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Guimarães, C
Gonzalez Zarate, O.J
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Authors
Rodolfo, T.A
Gonzalez Zarate, O.J
Gonzalez Aguilera, C
Fontena, V
Wagner, N.K
Teixeira, C
Lopes, J
Moura, L
Guimarães, C
Topics
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Agricultural Robotics, Automation, and Mechanization
Type
Oral
Year
2026
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1. An Interpretable Machine Learning Framework for Soil Nutrient Assessment Based on pH and Electrical Conductivity

Understanding how the physical and chemical properties of soil influence nutrient availability is fundamental for advancing precision agriculture, as these properties directly affect the efficiency of macro- and micronutrient absorption by plants. In recent years, the increasing availability of open agricultural datasets has created new opportunities for developing data-driven frameworks capable of supporting large-scale soil assessment and decision-making. However, the effective integration of... T.A. Rodolfo, O.J. Gonzalez Zarate, C. Gonzalez Aguilera

2. Orchestration of Missions for Coordination between Autonomous Agents in Agriculture.

Due to technological advancement in agriculture, various autonomous agents, such as drones, mobile robots, and intelligent agricultural vehicles, are being used to automate repetitive tasks and increase agricultural production. In addition, these agents, often developed by different manufacturers and endowed with different capabilities, form a highly heterogeneous environment, imposing a central challenge to be solved: the need to manage these agents so that they can act in a coordinated and effective... V. Fontena, N.K. Wagner, C. Teixeira, J. Lopes, L. Moura, C. Guimarães