Applications of Spectroscopy Combined with Machine Learning in Food Quality and Safety: Second Edition
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 368
Special Issue Editors
Interests: food safety; food quality; food authenticity; hyperspectral imaging; NIR; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; hyperspectral imaging; plant phenotyping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The first edition (https://www.mdpi.com/journal/foods/special_issues/1O3R8F3GGG) of this Special Issue was incredibly successful. We would like to express our gratitude to everyone involved for their participation and acknowledge the support of a number of high-profile scientists. The use of spectroscopy combined with machine learning in food quality and safety continues to represent a pivotal issue today, and it is for this reason that we believe that it is time for a second edition to be launched, which will hopefully prove to be as successful as the first.
Food quality and safety are attracted increasing attention due to improvements in living standards and the emergence of negative food incidents. There is increasing awareness of the utilization of reliable detection technologies to achieve food authentication and traceability. Spectroscopy can reveal the internal chemical properties of food; numerous techniques, including infrared spectroscopy, hyperspectral imaging, terahertz spectroscopy, and Raman spectroscopy, are currently being increasingly implemented to authenticate and trace a wide range of foods.
Spectroscopy combined with machine learning has been widely proven to represent an effective food analysis technology, including traditional algorithms (linear regression, support vector machine, logistic regression, random forest, and back propagation neural networks) and deep learning. This Special Issue will focus on food quality, safety, variety, and origin. It will provide the latest original research on food in relation to spectroscopy and machine learning.
Potential topics include, but are not limited to, the following:
- Preprocessing methods for food spectral data;
- The extraction of spectral features related to food properties based on machine learning;
- The prediction of food internal quality, microorganisms, and harmful substances;
- The identification of adulteration and authenticity;
- The traceability of variety and origin;
- The establishment of food spectral fingerprints.
Prof. Dr. Zhengjun Qiu
Dr. Lei Zhou
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
- infrared spectroscopy
- hyperspectral imaging
- machine learning
- deep learning
- convolutional neural networks
- food quality
- food safety
- food authentication
- food traceability
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