Evidence map›Paper›PMID 31572877›Full record

ArticleACS omega2019

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints.

Ting-Hao Kuo, Min-Shan Kuei, Yi Hsiao, Hsin-Hsiang Chung, Cheng-Chih Hsu, Hong-Jhang Chen

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Article in ACS omega, 2019. 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
–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

6 citing papers in PubMed.

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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

6 authors.

Ting-Hao KuoDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.
Min-Shan KueiDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.
Yi HsiaoDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.
Hsin-Hsiang ChungDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.
Cheng-Chih HsuDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.
Hong-Jhang ChenDepartment of Chemistry, Institute of Food Science and Technology, and Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this study, a robust and simple MALDI-TOF-MS platform for rapid fingerprinting of triacylglycerols (TAGs) in edible oils was developed, where spectral similarity analysis was performed to quantitatively reveal correlations among edible oils in the chemical level. Specifically, we proposed oil networking, a spectral similarity-based illustration, which enabled reliable classifications of tens of commercial edible oils from vegetable and animal origins. The strategy was superior to traditional multivariate statistics due to its high sensitivity in probing subtle changes in TAG profiles, as further demonstrated by the success in determination of the adulterated lard in a food fraud in Taiwan. Finally, we showed that the platform allowed quantitative assessment of the binary mixture of olive oil and canola oil, which is a common type of olive oil adulteration in the market. Overall, these results suggested a novel strategy for chemical fingerprint-based quality control and authentication of oils in the food industry.

Identifiers

PMID31572877
PMCPMC6761802

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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.