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Influence of Soil Characteristics on the Phytochemistry of Evergreen Ivy (<i>Hedera helix</i> L.) Leaves in Deciduous Forests

Elif Begüm YıldırımDepartment of Pharmacognosy, Faculty of Pharmacy Yeditepe University İstanbul TürkiyeGülçin ÖzerMarmara Forestry Research Institute İstanbul TürkiyeNisa Beril ŞenDepartment of Pharmacognosy, Faculty of Pharmacy Yeditepe University İstanbul TürkiyeEmrah ÖzdemirDepartment of Forest Yield and Biometry, Faculty of Forestry İstanbul University‐Cerrahpaşa İstanbul TürkiyeEnder MakineciDepartment of Soil Science and Ecology, Faculty of Forestry İstanbul University‐Cerrahpaşa İstanbul TürkiyeDurmuş ÖzdemirDepartment of Chemistry, Faculty of Science İzmir Institute of Technology İzmir TürkiyeEtil GüzelmeriçDepartment of Pharmacognosy, Faculty of Pharmacy Yeditepe University İstanbul Türkiye
Chemistry & Biodiversityjournal2025en
ABI

Аннотация

The evergreen ivy (Hedera helix L.), traditionally used to treat respiratory conditions, contains triterpene saponins, primarily hederacoside C, and various phenolic compounds. This study investigated the relationships between the chemical composition of ivy leaves and their natural growing conditions (moisture, temperature, pH, and electrical conductivity of soil). Ivy leaves were collected monthly over 1 year from oak and beech forests. Hederacoside C, rutin, chlorogenic acid (ChA), neoChA, 4,5-dicaffeoylquinic acid (DCQA), and 3,5-DCQA were analyzed by high-performance thin-layer chromatography (HPTLC) and high-performance liquid chromatography (HPLC). Soil parameter data, along with the quantitative HPLC results of ivy leaves, were first subjected to bivariate analysis, which revealed significant correlations, particularly between soil moisture, soil temperature, and the chemical composition of ivy leaves. In addition, ivy samples were classified and clustered based on seasons by principal component analysis (PCA) and hierarchical cluster analysis (HCA), regardless of their collection sites. Digitized HPTLC chromatograms were evaluated by PCA and partial least squares discriminant analysis (PLS-DA) analyses; PCA enabled the grouping of ivy leaves based on their collection sites, and PLS-DA categorized the samples by seasons. The evaluation of the relationships between the phytochemistry of ivy leaves and their natural growing conditions has been reported for the first time.

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