Machine Learning from Foods – Applied Food Technology

A special issue of Foods (ISSN 2304-8158).

Deadline for manuscript submissions: closed (10 December 2021)

Special Issue Editors


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Guest Editor
Departamento de Ingeniería Química y de Materiales, Facultad de CC. Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
Interests: computing in mathematics; natural science; engineering and medicine; pattern recognition; artificial intelligence

E-Mail Website
Guest Editor
Scintillon Institute, San Diego, CA, USA
Interests: Machine Learning; Artificial Intelligence; Deep Learning; Chemometric Tools; Biochemistry; Biotechnology; Food Technology; Food Quality and Safety; Disease Diagnosis.

Special Issue Information

Despite the wide variety of foods and their properties, an undeniable truth is that access to safe and healthy food is a crucial aspect for society worldwide. Ensuring food quality and safety must be prioritized and monitored in detail, not only by producers, but also by administrations and governments.

Administrations via regulations attempt to control and guarantee food quality and safety prior to reaching consumers. In some cases, these regulations are based on analytical tools and their derived readings. These resulting data must be complemented with algorithmic tools in order to take full advantage of the analytical equipment. Being able to design and apply powerful algorithms, such as those based on machine learning, will enable employing a wide range of equipment in terms of signals generated and cost. Inexpensive equipment can benefit from a thorough mathematical phase and chemometric design, allowing a wider range of administrations and research teams to act in this context, even with limited budgets.

All of the above has inspired the creation of this Special Issue, as it aims to present combinations in which intelligent mathematical tools work together with a wide assortment of analytical approaches, including cost-effective systems, to reach reliable and fast food analyses. In this topic, applications can cover or monitor any phase of a given food product, including production itself, its distribution chain, or even shelf-life. Furthermore, quality control, compound detection and quantification, either beneficial or due to adulteration, as well as food safety, will be considered as suitable potential applications.

Prof. Dr. Jose Torrecilla
Dr. John C. Cancilla
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 100 words) can be sent to the Editorial Office for announcement on this website.

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 quality • Food production • Food distribution chain • Food safety • Adulteration detection • Machine learning • Chemometric tools

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Published Papers

There is no accepted submissions to this special issue at this moment.
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