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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
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Blog Post number 1
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portfolio
ON Cerco - Harnessing oblique and nadir observation angles to improve plant disease prediction in sugar beet.
The standard view when using drones is looking straight down (nadir). Oblique viewing angles allow adding more information that can be used for plant disease incidence and severity estimates. 
ON Cerco - Understanding multi-angular reflectance patterns in a Cercospora beticola trial.
In 2024, the IfZ is looking for a M.Sc. student to explore the diurnal variability of leaf angle in a cercospora/sugar beet variety trial. The goal is to understand the dynamics of angular leaf movement throughout multiple days and link this to weather parameters. Different sugar beet cultivars, inoculated with Cercospora beticola and healthy plants will be assessed. Eventually, the results will be used to link them to aerial reflectance data and evaluate to what extent diurnal variability in LAD in affecting spectral signals.
M.Sc. Research (Active) - Accuracy assessment for spot-spraying robots.
Teresa Starck evaluated the accuracy and practicability of spot-spraying robots in maize and sugar beet.
M.Sc. Research (Active) - Digital technologies for Virus Yellows phenotyping in sugar beet across spatial scales.
Nathan Okole is investigating whether optical sensors at close-range and from uncrewed aerial systems (UAS) can be used for phenotyping Virus Yellows in sugar beet.
B.Sc. Research (Alumni) - Can we predict the susceptibility to myrtle rust with the help of physical leaf traits?
Larissa Krey collected, and statistically associated, various - biologically relevant - plant functional traits to the pathosystem Austropuccinia psidii on Backhousia citridora.
publications
Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis
Published in Frontiers in Plant Science, 2015
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The Effect of Epidermal Structures on Leaf Spectral Signatures of Ice Plants (Aizoaceae)
Published in Remote Sensing, 2015
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Detecting myrtle rust (Austropuccinia psidii) on lemon myrtle trees using spectral signatures and machine learning
Published in Plant Pathology, 2018
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Multispectral, Aerial Disease Detection for Myrtle Rust (Austropuccinia psidii) on a Lemon Myrtle Plantation
Published in Drones, 2019
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Developing a spectral disease index for myrtle rust (Austropuccinia psidii)
Published in Plant Pathology, 2019
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Breaking down barriers between remote sensing and plant pathology
Published in Tropical Plant Pathology, 2019
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Estimating food resource availability in arid environments with Sentinel 2 satellite imagery
Published in PeerJ, 2020
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Identifying Invasive Weed Species in Alpine Vegetation Communities Based on Spectral Profiles
Published in Geomatics, 2021
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Digital plant pathology: a foundation and guide to modern agriculture
Published in Journal of Plant Diseases and Protection, 2022
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Special Issue: Digital Plant Pathology for Precision Agriculture
Published in Journal of Plant Diseases and Protection, 2022
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A Multisensor UAV Payload and Processing Pipeline for Generating Multispectral Point Clouds
Published in Remote Sensing, 2023
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Digital Technologies in Crop Production
Agricultural Sciences (M.Sc.), Georg-August-Universität Goettingen, Agricultural Sciences, 2023
In this module, students are introduced to selected digital technologies and their technical environment for use in crop production systems. In a second block of the course, the different sensors are in the foreground: environmental sensors / optical sensors such as RGB, multi- and hyperspectral technologies / 3D technologies, chlorophyll fluorescence and thermography / acoustic sensors and force measurement / remote sensing and satellites. In a third block of the lecture, practical applications are presented, some of which are already in use: Detection of the development of a crop and abiotic stress, case studies on the detection of plant diseases by means of optical sensors and on yield parameters and machine sensors with field applications (vehicle- or airborne). Applications in arable, fruit and vegetable production are considered.