Evidence map›Paper›PMID 31817434›Full record

ArticleSensors (Basel, Switzerland)2019

Computer Vision Approach for the Determination of Microbial Concentration and Growth Kinetics Using a Low Cost Sensor System.

Marco Grossi, Carola Parolin, Beatrice Vitali, Bruno Riccò

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Growth Kinetics ofACS omega · 2021
    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

4 authors.

Marco GrossiDepartment of Electrical Energy and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, 40136 Bologna, Italy.ORCID 0000-0003-1316-9035
Carola ParolinDepartment of Pharmacy and Biotechnology (FaBiT), University of Bologna, 40127 Bologna, Italy.
Beatrice VitaliDepartment of Pharmacy and Biotechnology (FaBiT), University of Bologna, 40127 Bologna, Italy.
Bruno RiccòDepartment of Electrical Energy and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, 40136 Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The measurement of microbial contamination is of primary importance in different fields, from environmental monitoring to food safety and clinical analysis. Today, almost all microbiology laboratories make microbial concentration measurements using the standard Plate Count Technique (PCT), a manual method that must be performed by trained personnel. Since manual PCT analysis can result in eye fatigue and errors, in particular when hundreds of samples are processed every day, automatic colony counters have been built and are commercially available. While quick and reliable, these instruments are generally expensive, thus, portable colony counters based on smartphones have been developed and are of low cost but also not accurate as the commercial benchtop instruments. In this paper, a novel computer vision sensor system is presented that can measure the microbial concentration of a sample under test and also estimate the microbial growth kinetics by monitoring the colonies grown on a Petri dish at regular time intervals. The proposed method has been in-house validated by performing PCT analysis in parallel under the same conditions and using these results as a reference. All the measurements have been carried out in a laboratory using benchtop instruments, however, such a system can also be realized as an embedded sensor system to be deployed for microbial analysis outside a laboratory environment.

Indexed as

AlgorithmsBacteriaColony Count, MicrobialImage Processing, Computer-AssistedKineticsbacteriacomputer visionplate countportable systemsensor

Identifiers

PMID31817434
PMCPMC6960508

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LicenceCC BY
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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.