Detection of pyrrolizine alkaloids (PA) in plants – sorting of PA-contaminated medicinal plant products

Pyrrolizindine alkaloids (PAs) are secondary plant substances that are toxic to the liver and serve to protect plants from predators. In recent years, PAs have increasingly come to the fore, as they have been used as an unwanted by-product in organic and children's teas in particular, leading to sometimes very high alkaloid contamination. This has led to stricter PA limit values, which mean that under certain circumstances four to five PA-forming plants per hectare of cultivated area are sufficient to endanger the marketability of a ton of medicinal drug. Since the required close and regular field control and mechanical weed removal is hardly feasible from an economic point of view, quality control after harvesting to remove potential PA weeds is of particular importance.

The aim of the joint project of the Fraunhofer IOSB and the Julius Kühn Institute Berlin (Institute for Ecological Chemistry, Plant Analysis and Stock Protection), which is funded by the Agency for Renewable Resources, is to develop a powerful detection method based on hyperspectral near-infrared spectroscopy to identify contamination by PA-containing plant parts in the harvested material of medicinal and aromatic plants. Initial tests have shown that it is possible to classify plant species using NIR spectroscopy. The realisation of the method for an optical bulk sorting system should enable the separation of these weeds. For this purpose, a prototype, which carries out the real-time cleaning of harvest batches, is being developed. In this way, the health risks posed by PA-contaminated medicinal plant products for growers and processors of medicinal plants could be reduced in an ecologically and economically efficient manner.

Colour and hyperspectral image of a composite sample

Colour image of a sample consisting of the three target cultures and two PA herbs. Right: False colour image based on a pixelwise principal component analysis with clustering by target (green) and weed (blue-green) cultures.

© Fraunhofer IOSB

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