Evidence map›Paper›PMID 31028031›Full record

ArticleApplied and environmental microbiology2019

Viable and Total Bacterial Populations Undergo Equipment- and Time-Dependent Shifts during Milk Processing.

Mary E Kable, Yanin Srisengfa, Zhengyao Xue, Laurynne C Coates, Maria L Marco

Open access · bronzeAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.4field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. A Flagella Hook Coding GeneFrontiers in microbiology · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. 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 at 2 institutions in 1 country.

Mary E KableDepartment of Food Science and Technology, University of California-Davis, Davis, California, USA.
Yanin SrisengfaDepartment of Food Science and Technology, University of California-Davis, Davis, California, USA.
Zhengyao XueDepartment of Food Science and Technology, University of California-Davis, Davis, California, USA.
Laurynne C CoatesDepartment of Food Science and Technology, University of California-Davis, Davis, California, USA.
Maria L MarcoDepartment of Food Science and Technology, University of California-Davis, Davis, California, USA mmarco@udavis.edu.
University of California, Davis · USWestern Human Nutrition Research Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We set out to identify the viable and total bacterial content in milk as it passes through a large-scale, dairy product manufacturing plant for pasteurization, concentration, separation, blending, and storage prior to cheese manufacture. A total of 142 milk samples were collected from up to 10 pieces of equipment for a period spanning 21 h on two collection dates in the spring and late summer of 2014. Bacterial composition in the milk was determined by 16S rRNA marker gene, high-throughput DNA sequencing. Milk samples from the late summer were paired such that half were treated with propidium monoazide (PMA) to enrich for viable cells prior to quantification by PCR and identification by DNA sequence analysis.

Indexed as

BacteriaFood MicrobiologyMicrobiotaPasteurizationAnimalsMilkbovine milkbuilt environmentcheesedairyfermentationmicrobiotaprocessing

Identifiers

PMID31028031
PMCPMC6581186
OpenAlexW2941637819

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.