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Luns Hatum de Almeida , S
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Authors
Oliveira, M.F
Ortiz, B.V
Hanyabui, E
Costa Souza, J.B
Sanz-Saez, A
Luns Hatum de Almeida , S
Pilcon, C
Vellidis, G
Alves de Araújo, G
Costa Souza, J.B
Freire de Oliveira, M
Ortiz, B.V
Luns Hatum de Almeida, S
Felipe dos Santos, A
Pereira da Silva, R.P
Conceicao da Silva, L
Luns Hatum de Almeida, S
Costa Souza, J
Sysskind, M
Vellidis, G
Pilcon, C
Pereira da Silva, R.P
da Silva Rego, R
da Silva Sousa, W
Costa Souza, J.B
Luns Hatum de Almeida, S
Bernardo Almeida, E.I
Costa Linhares , S
Topics
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Remote and Proximal Sensing of Soils and Crops
Type
Oral
Poster
Year
2024
2026
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1. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama

Harvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa Souza, A. Sanz-saez, S. Luns Hatum De Almeida , C. Pilcon, G. Vellidis

2. Integrating Management Zones, Artificial Neural Networks and Remote Sensing for Smart Peanut Harvesting

The integration of technologies contributes significantly to agricultural development, especially regarding the rational and more sustainable use of soil. Thus, the use of remote sensing and artificial intelligence techniques combined with precision agriculture can maximize smart harvesting for peanut crops, which face several challenges such as limited harvesting technology, indeterminate growth, and the development of pods below the soil surface. Therefore, this study aimed to develop a peanut...

3. Evaluation of the Similarity between Management Zones Based on Spectral Indices and Soil Electrical Conductivity

The delineation of management zones is one of the main strategies in precision agriculture, as it enables site-specific interventions and improves input-use efficiency. Soil electrical conductivity (EC) is widely used to represent the spatial variability of soil physical and chemical attributes and is often considered a reliable indicator. However, acquiring EC data requires specific equipment and field operations, which may increase operational costs. In contrast, spectral indices derived from...

4. Impact of Mechanical Decompaction on Soybean Yield through Remote Sensing and Agronomic Variables

Soil compaction is one of the main limiting factors for agricultural productivity, requiring efficient diagnostic and management methods. Increased machinery traffic in agricultural areas alters soil physical properties, reducing macroporosity and increasing soil penetration resistance, which restricts root growth and limits water and nutrient uptake. Traditional field methods for diagnosing soil compaction are often punctual and labor-intensive, and they may not adequately represent the spatial...