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| Contribution to a conference proceedings/Contribution to a book | FZJ-2025-03121 |
; ; ;
2025
The Hague
ISBN: 978-94-62614-32-1
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Please use a persistent id in citations: doi:10.17660/ActaHortic.2025.1433.6 doi:10.34734/FZJ-2025-03121
Abstract: In biogenic value creation, medicinal plants are playing an important role including the commercial cultivation to meet the growing global demand. This opens up new opportunities to improve harvest quantities through breeding, cultivation management and harvesting techniques. An important aspect is the determination of optimal harvest times, which depend on the weather conditions, the state of the plant organ with regard to the harvesting process and the content of the active ingredients, which fluctuates over time. In this study, we used the medicinal plant Arnica montana ‘Arbo’ to examine the aspect of target compound yield of helenalin, dihydrohelenalin and their esters depending on the life cycle of the flower, in order to develop methods for estimating optimal harvest time windows. A neural network was trained to classify seven stages from time-lapse images in order to track the development of each flower stage. To get typical content values, Arnica plants were grown in the field and amounts of the two target compound classes were determined for each flower type. By combining both outcomes, it was possible to calculate the time course of the total amount of active compounds and thereby determine better harvest time windows. This method is interesting also for other crops where external features can be used as a proxy for active compound concentrations.
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