Evidence map›Paper›PMID 42136795›Full record

ArticleFood science & nutrition2026

Comprehensive Flavor Profiling of Dairy Products Using Electronic Tongue: Discrimination Based on Processing Parameters and Formulations.

Juan Huang, Jing-Wei Zhong, Li-Guang Jiang, Yan-Yan Huang, Dong-Mei Liu

Abstract read
In one paragraph

Article in Food science & nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Juan HuangSchool of Food and Pharmaceutical Science and Technology Guangzhou College of Technology and Business Guangzhou Guangdong China.ORCID https://orcid.org/0009-0004-5393-885X
Jing-Wei ZhongSchool of Food and Pharmaceutical Science and Technology Guangzhou College of Technology and Business Guangzhou Guangdong China.
Li-Guang JiangSchool of Food and Pharmaceutical Science and Technology Guangzhou College of Technology and Business Guangzhou Guangdong China.
Yan-Yan HuangCollege of Food Science and Engineering Foshan University Foshan China.
Dong-Mei LiuSchool of Food Science and Engineering South China University of Technology Guangzhou Guangdong China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flavor is a critical determinant of consumer acceptance for dairy products. However, objectively deconvoluting the contributions of multifactor interactions-such as processing conditions, formulations, and raw material properties-remains challenging. This study employed the INSENT TS-5000Z electronic tongue (E-tongue), supplemented by sensory evaluation and chemical analysis, to profile eight fresh milk and six plain yoghurt samples from five leading brands. Key variables included sterilization methods, milk sources, and sugar content. Nine taste indices were quantified. Principal component analysis (PCA) effectively discriminated samples based on these parameters, with cumulative variances of 81.2% for milk and 92.5% for yoghurt. Organic milk (SY-JZ-ORG) exhibited significantly higher bitterness (10.77 ± 0.04 TU) and astringency (4.60 ± 0.02 TU), which correlated with elevated levels of α-linolenic acid, hydrophobic peptides, and the creamy lactone δ-decalactone. Full-sugar yoghurt (MN-Y) showed pronounced astringency (9.38 ± 0.20 TU), consistent with its highest sensory scores for "thickness" and "astringency." Partial least squares regression (PLSR) models reliably predicted sensory attributes from E-tongue data (R

Indexed as

dairy productselectronic tongueflavor profilingmultivariable interactionpartial least squares regressionprincipal component analysis (PCA)

Identifiers

PMID42136795
PMCPMC13169148

What OpenQuestion holds

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Registered trials

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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.