Previously, different Hydrangea macrophylla ssp. serrata cultivars were investigated by untargeted LC-MS analysis. From this, a list of tentatively identified and unknown compounds that differ significantly between these cultivars was obtained. Due to the lack of reference compounds, especially for dihydro-isocoumarins, we aimed to isolate and structurally characterise these compounds from the cultivar ‘Yae-no-amacha’ using NMR and LC-MS methods. For purification and isolation, counter-current chromatography was used in combination with reversed-phase preparative HPLC as an orthogonal and enhanced purification workflow. Thirteen dihydro-isocoumarins in combination with other metabolites could be isolated and structurally identified. Particularly interesting was the clarification of dihydrostilbenoid glycosides, which were described for the first time in H. macrophylla ssp. serrata. These results will help us in further studies on the biological interpretation of our data.

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Hyperspectral data are commonly used for the fast and inexpensive quantification of plant constituent estimation and quality control as well as in research and development applications. Based on chemical analysis, different models for dihydroisocoumarins (DHCs), namely hydrangenol (HG) and phyllodulcin (PD), were built using a partial least squares regression (PLSR). While HG is common in Hydrangea macrophylla, PD only occurs in cultivars of Hydrangea macrophylla subsp. serrata, also known as ‘tea-hortensia’. PD content varies significantly over the course of the growing period. For maximizing yield, a targeted estimation of PD content is needed. Nowadays, DHC contents are determined via UPLC, a time-consuming and a destructive method. In this research article we investigated PLSR-based models for HG and PD using three different spectrometers. Two separate trials were conducted to test for model quality. Measurement conditions, namely fresh or dried leaves and black or white background, did not influence model quality. While highly accurate modeling of HG and PD for single plants was not possible, the determination of the mean content on a larger scale was successful. The results of this study show that hyperspectral modeling as a decision support for farmers is feasible and provides accurate results on a field scale.

A wide range of secondary metabolites has been described for various Hydrangea species, including the sweet-tasting phenyldihydroisocoumarin phyllodulcin, which is found in the leaves of Hydrangea macrophylla ssp. serrata. This work aims at the development and validation of an analytical workflow for comprehensive semi-polar metabolite profiling using liquid chromatography coupled with electrospray ionization ion mobility quadrupole time-of-flight mass spectrometry (UPLC-ESI-IMS-QToF-MS) to complement existing analytical studies. The unsupervised analysis of this data set demonstrates the capability of this analytical workflow to distinguish different H. macrophylla ssp. serrata cultivars. In combination with supervised analysis, a list of metabolites responsible for the differentiation of the cultivars studied has been obtained. Suspect screening of phenyldihydroisocoumarins provides comprehensive information, which could help in the search for key enzymes related to the biosynthesis of phyllodulcin.

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