Traditional Chemometrics and Innovative Machine Learning Techniques as Tools to Assess Food Quality, Safety and Traceability
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Food Process Engineering".
Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 3060
Special Issue Editors
Interests: volatile organic compounds; food aroma; food microbiology; food biotechnology; food chemistry; sensory evaluation; flavour chemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The chemometric analysis in the field of food allows one to process a large number of data and responses, to extract information on the authentication of geographical or varietal origin, food quality, chemical composition, or even to trace the adulteration of commodities with high added value.
In recent years, machine learning techniques have also found a wide range of uses in the food sector, offering valuable support to classical chemometric techniques for data analysis, but also for the assessment of food quality, traceability and safety.
The application of AI has led to the development of techniques that are more reliable, objective, cost-effective, non-destructive and less time-consuming than traditional methods available in the industry.
This Special Issue aims to collect high quality manuscripts related to the implementation of machine learning techniques, coupled with classical chemometric strategies in the food industry, to highlight the potential and applications of these efficient and non-invasive techniques.
Dr. Maria Tufariello
Dr. Lorenzo Palombi
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 papers will be 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. 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 2000 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
- chemometric analysis
- machine learning techniques
- artificial intelligence
- food quality
- safety
- traceability
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