Unsere Publikationen

Publikationen

• Dharejo, M.; Minogue, L.; Kabelitz, T.; Amon, T.; Kashongwe, O.; Doherr, M. (2025): Time series data analysis to predict the status of mastitis in dairy cows by applying machine learning models to automated milking systems data. Preventive Veterinary Medicine. (242): p. 10675. Online: https://doi.org/10.1016/j.prevetmed.2025.106575 1.0
• Aghsaei, H.; Darvishi, A.; Yousefi, M.; Schirrmann, M.; Fohrer, N.; Wagner, P. (2025): Quantifying the Impact of Land Use/Land Cover Change Scenarios on Water-Related Ecosystem Services. Water Resources Management. : p. 1-25. Online: https://doi.org/10.1007/s11269-025-04244-0 1.0
• Vogel, S.; Gebbers, M.; Schröter, I.; Schwanghart, W.; Bönecke, E.; Rühlmann, J.; Kramer, E.; Gebbers, R. (2025): Towards site-independent calibration of in situ soil pH sensor data: Relevance of spatial and temporal proximity, sample size and data spread for calibration model performance. Geoderma. (April 2025): p. 117261. Online: https://www.sciencedirect.com/science/article/pii/S0016706125000990 1.0
• Matavel, C.; Meyer-Aurich, A.; Piepho, H. (2025): Bayesian-optimized experimental designs for estimating the economic optimum nitrogen rate: a model-averaging approach. Agronomy Journal. (3): p. 0. Online: https://doi.org/10.1002/agj2.70087 1.0
• Hafner, S.; Pedersen, J.; Fuß, R.; Nørlem Kamp, J.; Frederik Rask, D.; Amon, B.; Pacholski, A.; Adamsen, A.; Sommer, S. (2025): Improved tools for estimation of ammonia emission from field-applied animal slurry: refinement of the ALFAM2 model and database. Atmospheric Environment. (January): p. 120910. Online: https://doi.org/10.1016/j.atmosenv.2024.120910 1.0
• Hobart, M.; Pflanz, M.; Tsoulias, N.; Weltzien, C.; Kopetzky, M.; Schirrmann, M. (2025): Fruit Detection and Yield Mass Estimation from a UAV Based RGB Dense Cloud for an Apple Orchard. Drones. (1): p. 60. Online: https://doi.org/10.3390/drones9010060 1.0
• Akhtari, H.; Navid, H.; Karimi, H.; Dammer, K. (2025): Deep learning-based object detection model for location and recognition of weeds in cereal fields using colour imagery. Crop & Pasture Science. (4): p. 24243. Online: https://doi.org/10.1071/CP24243 1.0
• Epper, C.; Zavattaro, L.; Velthof, G.; Janke, D.; Dragoni, F.; Diaz de Otálora Aguirre, X.; Amon, B.; Gilgen, A.; Cavalli, D.; Bretscher, D.; Bischoff, W.; Bechini, L.; Argento, F.; Amon, B.; Ammann, C.; Mayer, J. (2025): Optimizing nitrogen use efficiency in European livestock systems: From feed to plant growth. Advances in Agronomy. (191): p. 273-358. Online: https://doi.org/10.1016/bs.agron.2025.01.003 1.0
• Schroedter, L.; Schneider, R.; Venus, J. (2025): Scale-up study on fermentative succinic acid production from wheat straw following a cascading biorefinery approach. Industrial Crops & Products. (October 2025): p. 1-10. Online: https://doi.org/10.1016/j.indcrop.2025.121372 1.0
• Umar, W.; Vandenbussche, C.; Dinuccio, E.; Hongmin, D.; Amon, B. (2025): Acidification of slurry in housing and during storage to reduce the NH3 and GHG emissions- Recent advancements and future perspectives. Waste Management. (July): p. 114856. Online: https://doi.org/10.1016/j.wasman.2025.114856 1.0