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.

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Hortensias (Hydrangea macrophylla L.) are well known as ornamental plants with their impressive flowers. Besides being an ornamental plant, some hortensia species contain constituents of nutritional and pharmaceutical interest. In this context, H. macrophylla subsp. serrata contains dihydroisocoumarins (DHCs), in particular hydrangenol (HG) and phyllodulcin (PD), which determine produce quality. For the successful cultivation of H. macrophylla subsp. serrata, shading may be required. The response of H. macrophylla subsp. serrata as a source for DHCs was investigated in two growing seasons using three different cultivars (‘Amagi Amacha’, ‘Oamacha’ and ‘Odoriko Amacha’) under three different light conditions: no shade (100% photosynthetic active radiation, PAR), partial (72% PAR) and full shading (36% PAR). The shading regimes had no significant effect on dihydroisocoumarin content in leaf dry matter in each single cultivar. However, ‘Amagi Amacha’ and ‘Oamacha’ yielded significantly higher PD content in comparison to ‘Odoriko Amacha’, which showed, in contrast, the significantly highest HG content. The total biomass was not significantly affected by the shading regime, but slightly higher biomass was observed under partially shaded and full-shade conditions. Hyperspectral vegetation indices (VIs) and color measurements indicate less vital plants under no shade conditions. While lighting is an important growth factor for hortensia production, DHC is cultivar dependent.