A5040827471- Remote Sensing in Agriculture
- Smart Agriculture and AI
- Leaf Properties and Growth Measurement
- Spectroscopy and Chemometric Analyses
- Remote Sensing and LiDAR Applications
- Greenhouse Technology and Climate Control
- Plant Pathogens and Fungal Diseases
- 3D Surveying and Cultural Heritage
- Plant Disease Resistance and Genetics
- Plant Pathogens and Resistance
- Horticultural and Viticultural Research
- Essential Oils and Antimicrobial Activity
- Wheat and Barley Genetics and Pathology
- Big Data and Business Intelligence
- Plant Disease Management Techniques
- Agriculture, Soil, Plant Science
- FinTech, Crowdfunding, Digital Finance
- Banana Cultivation and Research
- Cell Image Analysis Techniques
- Date Palm Research Studies
- Image and Object Detection Techniques
- Genetics and Plant Breeding
- Water Quality Monitoring and Analysis
- Advanced Numerical Analysis Techniques
- Soil Geostatistics and Mapping
Institute of Sugar Beet
2024
Institut für Zuckerrübenforschung
2019-2024
University of Göttingen
2021
University of Bonn
2013-2020
Over the last few years, 3D imaging of plant geometry has become significant importance for phenotyping and breeding. Several sensing techniques, like reconstruction from multiple images laser scanning, are methods choice in different research projects. The use RGBcameras requires a amount post-processing, whereas this context, scanning needs huge investment costs. aim present study is comparison between two current low-cost systems high precision close-up scanner as reference method. As...
Laserscanning recently has become a powerful and common method for plant parameterization growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution speed result in multitude of points that require processing analysis. The primary objective this research been to establish reliable fast technique throughput phenotyping using differentiation, segmentation classification single plants by fully automated system. In report, we introduce point...
Accessing a plant’s 3D geometry has become of significant importance for phenotyping during the last few years. Close-up laser scanning is an established method to acquire plant shapes in real time with high detail, but it stationary and investment costs. reconstruction from images using structure motion (SfM) multi-view stereo (MVS) flexible cost-effective method, requires post-processing procedures. The aim this study evaluate potential measuring accuracy SfM- MVS-based photogrammetric...
The development of plant diseases is associated with biophysical and biochemical changes in host plants. Various sensor methods have been used assessed as alternative diagnostic tools under greenhouse conditions. Changes photosynthetic activity, spectral reflectance transpiration rate diseased leaves, inoculated Cucumber mosaic virus ( CMV ), green mottle CGMMV the powdery mildew fungus Sphaerotheca fuliginea were by use non‐invasive sensors during disease development. Spatiotemporal leaf...
Understanding the growth and development of individual plants is central importance in modern agriculture, crop breeding, science. To this end, using 3D data for plant analysis has gained attention over last years. High-resolution point clouds offer potential to derive a variety traits, such as height, biomass, well number size relevant organs. Periodically scanning even allows performing spatio-temporal analysis. However, highly accurate from recorded at different stages are rare, acquiring...
Since the launch of "Generative Pre-trained Transformer 3.5", ChatGPT by Open, artificial intelligence (AI) has been a main discussion topic in public. Especially large language models (LLM), so called "intelligent" chatbots, and possibility to automatically generate highly professional technical texts get high attention. Companies, as well researchers, are evaluating possible applications how such powerful LLM can be integrated into daily work bring benefits, improve their business or make...
Due to the rise of laser scanning 3D geometry plant architecture is easy acquire. Nevertheless, an automated interpretation and, finally, segmentation into functional groups are still difficult achieve. Two barley plants were scanned in a time course, and organs separated by applying histogram-based classification algorithm. The leaf represented meshing algorithms, while stem parameterized least-squares cylinder approximation. We introduced surface feature histograms with accuracy 96% for...
Plant organ segmentation from 3D point clouds is a relevant task for plant phenotyping and growth observation. Automated solutions are required to increase the efficiency of recent high-throughput pipelines. However, geometrical properties vary with time, among observation scales different types. The main objective present research develop fully automated, fast reliable data driven approach segmentation.The automated organs using unsupervised, clustering methods crucial in cases where goal...
Abstract Background This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing breeding and improving crop production. Traditionally, reference data phenotyping rely on invasive methods. Recent advancements 3D sensing technologies offer possibility to collect parameters that cannot be referenced by manual measurements. work focuses evaluating a printed sugar beet model as tool. Results Fused deposition modeling has...
Previous plant phenotyping studies have focused on the visible (VIS, 400–700 nm), near-infrared (NIR, 700–1000 nm) and short-wave infrared (SWIR, 1000–2500 range. The ultraviolet range (UV, 200–380 has not yet been used in even though a number of molecules like flavones phenol feature absorption maxima this In study an imaging UV line scanner 250–430 nm is introduced to investigate crop plants for phenotyping. Observing UV-range can provide information about important changes substances. To...
Disease incidence (DI) and metrics of disease severity are relevant parameters for decision making in plant protection breeding. To develop automated sensor-based routines, a sugar beet variety trial was inoculated with Cercospora beticola monitored multispectral camera system mounted to an unmanned aerial vehicle (UAV) over the vegetation period. A pipeline based on machine learning methods established image data analysis extraction disease-relevant parameters. Features digital surface...
Laser scanning is a non-invasive method for collecting and parameterizing 3D data of well reflecting objects. These systems have been used imaging plant growth structure analysis. A prerequisite that the recorded signals originate from true surface. In this paper we studied effects species, leaf chlorophyll content sensor settings on suitability accuracy commercial 660 nm active laser triangulation device. We found surface images Ficus benjamina leaves were inaccurate at low concentrations...
Abstract Photonics technologies play a crucial role in driving technological advancements within the agrifood industry, aiming to deliver sustainable food and agriculture, offering healthy, nutritious safe for all of us. Particularly, optical sensors imaging systems, together with machine-learning processing advanced lighting, pivotal monitoring crop soil health unprecedented precision, while safeguarding supply chain. This roadmap aims provide an overview state-of-the-art photonics...
Abstract In recent studies, the potential of hyperspectral sensors for analysis plant–pathogen interactions was expanded to ultraviolet range (UV; 200–380 nm) monitor stress processes in plants. A imaging set‐up established highlight influence early on secondary plant metabolites. this study, three different barley lines inoculated with Blumeria graminis f. sp. hordei (Bgh, powdery mildew) were investigated. One susceptible genotype (cv. Ingrid, wild type) and two resistant genotypes (Pallas...
Fungal infections trigger defense or signaling responses in plants, leading to various changes plant metabolites. The metabolites, for example chlorophyll flavonoids, have long been detectable using time-consuming destructive analytical methods including high-performance liquid chromatography photometric determination. Recent phenotyping studies revealed that hyperspectral imaging (HSI) the UV range can be used link spectral with To compare established new nondestructive measurements,...
The characterization of plant disease symptoms by hyperspectral imaging is often limited the missing ability to investigate early, still invisible states. Automatically tracing symptom position on leaf back in time could be a promising approach overcome this limitation. Therefore we present method spatially reference series close range images. Based points, robust presented derive suitable transformation model for each observation within experiment. A non-linear 2D polynomial has been...
Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing root rot, has already affected more than 25% of area under kiwifruit cultivation Italy. Diseased plants are characterised by severe decay fine roots and sudden wilting canopy, which is only visible season’s period heat (July–August). The swiftness symptom appearance prevents correct timing positioning for sampling disease, therefore barrier to aetiological studies. aim this study test...