Evidence map›Paper›PMID 33452026›Full record

ArticleApplied and environmental microbiology2021

Changes in Bacterial and Chemical Components and Growth Prediction for Lactobacillus sakei during Kimoto-Style Fermentation Starter Preparation in Sake Brewing: a Comprehensive Analysis.

Masayuki Takahashi, Kana Morikawa, Yasuko Kita, Takamasa Shimoda, Takeshi Akao, Nami Goto-Yamamoto

Open access · greenAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 8% of its field
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

7 citing papers in PubMed, 31 citations in OpenAlex.

  1. Review
  2. Article
  3. Comparative genomic analysis ofMicrobiology (Reading, England) · 2025
    Article
  4. Article
  5. Lot-to-lot variation in the microbiota during the brewing process ofBioscience of microbiota, food and health · 2024
    Article
  6. Article
  7. A dark matter inFrontiers in microbiology · 2023
    Article
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

6 authors at 1 institution in 1 country.

Masayuki TakahashiNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan m.takahashi@nrib.go.jp.ORCID 0000-0003-0594-5399
Kana MorikawaNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan.
Yasuko KitaNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan.
Takamasa ShimodaNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan.
Takeshi AkaoNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan.
Nami Goto-YamamotoNational Research Institute of Brewing (NRIB), Higashi-Hiroshima, Japan.
National Research Institute of Brewing · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kimoto-style seed mash is a traditional preparation method for sake that takes advantage of spontaneous lactic acid fermentation before the growth of yeast. Lactic acid helps decrease the pH in seed mash and control the growth of unfavorable microorganisms. In this study, we carried out a comprehensive analysis of the change in the bacterial community and chemical composition during the lactic acid fermentation stage in kimoto-style seed mash preparation. The bacterial transitions were diverse at five sake breweries, but they exhibited three patterns.

Indexed as

Alcoholic BeveragesArginineFermentationHydrogen-Ion ConcentrationLactic AcidLatilactobacillus sakeiTemperatureArginineLactic Acidargininebacterial diversitygrowth prediction of Lactobacillus sakeikimotosake

Identifiers

PMID33452026
PMCPMC8105003
OpenAlexW3124981547

What OpenQuestion holds

Textmetadata
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.