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Jensen, S.K
Bodanese, M
Oliveira, M.F
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Authors
Canciani, M
Han, E
Jørgensen, U
Ikeda, Y
Hansen, N.P
Jensen, S.K
Weisbjerg, M.R
Didion, T
Silva, V.S
Silva, E.S
Silva, D.O
Oliveira, M.F
Tavares, A.C
Negrini, R.P
Mendes, L.A
Topics
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Type
Poster
Oral
Year
2026
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1. UAV-Based Multispectral Modelling of Biomass and Crude Protein Yield for Green Biorefinery Applications

In animal production systems, protein demand is steadily increasing due to global population growth. This rising demand has highlighted the need to identify alternative and sustainable protein sources. Green biorefinery systems can efficiently extract protein from plant biomass. Previous studies confirmed that perennial grass crops such as Perennial Ryegrass, Festulolium, and Tall Fescue can produce high-quality biomass suitable for protein extraction. An estimation model of biomass yield and... M. Canciani, E. Han, U. Jørgensen, Y. Ikeda, N.P. Hansen, S.K. Jensen, M.R. Weisbjerg, T. Didion

2. Satellite Embedding-Based Corn Yield Prediction Using AutoML and Explainable AI

Accurate, spatially explicit yield mapping underpins many precision agriculture decisions (e.g., variable-rate inputs and zone management), yet reliable yield monitor data are not always available and can be difficult to standardize across operations. Satellite-based yield models are often built from hand-crafted vegetation indices or phenology metrics, which may limit transferability across fields and years. Here, we evaluated a pixel-level corn yield prediction workflow that uses Satellite Embedding... V.S. Silva, E.S. Silva, D.O. Silva, M.F. Oliveira, A.C. Tavares, R.P. Negrini, L.A. Mendes