively separated the Raman peak produced by packaged food and detected the packaged food without conferring damage.