Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2024
Authors
Theresa Weigl Jorunn Børve Emily Follett Ingunn Øvsthus Carl Gunnar Fossdal Hanne Larsen Siv Fagertun RembergAbstract
No abstract has been registered
Authors
Dalphy Ondine Camira HarteveldAbstract
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Authors
Dalphy Ondine Camira HarteveldAbstract
No abstract has been registered
Authors
Marco Ferretti Arthur Gessler Nathalie Cools Stefan Fleck Rossella Guerrieri Tamara Jakovljević Manuel Nicolas Tiina M. Nieminen Diana Pitar Nenad Potočić Stephan Raspe Marcus Schaub Kai Schwärzel Volkmar Timmermann Monika Vejpustková Lars Vesterdal Petteri Vanninen Peter Waldner Lothar Zimmermann Tanja GM SandersAbstract
No abstract has been registered
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Authors
Isabella BørjaAbstract
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Authors
Fernanda Leiva Florent Abdelghafour Muath K Alsheikh Nina Elisabeth Nagy Jahn Davik Aakash ChawadeAbstract
Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurately grade scab-infected potato tubers, this study introduces “ScabyNet”, an image processing approach combining color-morphology analysis with deep learning techniques. ScabyNet estimates tuber quality traits and accurately detects and quantifies CS severity levels from color images. It is presented as a standalone application with a graphical user interface comprising two main modules. One module identifies and separates tubers on images and estimates quality-related morphological features. In addition, it enables the extraction of tubers as standard tiles for the deep-learning module. The deep-learning module detects and quantifies the scab infection into five severity classes related to the relative infected area. The analysis was performed on a dataset of 7154 images of individual tiles collected from field and glasshouse experiments. Combining the two modules yields essential parameters for quality and disease inspection. The first module simplifies imaging by replacing the region proposal step of instance segmentation networks. Furthermore, the approach is an operational tool for an affordable phenotyping system that selects scab-resistant genotypes while maintaining their market standards.
Authors
Martin S. Mullett Anna R. Harris Bruno Scanu Kris Van Poucke Jared LeBoldus Elizabeth Stamm Tyler B. Bourret Petya K. Christova Jonás Oliva Miguel A. Redondo Venche Talgø Tamara Corcobado Ivan Milenković Marília Horta Jung Joan Webber Kurt Heungens Thomas JungAbstract
No abstract has been registered
Authors
Katherine Ann Gredvig Nielsen Magne Nordang Skårn Venche Talgø Martin Pettersson Inger Sundheim Fløistad Gunn Strømeng May Bente Brurberg Arne StensvandAbstract
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Authors
Mark A. Anthony Leho Tedersoo Bruno De Vos Luc Croisé Henning Meesenburg Markus Wagner Henning Andreae Frank Jacob Paweł Lech Anna Kowalska Martin Greve Genoveva Popova Beat Frey Arthur Gessler Marcus Schaub Marco Ferretti Peter Waldner Vicent Calatayud Roberto Canullo Giancarlo Papitto Aleksander Marinšek Morten Ingerslev Lars Vesterdal Pasi Rautio Helge Meissner Volkmar Timmermann Mike Dettwiler Nadine Eickenscheidt Andreas Schmitz Nina Van Tiel Thomas W. Crowther Colin AverillAbstract
No abstract has been registered