Recognition of Clove (<i>Eugenia caryophyllata</i>) Oil Adulteration by Monitoring Phenolic and Antioxidative Fingerprint Markers Utilizing Online HPLC Post Column and Spectrophotometric Assays with Chemometric Analysis

This research aims to develop a reliable and versatile methodology for authenticating clove (Eugenia caryophyllata) oil (CLO). Key variables included total antioxidant capacity (TAC), total phenolic content (TPC), quantitative analyses and/or individual antioxidant capacity of fingerprint markers including eugenol (EUG) and tocopherol isomers (alpha-T, gamma-T, and delta-T) using reversed-phase liquid-chromatography (RP-HPLC) with post-column detection. A total of 28 commercial CLO samples (certified as 100% pure and other commercial samples), potential adulterants like vegetable oils (sunflower oil (SFO) and corn oil (CO)), and 14 synthetically adulterated CLO samples blended with varying proportions (ranging from 5 to 50%) of SFO and CO were analyzed. The EUG content and antioxidant capabilities of each marker were ascertained by online RP-HPLC analysis with post column detection utilizing CUPRAC (cupric reducing antioxidant capacity). EUG content in commercial CLO ranged from 1.46 to 98.06 mg g(-1), while TAC ranged between 18.54 and 748.46 mu mol g(-1) Trolox equivalents (TE), as determined by the online HPLC-CUPRAC method. Depending on the type and ratio of adulterating oils, a considerable decrease in the TAC values of virgin CLO was recorded. Classification of the commercial and synthetically adulterated CLOs (total of 42 samples) was performed using partial least square discrimination analysis (PLS-DA) and hierarchical cluster analysis (HCA). Adulteration levels above > 5% were successfully detected with 95% confidence. Thus, the proposed chemometric strategy combining selected chemical markers and TAC data demonstrated high potential for authenticating CLO. This technique provides a more focused investigation alternative for determining the authenticity and quality of commercial CLO.

Journal

FOOD ANALYTICAL METHODS

Year

2025

Volume

19

Issue

1

ISSN

1936-9751

eISSN

1936-976X

DOI

10.1007/s12161-025-02937-1

WoS UID

WOS:001618150100001