Advances in Sensory Science: Integrating Cutting-Edge Technologies to Decode Sensory and Consumer Perceptions

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Sensory and Consumer Sciences".

Deadline for manuscript submissions: closed (23 October 2025) | Viewed by 1164

Special Issue Editor


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Guest Editor
Department of Food Science and Nutrition, Dankook University, Cheonan 31116, Republic of Korea
Interests: sensory evaluation; food texture and rheology; food processing (meat and agricultural products)
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Special Issue Information

Dear Colleagues,

In the era of rapid technological evolution, sensory science is undergoing a transformation driven by artificial intelligence, XR digital interfaces, neurophysiological tools, and omics technologies. These innovations are expanding the boundaries of how we understand and interpret consumer perception, especially in the context of food choice, product development, and consumer experience.

This Special Issue of Foods seeks to spotlight cutting-edge techniques in sensory and consumer science that are reshaping the field. We invite contributions that explore how AI-driven analytics, extended reality (XR)—including virtual reality (VR) and mixed reality (MR)—biometrics, neuroimaging, virtual environments, digital twins, and omics-based approaches are being applied to measure, predict, and enhance sensory quality and consumer satisfaction. 

Dr. Youngseung Lee
Guest Editor

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

  • AI and machine learning applications in sensory and consumer data analysis and predictive modeling
  • Electronic sensing systems: electronic noses, tongues, and robotic sensory evaluation;
  • Neurosensory and cognitive tools: EEG, fMRI, fNIRS applied to flavor, aroma, and texture perception;
  • XR technologies: use of VR, AR, and MR to simulate environments, enhance sensory immersion, and conduct contextualized food studies;
  • Digital twins and computational models for food product development and sensory optimization;
  • Biometrics in sensory testing: EMG, EGN, EEG, eye tracking, galvanic skin response, heart rate variability, and facial expression analysis;
  • Temporal sensory methods (e.g., Temporal Dominance of Sensations, Time–Intensity) integrated with real-time analytics;
  • Flavoromics, metabolomics, and chemometrics to uncover molecular sensory drivers;
  • Multimodal sensory integration using data fusion from vision, taste, smell, and texture;
  • Ethical, practical, and methodological considerations in the adoption of advanced technologies for sensory research

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Published Papers (1 paper)

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Review

45 pages, 1164 KB  
Review
Integrating Cutting-Edge Technologies in Food Sensory and Consumer Science: Applications and Future Directions
by Dongju Lee, Hyemin Jeon, Yoonseo Kim and Youngseung Lee
Foods 2025, 14(24), 4169; https://doi.org/10.3390/foods14244169 - 5 Dec 2025
Viewed by 391
Abstract
With the introduction of emerging digital technologies, sensory and consumer science has evolved beyond traditional laboratory-based and self-response-centered sensory evaluations toward more objective assessments that reflect real-world consumption contexts. This review examines recent trends and potential applications in sensory evaluation research focusing on [...] Read more.
With the introduction of emerging digital technologies, sensory and consumer science has evolved beyond traditional laboratory-based and self-response-centered sensory evaluations toward more objective assessments that reflect real-world consumption contexts. This review examines recent trends and potential applications in sensory evaluation research focusing on key enabling technologies—artificial intelligence (AI) and machine learning (ML), extended reality (XR), biometrics, and digital sensors. Furthermore, it explores strategies for establishing personalized, multimodal, and intelligent–adaptive sensory evaluation systems through the integration of these technologies, as well as the applicability of sensory evaluation software. Recent studies report that AI/ML models used for sensory or preference prediction commonly achieve RMSE values of approximately 0.04–24.698, with prediction accuracy ranging from 79 to 100% (R2 = 0.643–0.999). In XR environment, presence measured by the IPQ (7-point scale) is generally considered adequate when scores exceed 3. Finally, the review discusses ethical considerations arising throughout data collection, interpretation, and utilization processes and proposes future directions for the advancement of sensory and consumer science research. This systematic literature review aims to identify emerging technologies rather than provide a quantitative meta-analysis and therefore does not cover domain-specific analytical areas such as chemometrics beyond ML approaches or detailed flavor and aroma chemistry. Full article
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