ArticleFood chemistry: X2023
Determination of procymidone residues in rapeseed oil based on olfactory visualization technology.
Article in Food chemistry: X, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Integration of Colorimetric Sensing Dyes and Multi-Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis.Comprehensive reviews in food science and food safety · 2026Review
- Advances in predicting human olfactory perception: from data acquisition to computational models.RSC advances · 2025Review
- Near-infrared spectroscopy based on colorimetric sensor array coupled with convolutional neural network detecting zearalenone in wheat.Food chemistry: X · 2024Article
- Advancing image segmentation with DBO-Otsu: Addressing rubber tree diseases through enhanced threshold techniques.PloS one · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new means about olfactory visualization technique for the quantitative analysis of procymidone residues in rapeseed oil has been proposed. First, an olfactory visualization system was set up to collect volatile odor information from rapeseed oil samples containing different concentrations of procymidone residues. Then, we utilized four intelligent optimization algorithms, namely particle swarm optimization (PSO), genetic algorithm (GA), ant colony optimization (ACO) and simulated annealing (SA), to optimize the characteristics of the sensors. Finally, support vector machine regression (SVR) models employing optimized features were constructed for the quantitative detection of procymidone residues in rapeseed oil. The study demonstrated that the SA-SVR model demonstrated superior prediction results, achieving a high determination coefficient of prediction (
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Registered trials
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.