Detection and Evaluation Process of Toxic and Harmful Substances in Foods

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Food Process Engineering".

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 1818

Special Issue Editors


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Guest Editor
Department of Food Science, National Taiwan Ocean University, Keelung City 20224, Taiwan
Interests: food safety; human health risk assessment; total diet study; environmental modeling and simulation

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Guest Editor
Department of Food Science and Nutrition, Meiho University, Pingtung County 91202, Taiwan
Interests: food analysis; chemometrics; chemical sensor; risk assessment

Special Issue Information

Dear Colleagues,

Food safety, nutrition and food security are closely linked. Unsafe food containing harmful bacteria, viruses, parasites, natural toxin, process induced contaminants or chemicals creates a vicious cycle of disease and malnutrition, particularly affecting infants, young children, the elderly and the sick. The detection and evaluation of toxic or harmful substances in food is even more important. Toxic or hazardous substances in food include biological, physical, and chemical substances. Biological hazardous substances in food include food microorganisms, mycotoxins, marine biotoxins, plant toxins, etc. Physical hazardous substances in food include food radiation, plastic particles, etc. Chemical hazardous substances in food include food additives, residues (e.g., pesticide residues and veterinary drugs), environmental contaminants (e.g., metals, persistent organic pollutants), food process contaminants (e.g., PAHs, acrylamide, 3-MPCD), and contaminants derived from food packaging, etc. Topics include, but are not limited to:

  • Hazard analysis;
  • Hazard analysis critical control point (HACCP);
  • Microbial food safety and antimicrobial systems;
  • Mycotoxins, marine biotoxins, plant toxins;
  • Trace elements;
  • Environmental contaminants;
  • Food process contaminants;
  • Adulteration, authenticity and allergenicity of foods;
  • Animal feed where residues and contaminants can give rise to food safety concerns;
  • Good manufacturing practices;
  • Rapid methods of analysis and detection, including sensor technology.

Prof. Dr. Min-Pei Ling
Dr. Tai-Sheng Yeh
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • food safety
  • hazardous substances
  • hazard analysis
  • HACCP
  • good manufacturing practices

Published Papers (1 paper)

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Research

13 pages, 3216 KiB  
Article
Portable NIR Spectroscopic Application for Coffee Integrity and Detection of Adulteration with Coffee Husk
by Vida Gyimah Boadu, Ernest Teye, Charles L. Y. Amuah, Francis Padi Lamptey and Livingstone Kobina Sam-Amoah
Processes 2023, 11(4), 1140; https://doi.org/10.3390/pr11041140 - 07 Apr 2023
Cited by 2 | Viewed by 1389
Abstract
Reliable and user-friendly discrimination of coffee bean integrity and quantification of adulteration in the coffee bean processing value chain would be vital for ensuring consumer trust in quality control and traceability management. In this research, a portable short-wave NIR spectroscopy coupled with chemometric [...] Read more.
Reliable and user-friendly discrimination of coffee bean integrity and quantification of adulteration in the coffee bean processing value chain would be vital for ensuring consumer trust in quality control and traceability management. In this research, a portable short-wave NIR spectroscopy coupled with chemometric data analysis was employed under different pre-treatments to develop a rapid detection technique. Different pre-processing treatments (multiplicative scatter correction; MSC, standard normal variant; SNV, first derivative; FD) together with multivariate techniques; support vector machine (SVM), linear discriminant analysis (LDA), neural network (NN), and random forest (RF) were comparatively assessed using accuracy and correlation coefficient (R) for discrimination and quantification. The results showed that the FD-LDA model had 97.78% and 100 % in both the calibration set and prediction set. In comparison, the SPA-PLS model had R = 0.9711 and 0.9897 in both the calibration set and prediction set. The outcome of this study showed portable short-wave NIR spectroscopic techniques could be used for examining the integrity of coffee. Full article
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