Proceedings
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| Filter results7 paper(s) found. |
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1. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping ApplicationsCurrently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the particular... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen |
2. Sugarcane Yield Mapping Using an On-board Volumetric SensorFew alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being introduced... G. Balboa, J.C. Masnello, F. De Oliveira Moreira, R. Canal Filho, E.R. Da Silva, J.P. Molin |
3. What 255 Sugarcane Farms and 15,000 Ha Reveal About Sustainable Nutrient ManagementConsidering spatial and temporal variability in agricultural production is a key pathway toward improving sustainability in broadacre systems. Cropping systems under uniform management (UM) assumptions inherently neglect this variability, creating substantial inefficiencies and environmental risks. In Brazil, sugarcane occupies approximately 9 million hectares and underpins a bioenergy sector often cited as contributing to one of the most renewable energy matrices worldwide. However, fertilizer... R. Canal Filho, J.P. Molin, L. De Goes Sterle, V. Ferraz |
4. Integrating Data Layers with Machine Learning to Predict Yield for Irrigated Grain Crops within Management ZonesEffective yield prediction is fundamental for precision agriculture, enabling data-driven management decisions. This study, conducted in a 52.3 ha center-pivot irrigated field in Itaí, São Paulo, Brazil, evaluated the hypothesis that delineating management zones (MZs) based on stable soil and terrain attributes, combined with machine learning (ML) algorithms, improves grain yield prediction accuracy compared to field-scale models. Apparent soil electrical conductivity (ECa) at two... L. De Goes Sterle, R. Canal Filho, V. Ferraz, M. Gelain, J.P. Molin |
5. Site-specific Nutrient Management in Citrus: Agronomic, Economic and Energy Implications of Variable Rate FertilizationBrazilian citrus production faces increasing challenges due to rising costs, intensifying climatic and biotic stresses, and the growing demand for optimization in input use, particularly fertilizers. In this context, precision agriculture can provide the conceptual and operational basis for site-specific management, allowing fertilizer application to be adjusted to the spatiotemporal variability of the production system. This study evaluated, under commercial-scale conditions, the effects of variable-rate... G.V. Bedum, A. Colaço, M. Gelain, R. Canal Filho, J.P. Molin, E. Otavio Da Silva |
6. Simulation of Different Nitrogen Fertilization Strategies Using Management Zones in Sugarcane CultivationNitrogen plays a central role in sugarcane physiology, as it is a structural component of amino acids, proteins, nucleic acids, and chlorophyll, being essential for photosynthetic activity, leaf expansion, biomass accumulation, and stalk formation. Given its relevance, nitrogen management efficiency represents a central research topic in sugarcane, particularly in systems characterized by strong spatial heterogeneity, where soil physical–hydric attributes, fertility levels, and environmental... G.V. Bedum, J.P. Molin, R. Canal Filho |
7. Sugarcane row gaps enable the identification of critical rows for targeted interventionsDistinct patterns of sugarcane row gaps and associated plant population reduction drive the spatiotemporal variability of yield, creating a bottleneck for row prioritization in management decisions. This study tested the hypothesis that specific sugarcane rows within a field concentrate most of the linear gap lengths (LLG) and their associated economic and productive losses, consistent with the Pareto Principle. The objective was to identify rows that are critical in terms of LLG occurrence, making... E. Otavio Da Silva, J.P. Molin, R. Canal Filho, M.R. Cherubin |