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Furlan Maggi, M

Figueiredo, G

Figueirôa , E.D

FARIAS DO NASCIMENTO, J

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Authors

Fonseca, A

dos Anjos, J.F

da Silva, E.F

Moura, G.B

Figueirôa , E.D

Coelho, G.P

de Andrade, J.P

Lopes, E

Bezerra, A.C

Fonseca, A

Figueirôa , E.D

Coelho, G.P

de Andrade, J.P

Lopes, E

Ribeiro, A.D

Fonseca, A

da Silva, E.F

Bezerra, A.C

Moura, G.B

dos Anjos, J.F

Figueirôa , E.D

Coelho, G.P

de Andrade, J.P

Lopes, E

Silva, J.I

Torres Avila, E

Bazzi, C.L

Moro Lumertz, S

CELY BONILLA, E

Furlan Maggi, M

Medeiros, T.A

Perez, D

Schenatto, K

Sobjak, R

Chaves, C

Quicaña, A.

Chimello, L

Hermes, M

Andreoli, A

Albuquerque, M

Figueiredo, G

DE SOUZA Santos, R

HINES PORPINO SANTOS, E

FREITAS DO NASCIMENTO, J

FARIAS DO NASCIMENTO, J

GOMES MESQUITA, D

FREITAS DA SILVA, T

SILVA CAVALHEIRO, G

Topics

Decision Support Systems, Cloud Platforms, and Open Data Solutions

Remote and Proximal Sensing of Soils and Crops

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

Digital Solutions for Soil Health, Water Quality, and Conservation Practices

Site-Specific Nutrient, Lime and Seed Management

Type

Poster

Oral

Year

2026

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Authors

Filter results6 paper(s) found.
1. Influence of Meteorological Variables on Bean Yield in the Semi-Arid Region: A Data-Driven Approach for Agricultural Decision Support Common bean is a strategic crop for the Brazilian semi-arid region, predominantly cultivated under rainfed systems that are highly dependent on climate variability. In regions characterized by irregular rainfall patterns, high temperatures, and extreme weather events, incorporating temporal analyses based on meteorological data becomes essential for evidence-based agricultural planning. Within the context of precision agriculture, the integration of historical climate series and productivity indicators... A. Fonseca, J.F. Dos Anjos, E.F. Da Silva, G.B. Moura, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.C. Bezerra Download paper
2. Development of an IoT Platform for Soil and Climate Monitoring in Irrigated Fruit Production in the Semi-Arid Region of Pernambuco Irrigated fruit production in the São Francisco hinterland, led by the Petrolina production hub, reached US$ 294 million in exports in 2023, consolidating mango and grape crops as strategic pillars of Pernambuco’s economy and of the Brazilian semi-arid region. This production system is dependent on irrigation due to irregular rainfall distribution, high evaporative demand, and recurrent drought conditions. Despite its international competitiveness and technological advances in irrigation... A. Fonseca, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.D. Ribeiro Download paper
3. Nonlinear Modeling of Vegetation Response to Rainfall Variability in the Brazilian Semi-Arid Region Using Sentinel-2 and CHIRPS Data High climate variability in the Brazilian semi-arid region poses significant challenges to agriculture and the sustainable management of Caatinga ecosystems, requiring monitoring tools capable of anticipating vegetation responses to rainfall fluctuations. However, the spectral response of vegetation to precipitation does not always follow linear patterns and may reflect ecohydrological thresholds and water saturation effects. Sentinel-2 data were used to derive the Soil Adjusted Vegetation Index... A. Fonseca, E.F. Da Silva, A.C. Bezerra, G.B. Moura, J.F. Dos Anjos, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, J.I. Silva Download paper
4. Automated Detection of Melons (Cucumis melo L.) via Multispectral UAV and Deep Learning in Honduras Accurate agricultural production estimation is vital for the logistical and financial efficiency of agribusiness. This study proposes an automated melon detection pipeline using a multispectral Unmanned Aerial Vehicle (UAV) and deep learning architectures. The experiment was conducted in Apacilagua, Honduras, during the 2023–2024 season, covering an area of 32.17 ha. Data collection took place between 90 and 100 days after sowing (DAS)—a critical maturation phase—using a DJI... E. Torres Avila, C.L. Bazzi, S. Moro Lumertz, E. Cely Bonilla, M. Furlan Maggi, T.A. Medeiros, D. Perez, K. Schenatto, R. Sobjak Download paper
5. Use of Digital Permeameter for the Functional Characterization of Geoenvironments Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes
6. Development and Field Validation of SMART-C: A Geostatistics and PCA-Based Decision Framework for Site-Specific Cocoa Management in the Brazilian Amazon Cocoa production plays a major socioeconomic role in Pará State, Brazil’s largest producing region, with annual output exceeding 140 thousand tons. Although Brazil ranks among the world’s leading cocoa producers, most production systems are still managed using field-average approaches that disregard within-field spatial variability of soil attributes and crop performance. This limitation restricts input efficiency and long-term system sustainability in perennial tropical systems.This...

