Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Transform Infrared Spectroscopy.

Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xi WangState Key Laboratory of Marine Food Processing and Safety Control, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.

Siyi WangState Key Laboratory of Marine Food Processing and Safety Control, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.

Shibing ZhangState Key Laboratory of Marine Food Processing and Safety Control, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.

Jiping YinInformation Technology Center, Dalian Polytechnic University, Dalian 116034, China.

Qi ZhaoState Key Laboratory of Marine Food Processing and Safety Control, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.ORCID 0000-0003-1124-5516

Funding

National Key Research and Development Project 2018YFC1406805

6 · The paper itself

Abstract

As one kind of 'probable human carcinogen' (Group 2B) compound classified by the International Agency for Research on Cancer, 3-MCPD is mainly formed during the thermal processing of food. Tedious pretreatment techniques are needed for the existing analytical methods to quantify 3-MCPD. Hence, a nondestructive sensing technique that offers low noise interference and high quantitative precision must be developed to address this problem. Following this, Fourier transform infrared spectroscopy association with an convolutional neural network (CNN) model was employed in this investigation for the nondestructive quantitative measurement of 3-MCPD in oil samples. Before building the CNN model, NL-SGS-D

Indexed as

3-monochloropropane-1,2-diolconvolutional neural networkdata preprocessingFourier transform infrared spectroscopyrapid detection

Identifiers

PMID40428450

DOI10.3390/foods14101670

PMCPMC12111188

What OpenQuestion 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 OpenQuestion graph.