Proceedings
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| Filter results5 paper(s) found. |
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1. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital AgricultureAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira |
2. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast TrackAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes Junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues |
3. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart FarmCurrently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues |
4. Temporal NDRE Dynamics from UAS Imagery to Characterize Rice Drought ResponseCharacterizing drought resilience in rice remains challenging under increasing climate variability. Drought tolerance is a complex and dynamic trait that is difficult to quantify using traditional field phenotyping approaches, particularly when responses vary with time. High-throughput temporal phenotyping with unmanned aircraft systems (UAS) enables monitoring of canopy reflectance dynamics associated with water stress across the growing season. This study evaluated whether temporal... |
5. Leaf Nutrient Estimation in Soybean from Multispectral and Multitemporal Information Using UAV and Machine LearningPrecision agriculture, through remote sensing with Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence, offers solutions for monitoring crop growth and development, supporting decision-making aimed at resource optimization and agricultural sustainability. This study evaluated the feasibility of using multispectral information captured by UAVs at different phenological stages (V6, V8, and R2) to estimate leaf nutrients (N, P, K, Ca, Mg, Cu, Zn, and Mn) in soybean crops as an alternative... E. Cely Bonilla, C.L. Bazzi, R. Sobjak, K. Schenatto, E. Torres Avila, M. Rodrigues, S. Spricigo |