Filter results6 paper(s) found.

1. Influence of Meteorological Variables on Bean Yield in the Semi-Arid Region: A Data-Driven Approach for Agricultural Decision Support

Common bean is a strategic crop for the Brazilian semi-arid region, predominantly cultivated under rainfed systems that are highly dependent on climate variability. In regions characterized by irregular rainfall patterns, high temperatures, and extreme weather events, incorporating temporal analyses based on meteorological data becomes essential for evidence-based agricultural planning. Within the context of precision agriculture, the integration of historical climate series and productivity indicators... A. Fonseca, J.F. Dos Anjos, E.F. Da Silva, G.B. Moura, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.C. Bezerra

Download paper

2. Development of an IoT Platform for Soil and Climate Monitoring in Irrigated Fruit Production in the Semi-Arid Region of Pernambuco

Irrigated fruit production in the São Francisco hinterland, led by the Petrolina production hub, reached US$ 294 million in exports in 2023, consolidating mango and grape crops as strategic pillars of Pernambuco’s economy and of the Brazilian semi-arid region. This production system is dependent on irrigation due to irregular rainfall distribution, high evaporative demand, and recurrent drought conditions. Despite its international competitiveness and technological advances in irrigation... A. Fonseca, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.D. Ribeiro

Download paper

3. Nonlinear Modeling of Vegetation Response to Rainfall Variability in the Brazilian Semi-Arid Region Using Sentinel-2 and CHIRPS Data

High climate variability in the Brazilian semi-arid region poses significant challenges to agriculture and the sustainable management of Caatinga ecosystems, requiring monitoring tools capable of anticipating vegetation responses to rainfall fluctuations. However, the spectral response of vegetation to precipitation does not always follow linear patterns and may reflect ecohydrological thresholds and water saturation effects. Sentinel-2 data were used to derive the Soil Adjusted Vegetation Index... A. Fonseca, E.F. Da Silva, A.C. Bezerra, G.B. Moura, J.F. Dos Anjos, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, J.I. Silva

Download paper

4. Automated Detection of Melons (Cucumis melo L.) via Multispectral UAV and Deep Learning in Honduras

Accurate agricultural production estimation is vital for the logistical and financial efficiency of agribusiness. This study proposes an automated melon detection pipeline using a multispectral Unmanned Aerial Vehicle (UAV) and deep learning architectures. The experiment was conducted in Apacilagua, Honduras, during the 2023–2024 season, covering an area of 32.17 ha. Data collection took place between 90 and 100 days after sowing (DAS)—a critical maturation phase—using a DJI... E. Torres Avila, C.L. Bazzi, S. Moro Lumertz, E. Cely Bonilla, M. Furlan Maggi, T.A. Medeiros, D. Perez, K. Schenatto, R. Sobjak

Download paper

5. Use of Digital Permeameter for the Functional Characterization of Geoenvironments

Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes

6. Development and Field Validation of SMART-C: A Geostatistics and PCA-Based Decision Framework for Site-Specific Cocoa Management in the Brazilian Amazon

Cocoa production plays a major socioeconomic role in Pará State, Brazil’s largest producing region, with annual output exceeding 140 thousand tons. Although Brazil ranks among the world’s leading cocoa producers, most production systems are still managed using field-average approaches that disregard within-field spatial variability of soil attributes and crop performance. This limitation restricts input efficiency and long-term system sustainability in perennial tropical systems.This...