Krähmer, Andrea

Maier, Georg

Schulte, Henning

Tron, Nanina

English

JKI Open Journal Systems (Julius Kühn-Institut)

12th Young Scientists Meeting 2019, Kleinmachnow, Germany, November 6-8 Tron et al. NIRS-based detection of pyrrolizidine alkaloid containing weeds in crop plants after harvest – PA-NIRSort Nanina Tron1, Georg Maier2, Henning Schulte2 and Andrea Krähmer1 1 Julius Kühn Institute, Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Berlin 2 Fraunhofer-Institut for Optronics, System Technologies und Image Exploitation (IOSB), Karlsruhe E-mail of corresponding author: nanina.tron@julius-kuehn.deThe general objective of the project is the de-velopment of an efficient sorting system based on hyperspectral near-infrared spec-troscopy (NIR) for the detection and separa-tion of impurities by pyrrolizidine alkaloid (PA)-containing plant derived contamina-tions in cultural plants, e.g. medicinal and ar-omatic plants. PAs are liver-toxic secondary metabolites in plant defense and are known for causing seneciose in grazing animals. By now, the German Federal Institute for Drugs and Medical Devices (BfArM) has published strict PA maximum contents for phytophar-maceutical products as eg. Teas which can be contaminated with PA-containing weeds such as various types of ragwort, groundsels, common viper's head, common comfrey, common dog's tongue, water-east or borage and thus potentially endanger consumers. Due to these strict limits, four to five PA-con-taining plants of the species Senecio vulgaris may be sufficient to destroy one ton of me-dicinal drug. The planned process will analyze fresh and dried plant material on a flat conveyer using hyperspectral NIR spectroscopy to detect im-purities in the crop. After identification, con-taminants should be removed by a sorting technique, e.g. using compressed air pulses.Similar systems have already been estab-lished in plastic waste sorting and quality control, for example for grapes. The aim is to achieve a high throughput of up to five tons of harvested crop within three to four hours. With such an automated sorting technology, the health risks posed by PA-contaminated medicinal plant products could be reduced ecologically and economically efficient for cultivation and processing of medicinal plants. This would also mean safeguarding high-quality and competitive plant derived drug production in Germany. First results show that a classification of tar-get plant species and contaminating Senecio using NIR spectroscopy is generally possible. In order to be able to carry out such image analyses in real time, the amount of data to be processed will be reduced to the decisive factors by means of multifactorial data anal-ysis. This project is supported by funds of the Fed-eral Ministry of Food and Agriculture (BMEL) by decision of the German Bundestag and managed by the Agency for renewable re-sources (FNR) under the program “Renewa-ble Resources” with project number: 22013216. 50 Berichte aus dem Julius Kühn-Insitut 206

NIRS-based detection of pyrrolizidine alkaloid containing weeds in crop plants after harvest – PA-NIRSort

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NIRS-based detection of pyrrolizidine alkaloid containing weeds in crop plants after harvest – PA-NIRSort

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