Kapitel/Beitrag aus dem Buch: Beyerer J. & Längle T. 2021. OCM 2021 – 5th International Conference on Optical Characterization of Materials, March 17th – 18th, 2021, Karlsruhe, Germany : Conference Proceedings.
Plants containing pyrrolizidine alkaloids (PA) are unwanted
contaminants in consumer products such as herbal tea
due to their toxicity to humans. The detection of these plants or
their components using hyperspectral imaging was investigated,
with focus on application in sensor-based sorting. For this, 431
hyperspectral images of leafs from three common herbs (peppermint,
lemon balm, stinging nettle) and the poisonous common
groundsel were acquired. By using a convolutional neural network,
a mean F1 score of 0.89 was obtained for the classification
of all four plant products based on the individual spectra. To
validate the neural network, significant wavelengths were determined
and visualized in an attribution map.
Krause, J et al. 2021. Detection of pyrrolizidine alkaloid containingherbs using hyperspectral imaging in theshort-wave infrared. In: Beyerer J. & Längle T (eds.), OCM 2021 – 5th International Conference on Optical Characterization of Materials, March 17th – 18th, 2021, Karlsruhe, Germany : Conference Proceedings. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000128686-5
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Veröffentlicht am 17. März 2021