Proceedings
Authors
| Filter results5 paper(s) found. |
|---|
1. Influence of Meteorological Variables on Bean Yield in the Semi-Arid Region: A Data-Driven Approach for Agricultural Decision SupportCommon 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 |
2. Development of an IoT Platform for Soil and Climate Monitoring in Irrigated Fruit Production in the Semi-Arid Region of PernambucoIrrigated 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 |
3. Nonlinear Modeling of Vegetation Response to Rainfall Variability in the Brazilian Semi-Arid Region Using Sentinel-2 and CHIRPS DataHigh 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 |
4. Automated Detection of Melons (Cucumis melo L.) via Multispectral UAV and Deep Learning in HondurasAccurate 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 |
5. Use of Digital Permeameter for the Functional Characterization of GeoenvironmentsCharacterizing 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 |