Journal article

Publication year: 2020

Journal: Plant Phenomics

Volume number: 2020

ISSN: 2643-6515

Open access status: Gold

DOI Link: https://doi.org/10.34133/2020/5839856

Publisher: American Association for the Advancement of Science

Abstract: 
Managing plant diseases is increasingly difficult due to reasons such as intensifying the field production, climatic change-driven expansion of pests, redraw and loss of effectiveness of pesticides, rapid breakdown of the disease resistance in the field, and other factors. The substantial progress in genomics of both plants and pathogens, achieved in the last decades, has the potential to counteract this negative trend, however, only when the genomic data is supported by relevant phenotypic data that allows linking the genomic information to specific traits. We have developed a set of methods and equipment and combined them into a "Macrophenomics facility." The pipeline has been optimized for the quantification of powdery mildew infection symptoms on wheat and barley, but it can be adapted to other diseases and host plants. The Macrophenomics pipeline scores the visible powdery mildew disease symptoms, typically 5-7 days after inoculation (dai), in a highly automated manner. The system can precisely and reproducibly quantify the percentage of the infected leaf area with a theoretical throughput of up to 10000 individual samples per day, making it appropriate for phenotyping of large germplasm collections and crossing populations.

Harvard Citation style: Lück, S., Strickert, M., Lorbeer, M., Melchert, F., Backhaus, A., Kilias, D., et al. (2020) "Macrobot": An Automated Segmentation-Based System for Powdery Mildew Disease Quantification, Plant Phenomics, 2020, Article 5839856. https://doi.org/10.34133/2020/5839856

APA Citation style: Lück, S., Strickert, M., Lorbeer, M., Melchert, F., Backhaus, A., Kilias, D., Seiffert, U., & Douchkov, D. (2020). "Macrobot": An Automated Segmentation-Based System for Powdery Mildew Disease Quantification. Plant Phenomics. 2020, Article 5839856. https://doi.org/10.34133/2020/5839856