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Novel Techniques for the Detection of Toxins and Harmful Substances...
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Novel Techniques for the Detection of Toxins and Harmful Substances in Food

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Quality and Safety".

Deadline for manuscript submissions: closed (20 March 2026) | Viewed by 762

Special Issue Editors

Dr. Bruna Carbas

E-Mail Website
Guest Editor
Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
Interests: food safety; mycotoxins; analytical methods; FTIR; cereals and legumes
Special Issues, Collections and Topics in MDPI journals
Dr. Pedro N. Sousa Sampaio

E-Mail Website
Guest Editor
1. Computação e Cognição Centrada nas Pessoas, Lusófona University, Campo Grande, 376, 1749-019 Lisboa, Portugal
2. GREEN-IT Bioresources for Sustainability, ITQB NOVA, Av. da República, 2780-157 Oeiras, Portugal
Interests: FTIR; chemometrics; machine learning; bioactive compounds; spectroscopy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Natural toxins and harmful substances in food represent serious risks for human health, but they can be managed through detection, monitoring, and preventive measures. For assurance of food safety and protection of public health, it is crucial to prioritize research on advanced analytical techniques for detection and quantification, the adoption of good agricultural practices, and robust regulatory frameworks. Advances in analytical techniques, infrared spectroscopy, and artificial intelligence are improving our ability to detect and control food contaminants effectively.

Research and review articles exploring all aspects of “Novel Techniques for the Detection of Toxins and Harmful Substances in Food” are requested for this Special Issue of Foods. This Special Issue will focus on the development of predictive models for natural toxin occurrence and contaminants in food matrices using spectroscopic methods and machine learning technologies, including the influence of agricultural practices, food processing, and storage conditions for contaminant control, highlighting the enforcement of novel techniques for food safety measures and contaminant monitoring in food safety regulatory standards.

Dr. Bruna Carbas
Dr. Pedro N. Sousa Sampaio
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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. Foods is an international peer-reviewed open access semimonthly 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 2900 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 contaminants
  • natural toxins
  • cereals
  • mycotoxins
  • food safety
  • analytical methods
  • artificial intelligence
  • near-infrared spectroscopy
  • chemometrics
  • algorithms

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Published Papers (1 paper)

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Research

13 pages, 519 KB  
Article
Study on the Effect of Heavy Metal Contamination of Milk on the Coagulation Process
by Maria Natalia Chira and Sonia Amariei
Foods 2026, 15(9), 1498; https://doi.org/10.3390/foods15091498 - 25 Apr 2026
Cited by 1 | Viewed by 269
Abstract
This study investigated how Pb, Cd, and Cu are distributed between curd and whey during milk coagulation in milk from different animal species, and how the level of metal addition and the coagulation method influence metal retention. Raw milk from buffalo, cow, donkey, [...] Read more.
This study investigated how Pb, Cd, and Cu are distributed between curd and whey during milk coagulation in milk from different animal species, and how the level of metal addition and the coagulation method influence metal retention. Raw milk from buffalo, cow, donkey, goat, and sheep was supplemented with Pb, Cd, and Cu under controlled laboratory conditions at two levels corresponding to the regulatory maximum level (ML) and ten times this level (10 × ML). All three metals were added simultaneously to the same milk aliquot, and coagulation was induced either enzymatically or by acidification at pH 4.6. Metal concentrations in curd and whey were determined by atomic absorption spectrophotometry. In all milk types, Pb, Cd, and Cu were retained mainly in the curd fraction. At ML, curd retention generally ranged from about 77% to 97%, whereas at 10 × ML, retention decreased and transfer to whey increased. Donkey milk consistently showed lower metal retention in curd than ruminant milk. Statistical analysis of curd retention showed that metal type, milk species, the level of metal addition, and their interactions significantly influenced metal retention, indicating that the effect of coagulation method depended on the experimental conditions rather than being uniform across all cases. Overall, the results show that milk coagulation favours the association of Pb, Cd, and Cu with the curd fraction, highlighting the importance of the milk protein phase in determining metal distribution during dairy processing. These findings improve our understanding of heavy-metal behaviour during milk processing and help clarify their potential transfer into curd-based dairy products. Full article
(This article belongs to the Special Issue Novel Techniques for the Detection of Toxins and Harmful Substances in Food)
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