Exploring essential oil composition and mood effects

Despite the prevalence of aromatherapeutic practices, the molecular determinants of essential oils’ mood-altering properties lack systematic investigation. This knowledge gap was addressed through an analysis of chemical composition–mood relationships across 40 botanically diverse essential oils. Gas chromatography–mass spectrometry data from peer-reviewed sources underwent Pearson correlation analysis to identify compounds most strongly associated with calming, uplifting, or stimulating effects. Binary Logistic Regression models achieved leave-one-out cross-validated accuracies of 62.5–77.5% when predicting mood categories from chemical profiles alone. Distinct molecular signatures emerged for each mood category: geraniol and citronellol dominated uplifting associations (r = 0.414 and 0.408; p < 0.01), limonene characterized uplifting effects (r = 0.488; p < 0.01), while 1,8-cineole and menthol were distinguished by their stimulant effects (r = 0.376 and 0.360; p < 0.05). Principal Component Analysis confirmed natural chemical clustering aligned with traditional mood classifications. Additionally, a supplementary physicochemical descriptor, the molar volume to polarizability ratio, demonstrated a modest discriminatory ability between calming and non-calming oils (AUC = 0.666), complementing multivariate composition-based findings. These results suggest an organization of the olfactory architecture that is different from the conventional ‘lock-and-key’ model, demonstrating the ability of the neuronal signaling machinery to recognize and transmit analogous, converse and null chemical codes. The results also establish semi-quantitative relationships between chemical composition and aromatherapeutic mood categories and identify promising molecular features for future mechanistic and therapeutic investigation.