AUTHENTICATION OF GRAPE SEED FACE OIL USING FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS TECHNIQUES

ANDI PRAYOGA; ANJAR WINDARSIH; WURI APRIYANA; FLORENTINUS DIKA OCTA RISWANTO; ENADE PERDANA ISTYASTONO

doi:10.22159/ijap.2024v16i5.51525

Authors

ANDI PRAYOGA Magister of Pharmacy Study Program, Faculty of Pharmacy, Universitas Sanata Dharma, Yogyakarta-55282, Indonesia
ANJAR WINDARSIH Research Center for Food Technology and Processing, National Research and Innovation Agency, Jl. Jogja Wonosari km 31,5, Gunungkidul, Yogyakarta, Indonesia https://orcid.org/0000-0002-2235-7575
WURI APRIYANA Research Center for Food Technology and Processing, National Research and Innovation Agency, Jl. Jogja Wonosari km 31,5, Gunungkidul, Yogyakarta, Indonesia
FLORENTINUS DIKA OCTA RISWANTO Research Group of Computer-Aided Drug Design and Discovery of Bioactive Natural Products, Faculty of Pharmacy, Sanata Dharma University, Yogyakarta-55282, Indonesia https://orcid.org/0000-0002-7174-6382
ENADE PERDANA ISTYASTONO Magister of Pharmacy Study Program, Faculty of Pharmacy, Universitas Sanata Dharma, Yogyakarta-55282, Indonesia. Research Group of Computer-Aided Drug Design and Discovery of Bioactive Natural Products, Faculty of Pharmacy, Sanata Dharma University, Yogyakarta-55282, Indonesia

DOI:

https://doi.org/10.22159/ijap.2024v16i5.51525

Keywords:

Grape seed oil, Face oil, Adulteration, FTIR spectroscopy, Chemometrics

Abstract

Objective: This research aims to authenticate grape seed oil products using FTIR spectroscopy combined with chemometric methods.

Methods: In the initial stage, exploratory data analysis was carried out by applying the main components with the Principal Component Analysis (PCA) model. Second derivative spectra resulting from preprocessing of the original spectra are used to create multivariate Principal Component Regression (PCR) and Partial Least Squares (PLS) calibration models. The second derivative spectra of Grape Seed Oil (GO), Olive Oil (OO), and the binary mixture GO+OO are utilized to generate a sparse partial least squares-discriminant analysis (SPLS-DA) model.

Results: The PCA model was successfully obtained with visualization that depicted a total of 93.8% in the first and second dimensions. Multivariate calibration produced the best model in PLS with second derivative spectra for both GO and OO. PLS model for GO resulted the value of R_cal², R_CV², R_val², RMSEC, RMSECV, and RMSEP of 0.998, 0.992, 0.982, 0.700, 1.557, and 2.331, respectively. The SPLS-DA model was successfully built and discriminated with AUC-ROC values of 1.000, 1.000, and 0.994 for GO, OO, and GO+OO, respectively.

Conclusion: Authentication of grape seed face oil can be undertaken using FTIR spectroscopic methods and chemometric techniques, which can produce high sensitivity and specificity values.

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