Evidence map›Paper›PMID 40746653›Full record

ReviewFood science & nutrition2025

Trends and Directions of Preference Elicitation and Assessment in Food Science: Single-, Pair-, and Multi-Criteria Ranking Methods.

László Sipos, Zsófia Galambosi, Péter Biró, László Csató, Sándor Bozóki

Abstract readReview
In one paragraph

Review in Food science & nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

László SiposInstitute of Food Science and Technology, Department of Postharvest, Commercial and Sensory Science Hungarian University of Agriculture and Life Sciences Budapest Hungary.ORCID https://orcid.org/0000-0002-4584-6697
Zsófia GalambosiInstitute of Food Science and Technology, Department of Postharvest, Commercial and Sensory Science Hungarian University of Agriculture and Life Sciences Budapest Hungary.
Péter BiróCentre of Economic and Regional Studies, Hungarian Research Network (HUN-REN) Institute of Economics Budapest Hungary.
László CsatóInstitute of Operations Research and Decision Systems, Department of Operations Research and Actuarial Sciences Corvinus University of Budapest Budapest Hungary.
Sándor BozókiInstitute of Operations Research and Decision Systems, Department of Operations Research and Actuarial Sciences Corvinus University of Budapest Budapest Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Different ranking methods have long been used in sensory testing. Their diffusion was mainly due to their simplicity, their standardized methods, their software support, and their wide range of applications. However, a number of research and industrial problems have emerged recently that cannot be adequately solved by the standard approaches, making it necessary to apply and adapt methods from other disciplines. This article discusses the ranking methods of international sensory standardization (single-, pair-ranking methods, balanced incomplete block design (BIBD) according to the structure of standardization). We overview ranking methods in international sensory competitions. We evaluate some potential applications of ranking methodological developments pair ranking, Analytic Hierarchy Process (AHP), multi-criteria decision making (MCDM), graph theory, developed and applied by other disciplines, which are less used in sensory sciences. The principles and applications of these methodologies are summarized, and factors affecting their effectiveness and limitations are discussed. Preference modeling and quantification are key questions of decision and sensory sciences. Both areas require true, unbiased individual responses as well as their appropriate aggregation. Competitions are typically multi-criteria problems, evaluated by several decision makers. To better understand consumer preferences and to explore complex consumer choices, different methods and software from other disciplines-decision and social choice theory, operations research, economics (e.g., ranking based on pairwise comparisons, AHP, MCDM, graph theory)-are adapted and disseminated. In addition to surveying latest trends, we propose some areas of future research development.

Indexed as

analytic hierarchy process (AHP)balanced incomplete block design (BIBD)multi‐criteria decision making (MCDM)pairwise rankingsensory food competitions

Identifiers

PMID40746653
PMCPMC12311391

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.