Guava (Psidium guajava L.) leaves are increasingly processed into caffeine-free herbal teas, valued for their rich phenolic composition and cultivar-dependent sensory profile. However, no systematic study has yet resolved how cultivar identity shapes the volatile, non-volatile, and functional dimensions of the finished tea. Here, eight guava tea cultivars were profiled using a multi-platform approach combining electronic nose sensing, headspace GC–MS, electronic-tongue analysis, non-targeted and targeted LC–MS metabolomics, and physicochemical indices. The eight cultivars were described by three volatile composition patterns: (i) a monoterpene-rich group, most pronounced in ‘Yanzhi Hong’, (ii) a compositionally diverse non-monoterpene group dominated by sesquiterpene esters and alkanes, and (iii) a group with a lower abundance of most discriminant volatiles—a pattern consistent across electronic nose sensor responses and GC–MS compound-level data. Electronic-tongue profiling identified largely independent instrumental taste-response modules. Instrumental astringency showed a robust, cross-platform-supported association with cultivars enriched in flavonoid glycosides (sparse partial least squares [sPLS] Q2 = 0.733–0.900), whereas bitterness was statistically detectable but compositionally unresolved. Antioxidant (DPPH) capacity was only weakly associated with total phenolic and flavonoid contents (r = 0.188 for each), indicating that bulk phenolic indices alone did not adequately explain cultivar-level DPPH variation. Integrating these results into a candidate pathway-output framework indicated that aroma, taste, and antioxidant-related quality are shaped by partially independent metabolic axes rather than a single quality gradient. These findings provide a candidate-based, cultivar-resolved framework for guava leaf tea quality and identify candidate cultivars suited to terpene-rich, non-monoterpene, or phenolic-retention-oriented product development.
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Ma et al. (2026) studied this question.
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