Adulteration of Clove Essential Oil: Detection Using an Electronic Nose with Polymeric Gas Sensors

• Published in: Food analytical methods Vol. 17; no. 2; pp. 296 - 308
• Main Authors: Graboski, Adriana Marcia, Feltes, Giovana, Zakrzevski, Claudio Augusto, Shimizu, Flavio Makoto, Steffens, Juliana, Paroul, Natália, Steffens, Clarice
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2024; Springer Nature B.V
• Subjects: Adulterants; Analytical Chemistry; Chemistry; Chemistry and Materials Science; Chemistry/Food Science; Cluster analysis; Clustering; Discriminant analysis; Electronic noses; Essential oils; Food industry; Food Science; Fourier transforms; Gas sensors; Infrared analysis; Microbiology; Nanocomposites; Oils & fats; Petrolatum; Principal components analysis; Refractivity; Sensors; Volatile compounds; Vaseline; Nanocomposite sensors; Clove essential oil; Electronic nose
• ISSN: 1936-9751; 1936-976X
• DOI: 10.1007/s12161-023-02564-8

Food adulteration is a global concern that affects almost all the food industry. The market for clove essential oil (CEO) has also been affected by corrupt practices. As an alternative to monitoring the quality of this product, an electronic nose (e-nose) based on an array of polymeric nanocomposite gas sensors modified with different sensitive layers was applied to detect vaseline (petroleum jelly), the most common adulterant found in the CEO. Different proportions of vaseline (ranging from 3 to 100% (v/v)) were mixed with CEO samples, and the fingerprints of volatile compounds were obtained using the e-nose and Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy. Collected data were analyzed using clustering analysis (CA), principal component analysis (PCA), linear discriminant analysis (LDA), and interactive document map (IDMAP) multivariate projection techniques. These were capable of discriminating between the different percentages of adulterants. The results of this study demonstrated that chemometric tools can be successfully used as e-nose and applied to detect mislabeling and adulteration of CEO, where PCA, LDA, and IDMAP showed accuracies of 99.85, 98.30, and 99.81%, respectively. The e-nose results were consistent with the findings from density and refractive index experiments. Thus, the results obtained demonstrate that the e-nose is a promising tool for analyzing CEO adulterations, proving its potential application in the food industry due to its rapid, economical, and high-performance tool.