Aufsätze in referierten Fachzeitschriften
- Schmidinger, J.; Schröter, I.; Bönecke, E.; Gebbers, R.; Rühlmann, J.; Kramer, E.; Mulder, V.; Heuvelink, G.; Vogel, S. (2024): Effect of training sample size, sampling design and prediction model on soil mapping with proximal sensing data for precision liming. Precision Agriculture. : p. 1-27. Online: https://doi.org/10.1007/s11119-024-10122-3 1.0
- Mbogning, S.; Okiobe, S.; Theuerl, S.; Nwaga, D. (2024): Synergistic interplay between arbuscular mycorrhizal fungi and fern manure compost tea suppresses common tomato phytopathogens and pest attacks on-farm. Frontiers in Horticulture. : p. 1253. Online: https://doi.org/10.3389/fhort.2024.1253616 1.0
- Tapia Zapata, N.; Saha, K.; Tsoulias, N.; Zude-Sasse, M. (2024): A geometric modelling approach to estimate apple fruit size by means of LiDAR 3D point clouds. International Journal of Food Properties. (1): p. 566-583. Online: https://doi.org/10.1080/10942912.2024.2330494 1.0
- Hanike Basavegowda, D.; Schleip, I.; Mosebach, P.; Weltzien, C. (2024): Deep learning-based detection of indicator species for monitoring biodiversity in semi-natural grasslands. Environmental Science and Ecotechnology. (September): p. 100419. Online: https://doi.org/10.1016/j.ese.2024.100419 1.0
- Hobart, M.; Schirrmann, M.; Abubakari, A.; Badu-Marfo, G.; Kraatz, S.; Zare, M. (2024): Drought Monitoring and Prediction in Agriculture: Employing Earth Observation Data, Climate Scenarios and Data Driven Methods; a Case Study: Mango Orchard in Tamale, Ghana. Remote Sensing. (11): p. 1942. Online: https://www.mdpi.com/2072-4292/16/11/1942 1.0
- Vogel, S.; Emmerich, K.; Schröter, I.; Bönecke, E.; Schwanghart, W.; Rühlmann, J.; Kramer, E.; Gebbers, R. (2024): The effect of soil moisture content and soil texture on fast in situ pH measurements with two types of robust ion-selective electrodes. Soil. (1): p. 321-333. Online: https://doi.org/10.5194/soil-10-321-2024 1.0
- Shamshiri, R.; Navas, E.; Dworak, V.; Auat Cheein, F.; Weltzien, C. (2024): A modular sensing system with CANBUS communication for assisted navigation of an agricultural mobile robot. Computers and Electronics in Agriculture. (August): p. 109112. Online: https://doi.org/10.1016/j.compag.2024.109112 1.0
- Schmidinger, J.; Barkov, V.; Tavakoli, H.; Correa Reyes, J.; Ostermann, M.; Atzmüller, M.; Gebbers, R.; Vogel, S. (2024): Which and how many soil sensors are ideal to predict key soil properties: A case study with seven sensors. Geoderma. (October): p. 117017. Online: https://doi.org/10.1016/j.geoderma.2024.117017 1.0
- Maß, V.; Alirezazadeh, P.; Seidl-Schulz, J.; Leipnitz, M.; Fitzsche, E.; Ibraheem, R.; Geyer, M.; Pflanz, M.; Reim, S. (2024): Annotated image dataset of fire blight symptoms for object detection in orchards. Data in Brief. (Ocotber): p. 110826. Online: https://doi.org/10.1016/j.dib.2024.110826 1.0
- Reim, S.; Richter, S.; Leonhardt, O.; Maß, V.; Wöhner, T. (2024): YOLO-Based Phenotyping of Apple Blotch Disease (Diplocarpon coronariae) in Genetic Resources after Artificial Inoculation. Agronomy. (5): p. 1042. Online: https://doi.org/10.3390/agronomy14051042 1.0