guest ::
| Home > Publications database > AI-supported optimization of the harvest time of Arnica montana |
| Home > Publications database > AI-supported optimization of the harvest time of Arnica montana |
| Poster (After Call) | FZJ-2025-03821 |
; ;
2025
Abstract: Arnica montana is an economically important medicinal plant whose extracts, containing the active ingredients helenalin and dihydrohelenalin, are used as raw materials in the pharmaceutical industry due to their various properties. However, the asynchronous flower development of Arnica montana poses a major challenge for determining the optimal harvest time in controlled cultivation, as the active ingredient content and harvestability depend heavily on the phenological stage of the flowers. To solve this problem, a methodological approach was developed that uses image-based monitoring together with a neural network to classify seven defined flower stages in a field-suitable and non-invasive manner. This enables quantitative recording of the stage distribution in the plant population over time. With known concentrations of the target compounds helenalin and dihydrohelenalin for each characteristic stage it is possible to estimate the temporal progression of the potential total active ingredient yield of a crop. The results enable a well-founded determination of the harvest window, taking into account active ingredient accumulation and decreasing harvest efficiency. The presented method has transfer potential to other medicinal plants where morphological characteristics can be used as proxies for ingredient concentrations.
|
The record appears in these collections: |