Recent Advances in Statistical Research of Food Sensory Evaluation and Preference
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Sensory and Consumer Sciences".
Deadline for manuscript submissions: 15 September 2025 | Viewed by 520
Special Issue Editors
Interests: chemometrics and sensometrics; food sensory analysis; consumer studies: acceptability; market research; consumers
Special Issue Information
Dear Colleagues,
Sensory analysis and consumer studies represent dynamic fields in which statistical tools are crucial in experimental design and result interpretation. Simple univariate methods are essential in panellist selection and training, ensuring consistent and reliable data collection. Multivariate techniques can address the challenges of large and varied datasets influenced by individual histories, preferences, environmental factors, and cultural differences. Approaches such as principal component analysis for dimensionality reduction and interpretation, discriminant analysis for characterization and classification, correspondence analysis to associate individuals with food attributes or products, and generalized Procrustes analysis to align individual variations across practical techniques, among many others now included under the broad term “sensometrics”, can reveal patterns in high-dimensional data, linking sensory attributes to chemical composition, consumer preferences, and engineering variables.
Mixed-effects models and Bayesian statistics can further enhance analysis by handling variability within and between panels. These methods account for uncertainties, ensuring robust results even in the presence of complex sources of error. They also provide critical insights, supporting advanced techniques such as machine learning (ML) and artificial intelligence (AI) in predicting and segmenting consumer groups effectively. Moreover, multisensory integration models combine data on taste, aroma, and texture to offer a holistic understanding of sensory studies, enabling the development of products that better meet consumer expectations. Together, these approaches form an interdisciplinary framework that drives innovation in food science, helping researchers and the food industry to refine product development and enhance consumer satisfaction.
Prof. Dr. Manuel Rui Alves
Dr. Carla Barbosa
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
- sensory analysis
- consumer studies
- statistical tools
- consumer preferences
- chemometric techniques
- sensometric techniques
- multivariate analysis
- sensory attributes
- aroma
- texture
- product development
- artificial intelligence (AI)
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