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Multi-omics insights into Citrus essential oils: linking biosynthesis, molecular mechanisms, and applications in food, health, and agriculture

Year: 2026

Type: article

Abstract: Citrus essential oils (CEOs) are complex mixtures of volatile terpenoids with potential applications in food preservation, health-related products, and sustainable agriculture. However, variations in chemical composition, physicochemical instability, and limited mechanistic evidence constrain their standardization and practical utilization. This review critically examines CEO biosynthesis and applications from a multi-omics perspective, focusing on essential oils derived from species of the genus Citrus. Genomic and transcriptomic studies have identified terpene synthase genes and regulatory networks associated with secretory-cavity development and volatile production, whereas metabolomic analyses have revealed species-, tissue-, developmental-, and environment-dependent variations in CEO composition. Structural and functional studies provide complementary insights into enzyme specificity, although direct proteomic evidence in Citrus remains limited. Available integrative studies predominantly combine transcriptomic and metabolomic data, while comprehensive connections among genomic variation, transcripts, proteins, metabolites, and phenotypes remain insufficiently validated. Machine learning approaches have shown potential for authentication, adulteration detection, chemical composition prediction, and composition–activity modeling, but their reliability is restricted by heterogeneous datasets, overfitting, limited interpretability, and insufficient external validation. Nanoemulsion, encapsulation, and controlled-release systems can improve CEO dispersion, stability, and persistence, although their performance depends strongly on formulation properties and application matrices. Further translation requires attention to sensory effects, toxicity, regulatory compliance, standardization, scalability, and economic feasibility. Future research should prioritize matched multi-omics datasets, quantitative proteomics, standardized analytical and metadata protocols, explainable computational models, and experimental validation to support reliable and scalable CEO applications in food, health, and agriculture.

Source: Cogent Food & Agriculture

DOI: 10.1080/23311932.2026.2745309