Evidence map›Paper›PMID 27555305›Full record

ArticlemBio2016

The Core and Seasonal Microbiota of Raw Bovine Milk in Tanker Trucks and the Impact of Transfer to a Milk Processing Facility.

Mary E Kable, Yanin Srisengfa, Miles Laird, Jose Zaragoza, Jeremy McLeod, Jessie Heidenreich, Maria L Marco

Abstract read
In one paragraph

Article in mBio, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
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  11. Inactivation of KhpB (EloR/Jag) inApplied and environmental microbiology · 2025
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  17. Genetic Profile and Toxigenic Potential ofFoods (Basel, Switzerland) · 2024
    Article
  18. Article
  19. Article
  20. Article

8 more citing papers are in PubMed but not listed here.

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

7 authors.

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.
Miles LairdDepartment of Food Science and Technology, University of California Davis, Davis, California, USA.
Jose ZaragozaDepartment of Food Science and Technology, University of California Davis, Davis, California, USA.
Jeremy McLeodHilmar Cheese Company, Hilmar, California, USA.
Jessie HeidenreichHilmar Cheese Company, Hilmar, California, USA.
Maria L MarcoDepartment of Food Science and Technology, University of California Davis, Davis, California, USA mmarco@udavis.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledCurrently, the bacterial composition of raw milk in tanker trucks and the outcomes of transfer and storage of that milk at commercial processing facilities are not well understood. We set out to identify the bacteria in raw milk collected for large-scale dairy product manufacturing. Raw bovine milk samples from 899 tanker trucks arriving at two dairy processors in San Joaquin Valley of California during three seasons (spring, summer, and fall) were analyzed by community 16S rRNA gene sequencing. This analysis revealed highly diverse bacterial populations, which exhibited seasonal differences. Raw milk collected in the spring contained the most diverse bacterial communities, with the highest total cell numbers and highest proportions being those of Actinobacteria Even with this complexity, a core microbiota was present, consisting of 29 taxonomic groups and high proportions of Streptococcus and Staphylococcus and unidentified members of Clostridiales Milk samples were also collected from five large-volume silos and from 13 to 25 tankers whose contents were unloaded into each of them during 2 days in the summer. Transfer of the milk to storage silos resulted in two community types. One group of silos contained a high proportion of Streptococcus spp. and was similar in that respect to the tankers that filled them. The community found in the other group of silos was distinct and dominated by Acinetobacter Overall, despite highly diverse tanker milk community structures, distinct milk bacterial communities were selected within the processing facility environment. This knowledge can inform the development of new sanitation procedures and process controls to ensure the consistent production of safe and high-quality dairy products on a global scale. IMPORTANCE: Raw milk harbors diverse bacteria that are crucial determinants of the quality and safety of fluid milk and (fermented) dairy products. These bacteria enter farm milk during transport, storage, and processing. Although pathogens are destroyed by pasteurization, not all bacteria and their associated enzymes are eliminated. Our comprehensive analyses of the bacterial composition of raw milk upon arrival and shortly after storage at major dairy processors showed that the communities of milk microbiota are highly diverse. Even with these differences, there was a core microbiota that exhibited distinct seasonal trends. Remarkably, the effects of the processing facility outweighed those of the raw milk microbiome and the microbial composition changed distinctly within some but not all silos within a short time after transfer. This knowledge can be used to inform cleaning and sanitation procedures as well as to enable predictions of the microbial communities in raw milk that result in either high-quality or defective products.

Indexed as

BiotaAnimalsBacteriaCaliforniaCluster AnalysisDairyingDNA, BacterialDNA, RibosomalMilkPhylogenyRNA, Ribosomal, 16SSeasonsSequence Analysis, DNADNA, BacterialDNA, RibosomalRNA, Ribosomal, 16S

Identifiers

PMID27555305
PMCPMC4999540

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.