Proceedings :: International Society of Precision Agriculture

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Ferreira, E.J

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Authors

Françani, A.O

Zhao, L

Ferreira , J

Yan, J

Ferreira, E.J

Jorge, L.A

Bassoi, L.H

Costa, B.S

Ferreira, E.J

Oldoni, H

Jorge, L.A

Speranza, E.A

Ferreira, E.J

Bassoi, L.H

Rabello, L.M

Vaz, C.M

Torre-Neto, A

Karasinski, M.A

Macedo, E

Costa, R

Peixoto, A.S

Duarte, D.S

Gil da Silva, B.J

Ferreira, E.J

Jorge, L.A

Bendahan, A.B

Topics

Precision Crop Protection, Pest, and Plant Health

Variable-Rate Irrigation, Drainage Optimization, and Water Management

Remote and Proximal Sensing of Soils and Crops

UAV-Based Scouting, Imaging, and Targeted Applications

Type

Oral

Poster

Year

2026

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Authors

Filter results4 paper(s) found.
1. Characterizing Cross-Crop Stink Bug Spectral Signatures from Hyperspectral Data Effective crop protection in agricultural production systems requires the ability to detect pest-induced stress in a timely and reliable manner. In large-scale farming systems, stink bugs attack multiple crop species, making cross-crop pest detection a critical capability for scalable monitoring solutions. Rather than developing crop-specific models that require retraining for each species, identifying crop-independent spectral signatures of stink bug infestation enables transferable detection... A.O. Françani, L. Zhao, J. Ferreira , J. Yan, E.J. Ferreira, L.A. Jorge Download paper
2. A Hybrid Non-Destructive Approach Combining Image Processing and Spectral Feature Selection for Grapevine Leaf Water Content Estimation Reliable and continuous estimation of leaf water content (LWC) is essential for viticulture, as it enables assessment of spatiotemporal variability in vine water demand and supports improved irrigation management efficiency within Precision Agriculture (PA) practices. Although the gravimetric method based on fresh weight (FW) and dry weight (DW) measurements provides accurate LWC estimates, it is time-consuming, destructive, and exhibits limited scalability for large sample sizes. In contrast,... L.H. Bassoi, B.S. Costa, E.J. Ferreira, H. Oldoni, L.A. Jorge Download paper
3. A Statistical Approach to Defining Coffee Management Zones: Integrating Apparent Soil Electrical Conductivity, Altimetry and Satelitte Indices for Moisture Monitoring Characterizing the spatial and temporal behavior of soil and plant attributes represents the elementary step toward adoption precision agriculture. The expanding availability of multi-temporal remote sensing imagery with enhanced spatial resolution has rendered the delineation of management zones (MZ) an increasingly feasible strategy, especially when the intention is to carry out spatially differentiated interventions considering the vegetative vigor throughout the crop cycle or the plant yield.... E.A. Speranza, E.J. Ferreira, L.H. Bassoi, L.M. Rabello, C.M. Vaz, A. Torre-neto Download paper
4. Weed mapping: advantages of RGB CNN-based approaches vs multispectral pixel-based methods Weed detection remains a major challenge in modern agriculture, and accurate weed mapping is crucial to support rapid and efficient management interventions, ensuring crop productivity and economic viability. In this context, geotechnologies such as remote sensing and computer vision, together with the widespread adoption of drones, enable the acquisition of ultra–high spatial resolution imagery, allowing more detailed analyses in complex agricultural environments. Although multispectral...

Filter results4 paper(s) found.

1. Characterizing Cross-Crop Stink Bug Spectral Signatures from Hyperspectral Data

Effective crop protection in agricultural production systems requires the ability to detect pest-induced stress in a timely and reliable manner. In large-scale farming systems, stink bugs attack multiple crop species, making cross-crop pest detection a critical capability for scalable monitoring solutions. Rather than developing crop-specific models that require retraining for each species, identifying crop-independent spectral signatures of stink bug infestation enables transferable detection... A.O. Françani, L. Zhao, J. Ferreira , J. Yan, E.J. Ferreira, L.A. Jorge

Download paper

2. A Hybrid Non-Destructive Approach Combining Image Processing and Spectral Feature Selection for Grapevine Leaf Water Content Estimation

Reliable and continuous estimation of leaf water content (LWC) is essential for viticulture, as it enables assessment of spatiotemporal variability in vine water demand and supports improved irrigation management efficiency within Precision Agriculture (PA) practices. Although the gravimetric method based on fresh weight (FW) and dry weight (DW) measurements provides accurate LWC estimates, it is time-consuming, destructive, and exhibits limited scalability for large sample sizes. In contrast,... L.H. Bassoi, B.S. Costa, E.J. Ferreira, H. Oldoni, L.A. Jorge

Download paper

3. A Statistical Approach to Defining Coffee Management Zones: Integrating Apparent Soil Electrical Conductivity, Altimetry and Satelitte Indices for Moisture Monitoring

Characterizing the spatial and temporal behavior of soil and plant attributes represents the elementary step toward adoption precision agriculture. The expanding availability of multi-temporal remote sensing imagery with enhanced spatial resolution has rendered the delineation of management zones (MZ) an increasingly feasible strategy, especially when the intention is to carry out spatially differentiated interventions considering the vegetative vigor throughout the crop cycle or the plant yield.... E.A. Speranza, E.J. Ferreira, L.H. Bassoi, L.M. Rabello, C.M. Vaz, A. Torre-neto

Download paper

4. Weed mapping: advantages of RGB CNN-based approaches vs multispectral pixel-based methods

Weed detection remains a major challenge in modern agriculture, and accurate weed mapping is crucial to support rapid and efficient management interventions, ensuring crop productivity and economic viability. In this context, geotechnologies such as remote sensing and computer vision, together with the widespread adoption of drones, enable the acquisition of ultra–high spatial resolution imagery, allowing more detailed analyses in complex agricultural environments. Although multispectral...