Proceedings
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| Filter results9 paper(s) found. |
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1. An Integrated Water–Energy Vulnerability Index for Irrigated Agricultural RegionsThe growing interdependence between water availability and energy infrastructure has significantly increased the vulnerability of irrigated agricultural regions, particularly under conditions of climate variability, hydrological uncertainty, and seasonal demand peaks. Irrigated production systems simultaneously depend on reliable water supply and stable energy provision, making them particularly sensitive to disruptions in either domain. Although the water–energy nexus literature has advanced... T.A. Rodolfo, P.S. Schneider, M.A. Perez, F.D. Mantovan, H.R. Bressan, A.C. Reginatto |
2. Simplifying Lab Analysis for Mapping Texture and Om Content Via Sensor-based Inference: a Case Study Showing Maps of Eca and Traditional MethodsPrecision agriculture hinges on soil information at spatial resolutions that capture within-field variability, yet conventional laboratory workflows often constrain sampling density due to cost and turnaround time. In this study, we evaluated a laboratory-based sensor inference service for mapping soil organic matter (OM) and texture (clay and sand) using visible and near-infrared spectroscopy (vis-NIR) and X-ray fluorescence (XRF) spectroscopy. We further evaluated whether resulting maps are... -. -, E. Casciello, J. Pozzuto, T. Tavares, L. Da Silva, H.W. De Carvalho |
3. Integrated Evaluation of Precision Spraying Systems in Pecan Orchards: Smart Apply System™, Conventional Airblast, and Drone ApplicationPecan production in Georgia faces increasing challenges related to weather variability, rising labor costs, and higher prices of agricultural inputs, particularly fungicides required for scab (Venturia effusa) management. Conventional air-assisted sprayers operate at fixed application rates and do not account for tree size variability or canopy gaps, often resulting in overapplication and reduced efficiency. Emerging precision technologies, such as Smart Apply™ sprayers and spray... R.P. Oliveira, J.P. Silva, J.V. Martins, R. Dos Santos, M. Barbosa, L. Oliveira |
4. Topographic Modeling Using Remotely Piloted Aircraft to Identify Areas with Water Erosion Potential and to Plan Sowing LinesWater erosion constitutes one of the main factors of agricultural soil degradation. In this context, knowledge of the topography of agricultural fields and the planning of sowing lines guided by geotechnologies emerges as a strategy to mitigate surface runoff and soil loss. This study aimed to perform the topographic modeling of an agricultural field and to analyze the effect of using different sowing line designs on the longitudinal slope of these lines. The study was conducted in an agricultural... L. Silveira Pavão, A. Müllich, E. Rolim Farias Da Silva, R. Cavalcanti, M. Silveira De Farias, I. , J. Sgarbossa, L. |
5. Digital Agriculture in Decision-Making for Sustainable Disease Management in Soybean CropsSoybean (Glycine max L.) stands out as one of the main crops of agronomic interest, widely used in human and animal nutrition due to its high protein content and diversity of derivatives. Soybean crop productivity is strongly influenced by meteorological conditions, adopted management practices, and the incidence of pathogens, which can significantly reduce the plant’s photosynthetically active area, directly impacting final yield. In this context, the present study aimed to evaluate... E. Rolim Farias Da Silva, L. Lüdtke, G. Ductra Bortolotti, I. Maldaner, L. , J. Sgarbossa, L. Silveira Pavão, A. Müllich |
6. Spatial Delineation of Site-Specific Management Units Using Vegetation Indices in Precision AgriculturePrecision Agriculture has incorporated Remote Sensing as an essential tool for characterizing the spatial variability of agricultural crops. Among the available spectral indices, vegetation indices stand out for their ability to represent vegetative vigor and spatial patterns associated with crop performance. This study aimed to evaluate the spatial stability of spectral indices obtained from a median composite for management zone delineation and to analyze their agreement with a yield map in... L.G. Kern, L. Silveira Pavão, . Müllich, I. Maldaner, L. , J. Sgarbossa, G. Kaefer Seganfredo, E. Rolim Farias Da Silva, M. Silveira Farias |
7. Relationship Between Temporal Variability of Soybean Yield and Stable Soil AttributesManagement zones are widely used in precision agriculture and can be defined by different factors; however, uncertainties remain regarding their temporal stability when based on a single soil attribute. This study aimed to analyze the relationship between a temporal series of yield from five agricultural fields and four stable soil attributes—clay content, soil organic matter (SOM), Topographic Wetness Index (TWI), and apparent electrical conductivity (ECa)—using multiple linear regression... G. Kaefer Seganfredo, L.G. Kern, L. Silveira Pavão, A. Müllich, I. Maldaner, J. Sgarbossa, L. , E. Rolim Farias Da Silva, M.S. Farias |
8. Automatic Detection of White Shrimp (Litopenaeus Vannamei) Feeding Activity Using Acoustic SignalsIn the cultivation of white shrimp (Litopenaeus vannamei), feeding management is one of the main challenges, accounting for approximately 40% to 60% of operational costs. Inaccurate feed management not only increases production costs but also compromises water quality, leading to environmental impacts. Shrimp produce acoustic events known as clicks, which makes it possible to use these signals as indicators of feeding activity. This study analyzes acoustic data collected over... F. Costa Filho, L. Affonso Guedes, S. Peixoto, I. Sánchez-gendriz |
9. Drones as a Tool for Digital Agriculture in Soil and Water Management and ConservationThe use of drones in agriculture has evolved rapidly; however, it is still underutilized in one of the most strategic areas of agricultural production: conservation planning of the terrain. This short course proposes a practical and applied approach on how to use imaging drones for planialtimetric digitalization of agricultural areas, focusing on soil and water management and conservation. Based on the generation of digital surface and terrain models (DSM/DTM), techniques will be demonstrated... A. Müllich |