Evidence map›Paper›PMID 32012437›Full record

ArticleJournal of separation science2020

Elevated viscosities in a simulated moving bed for γ-aminobutyric acid recovery.

A Schultze-Jena, M A Boon, R C Vroon, P J Th Bussmann, A E M Janssen, A van der Padt

Abstract read
In one paragraph

Article in Journal of separation science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

1 citing paper in PubMed.

  1. 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.

A Schultze-JenaFood and Biobased Research, Wageningen University and Research, Wageningen, The Netherlands.ORCID https://orcid.org/0000-0001-9896-3881
M A BoonFood and Biobased Research, Wageningen University and Research, Wageningen, The Netherlands.
R C VroonFood and Biobased Research, Wageningen University and Research, Wageningen, The Netherlands.
P J Th BussmannFood and Biobased Research, Wageningen University and Research, Wageningen, The Netherlands.
A E M JanssenFood Process Engineering, Wageningen University and Research, Wageningen, The Netherlands.
A van der PadtFood Process Engineering, Wageningen University and Research, Wageningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Process streams of agro-food industries are often large and viscous. In order to fractionate such a stream the viscosity can be reduced by either a high temperature or dilution, the former is not an option in case of temperature sensitive components. Such streams are diluted prior to chromatographic fractionation, resulting in even larger volumes and high energy costs for sub-sequential water removal. The influence of feed viscosity on the performance of simulated moving bed chromatography has been investigated in a case study of the recovery of a γ-aminobutyric acid rich fraction from tomato serum. This work addresses the chromatographic system design, evaluates results from a pilot scale operation, and uses these to calculate the productivity and water use at elevated feed concentration. At the two higher feed viscosities (2.5 and 4 mPa·s) water use is lower and productivity higher, compared to the lowest feed viscosity (1 mPa·s). The behavior of the sugars for different feed viscosities can be described well by the model using the ratio of feed to eluent as dilution factor. The behavior of γ-aminobutyric acid is highly concentration dependent and the recovery could not be accurately predicted.

Indexed as

gamma-Aminobutyric AcidSolanum lycopersicumViscositygamma-Aminobutyric Acidchromatographyconcentration profileproductivitysimulated moving bedviscosity

Identifiers

PMID32012437
PMCPMC7187226

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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.