Special Issue "Applications of Non-destructive Technologies for Agricultural and Food Product Quality Determination"
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".
Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 17780
Special Issue Editors
Interests: sustainable food processing; non-destructive methods - hyperspectral imaging, acoustic sensing, machine learning; food extrusion; alternative ingredients/ protein; millet value-addition
Special Issues, Collections and Topics in MDPI journals
Interests: non-destructive testing of foods—hyperspectral imaging and near infrared spectroscopy; mathematical modeling of food systems; heat and mass transfer during food processing—deep-fat frying; novel extraction methods
Interests: hyperspectral imaging; computer vision; machine learning; artificial intelligence; food quality and safety
Special Issue Information
Dear Colleagues,
The recent pandemic reinforces the need for more nondestructive technology development within the agricultural and food processing sectors in order to prevent the disruption experienced in the food supply chain at the peak of the spread of the virus. There are several other advantages to nondestructive detection and characterization of biological materials such as foods. The product is preserved and reusable after testing, often rapid, and its application is easy; additionally, it removes the drudgery from the process, and it is a ready tool in robotics application in food. Nondestructive methods have the potential to increase sustainability within the agricultural production and food processing industry, through reduced waste, increased safety of our foods, efficient production and processing, and reduced cost. With recent advances in computational analysis, especially with improved machine learning methods and deep learning methods, the accuracy of prediction of food properties is improving, and this is pushing the boundaries of applications with increased reliability. This Special Issue will disseminate recent advances in innovation, technology, and application of the nondestructive approach for food and agricultural product quality determination.
Dr. Akinbode A. Adedeji
Prof. Dr. Michael Ngadi
Dr. Laura Liu
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
- novel nondestructive methods for food quality determination
- advances in traditional methods for nondestructive testing of foods: Raman spectroscopy, optical sensing, electronic nose, near-infrared spectroscopy, computer vision
- hyperspectral imaging application in biological material quality determination
- vibroacoustic emission method application in food quality detection
- machine and deep learning application in food quality determination
- model and sensor data fusion approach for improved data analytics
- artificial intelligence and robotics for improved quality characterization