Artificial intelligence enables new ways in seed quality testing

Dr. Marcus Jansen (Lemnatec GmbH)

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Seed assessments at various levels traditionally rely on visual inspections, but optical technologies increasingly take over rating tasks. While seed counting with computer vision is already established, optical inspections of germination processes, seedling quality, or seed purity are gaining importance. The implication of machine learning enables training the image processing algorithms in a way that the dedicatedly recognize features that are important for specific ratings. Thereby, it becomes possible to move automatic imaging-based inspection of seeds and seedlings closer to the demand of the rating experts. Beyond application-specific image processing, key advantages of such methods are consistent documentation of the samples by storing the original images and measuring options for all recognized items. These measuring options enable determining the size of each and every detected seed, seedling, root, shoot, or leaf. They can be measured for a range of parameters, including length, width, area, or information on colors and morphology. Many of these data give added value compared to visual scoring. Moreover, artificial intelligence enables recognizing sample- or user-specific quality traits in seeds and seedlings. Thereby, algorithms can be trained to discriminate between normal and non-normal seeds and seedlings. All imaging can be combined with automation technology that increases the throughput of samples. Thus, imaging and image processing is applicable at all scales from small labs to large factories.

Speaker Information

Dr. Marcus Jansen (Lemnatec GmbH)

Dr. Marcus Jansen is a scientist at the company LemnaTec GmbH in Aachen, Germany. He is experienced in plant biology and phenotyping and works to facilitate the use of sensing technologies for phenotyping measurements with plants and beyond.
He has received his doctorate from RWTH Aachen in 2007. During the doctoral studies he worked on plant pathology and investigated a plant-fungus interaction at phenotypic, biochemical, and molecular level. Between 2007 and 2014 he worked at Forschungszentrum Jülich, Germany in developing and applying methods for digital phenotyping in basic research as well as in plant breeding research. Since 2014 he works for LemnaTec which is part of the Nynomic Group since 2019. He is responsible for biological applications of phenotyping technologies, understanding biological requirements of customers and for marketing communications.

Marcus Jansen on Google Scholar