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Hansen, N.P
Buana, I
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Authors
Canciani, M
Han, E
Jørgensen, U
Ikeda, Y
Hansen, N.P
Jensen, S.K
Weisbjerg, M.R
Didion, T
Moura Bueno, J.
Rech, L.F
Diniz Dalmolin, R.S
de Paula Amaral, L
Buana, I
De Araujo Pedron, F
Topics
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Predictive Modeling, Phenotyping, and Digital Tools for Decision Support
Type
Poster
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. Field-scale Prediction of Soil Organic Carbon Using Integrated Proximal Sensing and Terrain Covariates

The knowledge of soil organic carbon (SOC) is essential for climate change mitigation strategies, soil security, and management within precision agriculture scenarios in agricultural areas. The use of approaches integrating spectral and magnetic sensor data with topographic covariates has shown promise for predicting SOC along the soil profile. In this context, the study aimed to develop predictive models of SOC content at depth through the integration of proximal sensing data and topographic... J. Moura Bueno, L.F. Rech, R.S. Diniz Dalmolin, L. De Paula Amaral, I. Buana, F. De Araujo Pedron