Proceedings :: International Society of Precision Agriculture

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Ribeiro, S

Ramos, L

Rodrigues, M

Ruscito, G.N

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Authors

Souza, E.G

Bazzi, C

Hachisuca, A

Sobjak, R

Gavioli, A

Betzek, N

Schenatto, K

Mercante, E

Rodrigues, M

Moreira, W

Aikes Junior, J

Souza, E.G

Bazzi, C

Sobjak, R

Hachisuca, A

Gavioli, A

Betzek, N

Schenatto, K

Moreira, W

Mercante, E

Rodrigues, M

Hachisuca, A

Souza, E.G

Mercante, E

Sobjak, R

Ganascini, D

Abdala, M

Mendes, I

Bazzi, C

Rodrigues, M

Luiz Panini, R

Tamara, A.R

Franco, G.M

de Oliveira, V.C

Lemos, H.R

Nishikawa, M

Forti, P.R

Biagi, M

Dudek, L.F

Hauschild, M.C

Ruscito, G.N

da Silva, M.P

Claro, E

de Souza, Z.M

Carrillo Montoya, K

De Guzman, C

Burgos, N

Ramos, L

Gyanwali, P

Uzoetoh, U

McCarty, D

Reddy Kalluri, R

Mason, D

CELY BONILLA, E

Bazzi, C.L

Sobjak, R

Schenatto, K

Torres Avila, E

Rodrigues, M

Spricigo, S

Topics

Decision Support Systems

Agricultural Robotics, Automation, and Mechanization

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Remote and Proximal Sensing of Soils and Crops

Type

Poster

Oral

Year

2022

2026

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Authors

Filter results6 paper(s) found.
1. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira Download paper
2. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes Junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues Download paper
3. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues Download paper
4. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative Approaches Weed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. This... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza Download paper
5. Temporal NDRE Dynamics from UAS Imagery to Characterize Rice Drought Response Characterizing drought resilience in rice remains challenging under increasing climate variability. Drought tolerance is a complex and dynamic trait that is difficult to quantify using traditional field phenotyping approaches, particularly when responses vary with time. High-throughput temporal phenotyping with unmanned aircraft systems (UAS) enables monitoring of canopy reflectance dynamics associated with water stress across the growing season. This study evaluated whether temporal...
6. Leaf Nutrient Estimation in Soybean from Multispectral and Multitemporal Information Using UAV and Machine Learning Precision agriculture, through remote sensing with Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence, offers solutions for monitoring crop growth and development, supporting decision-making aimed at resource optimization and agricultural sustainability. This study evaluated the feasibility of using multispectral information captured by UAVs at different phenological stages (V6, V8, and R2) to estimate leaf nutrients (N, P, K, Ca, Mg, Cu, Zn, and Mn) in soybean crops as an alternative... E. Cely Bonilla, C.L. Bazzi, R. Sobjak, K. Schenatto, E. Torres Avila, M. Rodrigues, S. Spricigo Download paper

Filter results6 paper(s) found.

1. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

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2. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes Junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

Download paper

3. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

Download paper

4. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative Approaches

Weed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. This... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza

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5. Temporal NDRE Dynamics from UAS Imagery to Characterize Rice Drought Response

Characterizing drought resilience in rice remains challenging under increasing climate variability. Drought tolerance is a complex and dynamic trait that is difficult to quantify using traditional field phenotyping approaches, particularly when responses vary with time. High-throughput temporal phenotyping with unmanned aircraft systems (UAS) enables monitoring of canopy reflectance dynamics associated with water stress across the growing season. This study evaluated whether temporal...

6. Leaf Nutrient Estimation in Soybean from Multispectral and Multitemporal Information Using UAV and Machine Learning

Precision agriculture, through remote sensing with Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence, offers solutions for monitoring crop growth and development, supporting decision-making aimed at resource optimization and agricultural sustainability. This study evaluated the feasibility of using multispectral information captured by UAVs at different phenological stages (V6, V8, and R2) to estimate leaf nutrients (N, P, K, Ca, Mg, Cu, Zn, and Mn) in soybean crops as an alternative... E. Cely Bonilla, C.L. Bazzi, R. Sobjak, K. Schenatto, E. Torres Avila, M. Rodrigues, S. Spricigo

Download paper