Evidence map›Paper›PMID 39123616›Full record

ArticleFoods (Basel, Switzerland)2024

Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey.

Mennatullah Shehata, Sophie Dodd, Sara Mosca, Pavel Matousek, Bhavna Parmar, Zoltan Kevei, Maria Anastasiadi

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2024. 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
–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

7 citing papers in PubMed.

  1. Article
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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.

Mennatullah ShehataCentre for Soil, Agrifood and Biosciences, Cranfield University, College Road, Cranfield, Bedford MK43 0AL, UK.ORCID 0009-0000-8243-7879
Sophie DoddCentre for Soil, Agrifood and Biosciences, Cranfield University, College Road, Cranfield, Bedford MK43 0AL, UK.ORCID 0000-0001-9805-4477
Sara MoscaCentral Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UKRI Harwell Campus, Didcot OX11 0QX, UK.ORCID 0000-0001-9479-5614
Pavel MatousekCentral Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UKRI Harwell Campus, Didcot OX11 0QX, UK.ORCID 0000-0003-0912-5339
Bhavna ParmarFood Standards Agency, Clive House, 70 Petty France, Westminster, London SW1H 9EX, UK.
Zoltan KeveiCentre for Soil, Agrifood and Biosciences, Cranfield University, College Road, Cranfield, Bedford MK43 0AL, UK.ORCID 0000-0002-3065-3198
Maria AnastasiadiCentre for Soil, Agrifood and Biosciences, Cranfield University, College Road, Cranfield, Bedford MK43 0AL, UK.ORCID 0000-0001-7871-5514

Funding

Food Standards Agency N/ASTFC Food NEtwork+ N/A
6 · The paper itself

Abstract

Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. This study aimed to develop non-invasive sensor methods coupled with a multivariate data analysis to detect the type and percentage of exogenous sugar adulteration in UK honeys. Through-container spatial offset Raman spectroscopy (SORS) was employed on 17 different types of natural honeys produced in the UK over a season. These samples were then spiked with rice and sugar beet syrups at the levels of 10%, 20%, 30%, and 50%

Indexed as

classificationhoneyrandom forestregressionSORS

Identifiers

PMID39123616
PMCPMC11312281

What OpenQuestion holds

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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.