Detection of Counterfeit Perfumes by Using GC-MS Technique and Electronic Nose System Combined with Chemometric Tools.
Youssra AghoutaneMihai BrebuMohammed MoufidRadu IonescuBenachir BouchikhiNezha El BariPublished in: Micromachines (2023)
The Scientific Committee on Cosmetic and Non-Food Products has identified 26 compounds that may cause contact allergy in consumers when present in concentrations above certain legal thresholds in a product. Twenty-four of these compounds are volatiles and can be analyzed by gas chromatography-mass spectrometry (GC-MS) or electronic nose (e-nose) technologies. This manuscript first describes the use of the GC-MS approach to identify the main volatile compounds present in the original perfumes and their counterfeit samples. The second part of this work focusses on the ability of an e-nose system to discriminate between the original fragrances and their counterfeits. The analyses were carried out using the headspace of the aqueous solutions. GC-MS analysis revealed the identification of 10 allergens in the perfume samples, some of which were only found in the imitated fragrances. The e-nose system achieved a fair discrimination between most of the fragrances analyzed, with the counterfeit fragrances being clearly separated from the original perfumes. It is shown that associating the e-nose system to the appropriate classifier successfully solved the classification task. With Principal Component Analysis (PCA), the three first principal components represented 98.09% of the information in the database.
Keyphrases
- gas chromatography mass spectrometry
- gas chromatography
- machine learning
- healthcare
- solid phase extraction
- emergency department
- deep learning
- mass spectrometry
- loop mediated isothermal amplification
- social media
- single cell
- risk assessment
- sensitive detection
- real time pcr
- bioinformatics analysis
- infectious diseases
- neural network