Proceedings :: International Society of Precision Agriculture

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Guimarães, C

Gonzalez Zarate, O.J

Gnyp, M

Genkin, K

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Authors

Katz, L

Genkin, K

Landau, A

Ness, Y

Crane, O

Golan, R

Rotbart, N

Nevo, E

Shapira, O

Fereres, E

Reichmann, O

Brook, A

Katz, L

Snir, N

Genkin, K

Rotbart, N

Nevo, E

Ronen, N

Reichmann, O

Rodolfo, T.A

Gonzalez Zarate, O.J

Gonzalez Aguilera, C

Fontena, V

Wagner, N.K

Teixeira, C

Lopes, J

Moura, L

Guimarães, C

Topics

Remote and Proximal Sensing of Soils and Crops

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

Agricultural Robotics, Automation, and Mechanization

Type

Oral

Year

2026

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Filter results4 paper(s) found.
1. From Pocket to Pixels: Smartphone-Based Proximal Sensing for Quantitative Monitoring of Peach Canopy Dynamics Monitoring peach canopy dynamics is essential for optimizing irrigation scheduling and promoting sustainable water management in intensively managed orchards. In well-watered systems, conventional irrigation practices often overlook spatial and temporal variability in canopy size and leaf area index (LAI), potentially leading to inefficient water use. Canopy size, as reflected by LAI—the ratio of total leaf area to ground area—serves as a key biophysical indicator linked to crop transpiration... L. Katz, K. Genkin, A. Landau, Y. Ness, O. Crane, R. Golan, N. Rotbart, E. Nevo, O. Shapira, E. Fereres, O. Reichmann, A. Brook Download paper
2. Smartphone-Based RGB Phenotyping of Hydroponic Lettuce Growth Dynamics Hydroponic lettuce production requires frequent, accurate growth assessment to optimize yield, nutrient efficiency, and crop uniformity within short, nutrient‑sensitive cycles. Existing imaging systems can deliver such precision but are often costly or technically demanding, limiting adoption in smaller hydroponic operations. Smartphone‑based imaging offers a practical alternative for scalable proximal phenotyping, yet its cross‑device quantitative accuracy and performance under operational... L. Katz, N. Snir, K. Genkin, N. Rotbart, E. Nevo, N. Ronen, O. Reichmann Download paper
3. 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 Download paper
4. 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 Download paper

Filter results4 paper(s) found.

1. From Pocket to Pixels: Smartphone-Based Proximal Sensing for Quantitative Monitoring of Peach Canopy Dynamics

Monitoring peach canopy dynamics is essential for optimizing irrigation scheduling and promoting sustainable water management in intensively managed orchards. In well-watered systems, conventional irrigation practices often overlook spatial and temporal variability in canopy size and leaf area index (LAI), potentially leading to inefficient water use. Canopy size, as reflected by LAI—the ratio of total leaf area to ground area—serves as a key biophysical indicator linked to crop transpiration... L. Katz, K. Genkin, A. Landau, Y. Ness, O. Crane, R. Golan, N. Rotbart, E. Nevo, O. Shapira, E. Fereres, O. Reichmann, A. Brook

Download paper

2. Smartphone-Based RGB Phenotyping of Hydroponic Lettuce Growth Dynamics

Hydroponic lettuce production requires frequent, accurate growth assessment to optimize yield, nutrient efficiency, and crop uniformity within short, nutrient‑sensitive cycles. Existing imaging systems can deliver such precision but are often costly or technically demanding, limiting adoption in smaller hydroponic operations. Smartphone‑based imaging offers a practical alternative for scalable proximal phenotyping, yet its cross‑device quantitative accuracy and performance under operational... L. Katz, N. Snir, K. Genkin, N. Rotbart, E. Nevo, N. Ronen, O. Reichmann

Download paper

3. 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

Download paper

4. 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

Download paper