Quantification of geometric isomers of citral and minor oleochemicals in Cymbopogon flexuosus (lemongrass) and Cymbopogon nardus (citronella) essential oils by ¹H qNMR method

The 1H quantitative Nuclear Magnetic Resonance (qNMR) has emerged as a powerful analytical tool due to its high sensitivity, ability to provide absolute quantification, and most importantly, its univocal structural assignment. So far, 1H qNMR has been used to quantify only the major constituents of the essential oils (EOs). Since the minor constituents of the EOs play a role in its various properties, quantification of minor constituents is essential. In this study, a 1H qNMR method is developed to quantify major and minor oleochemicals in the multifaceted Cymbopogon flexuosus (lemongrass) and Cymbopogon nardus (citronella) EOs. The 1H qNMR method is validated in terms of selectivity, linearity, robustness, and accuracy/precision using the 1H NMR spectra of citral. The use of a high-field 800 MHz NMR provides high spectral resolution, allowing discrimination between closely spaced signals. This enables in-depth analysis of the complex mixtures of essential oils, facilitating the quantification of twelve distinct components, including some at concentrations in the double-digit μg range. These results align with prior reports demonstrating the suitability of high-field NMR spectrometers for accurate quantification of analytes at low μg/mL concentrations. This method demonstrates high sensitivity, with a limit of detection (LOD) of 30.09 μg/mL and a limit of quantification (LOQ) of 90.93 μg/mL. It also proves to be highly reliable, showing a coefficient of variation (CV) of less than 1% across different acquisition and processing conditions tested. The key distinction between lemongrass and citronella oils lies in their citral content, which ranges from 72 to 74% in lemongrass oil compared to only 12–18% in citronella oil. The quantification of both major as well as minor constituents highlights the applicability of the 1H qNMR method for comprehensive profiling of EOs.