A rapid analytical method for turmeric essential oil authentication using mid-infrared spectroscopy and chemometrics

  • Elizabeth Cobbinah
  • , Oliver B. Generalao
  • , Guoyi Ke
  • , Roberto Malaluan
  • , Arnold Lubguban
  • , Gerard G Dumancas

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Turmeric essential oil (TEO), derived from Turmeric (Curcuma longa L.) herb, is one of several natural products which has seen a rise in demand in recent years. This rising demand increases the tendency for TEO to be adulterated with inferior or less expensive alternatives, such as vegetable oils and synthetic compounds – a practice that has significant economic and organoleptic consequences. Adulteration of highly valued essential oils such as TEOs with other inexpensive vegetable oils, especially at very low concentrations poses a significant challenge as the latter has no apparent effect on the gas chromatographic profile of the adulterated TEOs. Therefore, the overall goal of this study was to develop a facile, convenient, affordable, rapid, and direct analytical method for the authentication of TEO using Fourier transform infrared spectroscopic and chemometric methods, namely, partial least squares (PLS) and principal component regression (PCR). To accomplish this goal, TEO was first adulterated with sunflower (SFO) and soybean (SBO) oil in varying concentrations. For the PLS model, the best predictive performance in both the training and testing sets was observed at 3, 2 and 4 components for TEO, SFO and SBO, respectively. Further, the PLS model was more accurate than the PCR in the prediction of TEO in the training, testing, as well as unknown sets, with minimum root mean square error values of 1.2% and maximum R2=0.999. The developed PLS model could potentially be applied for the rapid and facile detection of vegetable oil adulterants in TEO, a valuable approach to assess the authenticity of such a highly valued commodity.
Original languageEnglish
Article number106102
JournalJournal of Food Composition and Analysis
Volume129
DOIs
StatePublished - May 1 2024

Keywords

  • Chemometrics
  • Essential oils
  • Infrared spectroscopy
  • Partial least squares
  • Principal component regression
  • Turmeric

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