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Leme, P.M
Pereira da Silva, S.D
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Authors
Amaral, L.D
Pereira da Silva, S.D
Fantinel, R.A
Richter, V
, N
Melo, M.D
Paiva, C.M
Oliveira, A.L
Maciel, F.N
Siqueira , G.C
Borges , M.R
Furtado, G.S
Leme, P.M
Topics
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Drivers and Barriers to Adoption of Precision and Digital Technologies
Type
Poster
Oral
Year
2026
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1. Evaluation of Convolutional Neural Network Architectures for Stress Detection in Eucalyptus saligna Using Multispectral UAV Imagery

Root malformation disorder (RMD) is a significant abiotic condition that impairs water and nutrient uptake in Eucalyptus saligna, leading to physiological stress and reduced stand uniformity. Early detection in commercial plantations is hampered by the extensive spatial scale and logistical limitations of manual field inspections. In this context, the present study evaluated the performance of three convolutional neural network (CNN) architectures, U-Net, U-Net++, and Attention U-Net, in detecting... L.D. Amaral, S.D. Pereira Da Silva, R.A. Fantinel, V. Richter, N.

2. Digital Agriculture in Dairy Farming: Connectivity Diagnosis and Barriers to Technology Adoption in an Agrotechnological District

The integration of digital tools and communication systems has underpinned a profound transformation in global production chains, aiming to optimize farm operations through technological innovation. Within this context, the present study forms part of the Semear Digital project, coordinated by Embrapa, and is grounded in the premise that digital inclusion constitutes an indispensable strategy for the sustainability and competitiveness of contemporary dairy farming. The primary objective... M.D. Melo, C.M. Paiva, A.L. Oliveira, F.N. Maciel, G.C. Siqueira , M.R. Borges , G.S. Furtado, P.M. Leme