Evidence map›Paper›PMID 42621155›Full record

ArticleCurrent research in food science2026

A triangulation and neural network approach reveals the microbe-metabolite-sensory associations of fermented milk.

Youming Tan, Tong Wu, Haojie Ni, Baosong Wang, Zihao Liu, Hong Zeng, Yanbo Wang

Abstract read
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Article in Current research in food science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Youming TanFlavor Science Laboratory, Beijing Life Science Academy (BLSA), Beijing, 102209, China.
Tong WuSchool of Food and Health, Beijing Technology and Business University, Beijing, 100048, China.
Haojie NiFlavor Science Laboratory, Beijing Life Science Academy (BLSA), Beijing, 102209, China.
Baosong WangSchool of Food and Health, Beijing Technology and Business University, Beijing, 100048, China.
Zihao LiuSchool of Food and Health, Beijing Technology and Business University, Beijing, 100048, China.
Hong ZengSchool of Food and Health, Beijing Technology and Business University, Beijing, 100048, China.
Yanbo WangSchool of Food and Health, Beijing Technology and Business University, Beijing, 100048, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the causal associations among microorganisms, flavor metabolites, and sensory attributes is essential for the precise regulation of the flavor of fermented milk. In this study, 22 commercial fermented milks were characterized using sensory evaluation, microbial analysis, and volatile metabolite profiling. Five sensory phenotypes were developed, each exhibiting unique flavor profiles. However, microbial community structures differed only slightly among phenotypes, suggesting that the community structure itself could not fully explain sensory diversification. Therefore, generalized microbe-phenotype triangulation analysis was performed and identified multiple causal taxa associated with different sensory phenotypes, while the mmvec model further revealed strong associations between certain microorganisms and characteristic aroma compounds. Overall, this study established a novel data-driven framework for exploring potential causal associations among microorganisms, flavor metabolites, and sensory phenotypes in fermented milks, representing a preliminary effort to move beyond conventional correlation-based analyses.

Indexed as

Computational methodFermented milkGC × GC-TOFMSMicrobe-metabolite-sensory associations

Identifiers

PMID42621155
PMCPMC13486852

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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.