Attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy coupled with chemometric analysis for detection and quantification of adulteration in lavender and citronella essential oils. Issue 6 (10th February 2021)

• Record Type: Journal Article
• Authors: Truzzi, Eleonora; Marchetti, Lucia; Bertelli, Davide; Benvenuti, Stefania
• Is Part Of: Phytochemical analysis. Volume 32:Issue 6(2021)
• Page Start: 907
• Page End: 920
• Publication Date: 2021-02-10
• Subjects: attenuated total reflectance–Fourier transform infrared (ATR–FTIR) -- citronella -- counterfeits -- Cymbopogon winterianus Jowitt -- Lavandula angustifolia Miller -- lavender -- multivariate statistical analysis -- partial least‐squares (PLS) regression -- principal component analysis (PCA); Plants -- Analysis -- Periodicals; Plants -- chemistry -- Periodicals; 572.2
• DOI: 10.1002/pca.3034
• Languages: English
• ISSNs: 0958-0344

Abstract

Abstract: Introduction: The growing consumer interest in "naturals" led to an increased application of essential oils (EOs). The market outbreak induced the intensification of EO adulterations, which could affect their quality. Objectives: Nowadays, little is known about the illegal practice of adulteration of EOs with vegetable oils. Therefore, the application of mid‐infrared spectroscopy coupled with chemometrics was proposed for the detection of EO counterfeits. Materials and methods: Two EOs, three seed oils, and their mixtures were selected to build the adulteration model. EO–adulterant mixtures for model calibration and validation were analyzed by attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy. The spectral data were analyzed with principal component analysis (PCA) and partial least‐squares (PLS) regression. Results: PCA allowed the discrimination of the EO and adulterant percentages by explaining 97.47% of the total spectral variance with two principal components. A PLS regression model was generated with three factors explaining 97.73% and 99.69% of the total variance in X and Y, respectively. The root mean square error of calibration and the root mean square error of cross‐validation were 0.918 and 1.049, respectively. The root mean square error of prediction value obtained from the external validation set was 1.588 and the coefficients of determination R 2 CAL and R 2 CV were 0.997 and 0.996, respectively. Conclusions: The results highlighted the robustness of the developed method in quantifying counterfeits in the range from 0 to 50% of adulterants, disregarding the type of EO and adulterant employed. The present work offers a research advance and makes an important impact in phytochemistry, revealing an easily applicable method for EO quality assessment. Abstract : The present study aims to assess the potential of ATR–FTIR spectroscopy coupled with chemometrics to determine vegetable oil content in adulterated EOs. Spectral data were examined by PCA and PLS regression to extract the most relevant information from data useful for adulteration detection. The results demonstrated the potentiality of the developed method in quantifying adulterant content in mixtures with EOs. The results laid the foundation for ameliorating the model for further development of this analytical method.