An analytical and machine learning approach for total mercury and methylmercury determination in squid: enhancing food safety testing and traceability monitoring systems

This study presents the first assessment of total mercury (THg) and methylmercury (MeHg) in squids (Todarodes sagittatus, L.), providing insights into contamination levels and their correlation with the geographical origin. A method based on acidic extraction of THg, re-extraction of MeHg into tolue...

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Bibliographic Details
Published in:Food chemistry 2025-12, Vol.496 (Pt 2), p.146766, Article 146766
Main Authors: Piroutková, Martina, Varrà, Maria Olga, Husáková, Lenka, Bachtíková, Tereza, Kuba, Martin, Zanardi, Emanuela
Format: Article
Language:English
Subjects:
Animals
cost effectiveness
cysteine
Decapodiformes - chemistry
Direct mercury analysis (DMA)
food chemistry
Food Contamination - analysis
Food Safety
Food traceability
Machine Learning
mercury
Mercury - analysis
methylmercury compounds
Methylmercury Compounds - analysis
Multivariate optimization
principal component analysis
Principal component analysis (PCA)
provenance
Seafood - analysis
squid
Support vector machine (SVM) classification
support vector machines
Todarodes
toluene
traceability
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