Proceedings :: International Society of Precision Agriculture

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Ribeiro, B.D

Rother, K

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Authors

Tabbassi, A

Henkler, S

Zakhary, A

Rother, K

Arantes, C

Amaral, L.R

Ribeiro, B.D

Cunha, I

Topics

Decision Support Systems, Cloud Platforms, and Open Data Solutions

Type

Oral

Poster

Year

2026

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Filter results2 paper(s) found.
1. Democratizing Prescriptive Agronomy: Quality-Preserving Edge AI for Sugar Beets The global sugar beet sector faces a critical production paradox where agronomic interventions designed to maximize root yield often compromise sucrose concentration and processing quality. While precision agriculture aims to navigate this delicate balance, current methodologies have reached a methodological impasse. Existing solutions are bifurcated between descriptive data-intensive machine learning (ML), which struggles to generalize across heterogeneous fields, and physiological Process-Based... A. Tabbassi, S. Henkler, A. Zakhary, K. Rother Download paper
2. RAVI: A QGIS plugin for satellite remote sensing applications of Vegetation Indices and SAR data in Precision Agriculture Remote Sensing (RS) plays a fundamental role in Precision Agriculture (PA), particularly through the use of satellite imagery to identify spatial variability within the fields. Compared to traditional methods for detecting field variability, such as soil sampling, yield mapping, and proximal sensors, RS offers advantages in reduced operational costs, lower labor demands, and greater spatial coverage. Analyzing vegetation indices (VIs) over time allows to track crop phenological development, identify...

Filter results2 paper(s) found.

1. Democratizing Prescriptive Agronomy: Quality-Preserving Edge AI for Sugar Beets

The global sugar beet sector faces a critical production paradox where agronomic interventions designed to maximize root yield often compromise sucrose concentration and processing quality. While precision agriculture aims to navigate this delicate balance, current methodologies have reached a methodological impasse. Existing solutions are bifurcated between descriptive data-intensive machine learning (ML), which struggles to generalize across heterogeneous fields, and physiological Process-Based... A. Tabbassi, S. Henkler, A. Zakhary, K. Rother

Download paper

2. RAVI: A QGIS plugin for satellite remote sensing applications of Vegetation Indices and SAR data in Precision Agriculture

Remote Sensing (RS) plays a fundamental role in Precision Agriculture (PA), particularly through the use of satellite imagery to identify spatial variability within the fields. Compared to traditional methods for detecting field variability, such as soil sampling, yield mapping, and proximal sensors, RS offers advantages in reduced operational costs, lower labor demands, and greater spatial coverage. Analyzing vegetation indices (VIs) over time allows to track crop phenological development, identify...