Evidence map›Paper›PMID 37893256›Full record

ReviewMicromachines2023

Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination.

Giovana Feltes, Sandra C Ballen, Juliana Steffens, Natalia Paroul, Clarice Steffens

Open access · goldAbstract readReview
In one paragraph

Review in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Compounds of Essential Oils from Different Parts ofFoods (Basel, Switzerland) · 2025
    Article
  3. Assessing the Authenticity and Quality of Paprika (Foods (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. 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

5 authors at 1 institution in 1 country.

Giovana FeltesDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, Brazil.
Sandra C BallenDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, Brazil.
Juliana SteffensDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, Brazil.ORCID 0000-0001-6607-2283
Natalia ParoulDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, Brazil.ORCID 0000-0001-9809-7944
Clarice SteffensDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, Brazil.ORCID 0000-0003-4394-125X
Universidade Regional Integrada do Alto Uruguai e das Missões · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consumer confidence. Through the utilization of physical-chemical and instrumental analyses, the purity of EOs was evaluated via qualitative and quantitative assessments, enabling the identification of constituents or compounds within the oils. Consequently, a diverse array of techniques has been documented, encompassing organoleptic, physical, chemical, and instrumental methodologies, such as spectroscopic and chromatographic methods. Electronic noses (e-noses) exhibit significant potential for identifying cinnamon adulteration, presenting a rapid, non-destructive, and cost-effective approach. Leveraging their capability to detect and analyze volatile organic compound (VOC) profiles, e-noses can contribute to ensuring authenticity and quality in the food and fragrance industries. Continued research and development efforts in this domain will assuredly augment the capacities of this promising avenue, which is the utilization of Artificial Intelligence (AI) and Machine Learning (ML) algorithms in conjunction with spectroscopic data to combat cinnamon adulteration.

Indexed as

authenticitydiscriminationfood industryinstrumental analysisphysical–chemical analysisquality assurance

Identifiers

PMID37893256
PMCPMC10609063
OpenAlexW4386996767

What Socratic 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 Socratic graph.