ATR-FTIR and FORS Fingerprints for Authentication of Commercial Sunflower Oils and Quantification of Their Oleic Acid
Metadatos
Mostrar el registro completo del ítemAutor
Jiménez Hernández, Guillermo; Bagur González, María Gracia; Ortega Gavilán, Fidel; García Del Moral Garrido, Luis F.; Martos, Vanessa; González Casado, AntonioEditorial
MDPI
Materia
Sunflower oil High oleic sunflower oil ATR-FTIR
Fecha
2026-02-13Referencia bibliográfica
Jiménez-Hernández, G., Bagur-González, M. G., Ortega-Gavilán, F., García del Moral, L. F., Martos, V., & González-Casado, A. (2026). ATR-FTIR and FORS Fingerprints for Authentication of Commercial Sunflower Oils and Quantification of Their Oleic Acid. Foods, 15(4), 682. https://doi.org/10.3390/foods15040682
Resumen
The composition of sunflower oil, rich in fatty acids, largely depends on the seed variety. Commercial sunflower oils are classified as low (SFO), medium (MOSFO), and high (HOSFO) oleic, distinguished by their oleic and linoleic acid content. Higher oleic acid levels enhance health benefits and oxidative stability. Due to their differing market values, ensuring the correct quality and authenticity of these oils is essential. Unsupervised chemometric methods have been applied to visualise the natural behaviour of sunflower oils, while supervised models have been used for authentication based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) fingerprints obtained from a benchtop spectrometer. Authentication of MOSFO is particularly challenging because of its wider oleic acid range (43.1–74.9%) and production via genetic modification or blending SFO/HOSFO. To address this, two multivariable PLS-R regression models were developed using ATR FT-IR and Fibre Optic Reflectance Spectroscopy (FORS) fingerprints, the latter obtained with a portable, cost-effective device. The results indicate that FORS could be used as a rapid quality control tool for on-site quantification. In contrast, ATR FT-IR is a more accurate tool for confirmation and quantification, achieving excellent results (Residual Predictive Deviation, RPD = 7.09 and Range Error Ratio, RER = 17.82).





