Proceedings
Topics
| Filter results51 paper(s) found. |
|---|
1. Predictive Analysis of Fertilizer Efficiency with Machine LearningFertilizers play a key role in agribusiness, both as an essential input for agricultural productivity and as a strategic component in the commercial chain. They provide nutrients that are indispensable for soil correction and crop growth, such as nitrogen, phosphorus, and potassium, allowing the soil to maintain its capacity to sustain crops even after several harvests. It is estimated that about 50% of global food production depends on the use of fertilizers, and in Brazil, these inputs repr... C.S. Santos, R.K. Weber |
2. A Model to Support Decision-making in the Generation of Management Zones for Fruit GrowingImplementation of precision fruit farming faces challenges in accurately defining these zones, mainly because, as the orchard reaches the productive phase, the relevance of soil fertility decreases compared to other phytotechnical and physiological parameters. Correct generation of management zones is crucial for the success of the operation, but the accurate interpretation of the collected data requires highly qualified professionals with years of experience, a gap that limits the adoption o... L. Gebler, J.M. Dias |
3. Data Governance Platform for Precision Agriculture: Enhancing Traceability and SustainabilityPrecision Agriculture (PA) is one of the enablers of data-driven agriculture. Digital Agriculture (DA) tools are increasingly vital in driving the adoption of PA techniques across small, medium, and large-scale farming operations. These technologies, including the Internet of Things (IoT), sensors, drones, satellite imagery, Artificial Intelligence (AI), and Big Data, work synergistically to capture detailed information on soil conditions, plant health, climate, and machinery performance. Thi... E.A. Speranza, R.Y. Inamasu, L.A. Romani, J. Naime, R. Sobjak, I. Vacari, C.L. Bazzi, S. Shibusawa |
4. Adapt Standard: Enabling Interoperability in Agricultural Field Operations DataModern agriculture increasingly relies on sophisticated technologies, including precision farming equipment, sensors, laboratory analyses, and farm management software, to generate critical operational data. Despite these advancements, the industry faces significant interoperability challenges, resulting in fragmented data ecosystems that impede optimized decision-making. While ISO 11783 (ISOBUS) successfully facilitates electronic communication at the machinery level, it does not adequately ... B. Craker, S.T. Nieman, J.W. Wilson, S. Rhea, K. Nelson, D. Danford, J.A. Wilson, B. Kemp |
5. Spatial Data Interpolation in the AgDataBox Platform Using Graphics Processing Unit ParallelismPrecision agriculture platforms increasingly operate as integrated ecosystems that collect, store, and process large volumes of heterogeneous spatial data originating from multiple sources, including soil sampling, onboard sensors embedded in agricultural machinery, yield monitors, and remote sensing technologies such as satellites and unmanned aerial vehicles (UAVs). These platforms play a fundamental role in transforming raw georeferenced data into actionable information that supports site-... R. Sobjak, V.H. Malacarne, C.L. Bazzi, E. Souza, K. Schenatto, M. Rodrigues |
6. Management Zone Delineation Replacing Yield Maps with Vegetation Indices: Effects of Spatial Resolution and Machine Learning-based SelectionThe delineation of Management Zones (MZs) is a precision agriculture strategy that exploits the spatial variability of crop fields to support more efficient and sustainable site-specific management practices. Traditionally, yield maps have been used as one of the main information layers in this process, as they integrate the effects of soil, climate, and management throughout the crop cycle. However, obtaining reliable yield maps still presents limitations, such as the need for onboard sensor... M. Gelain, J.P. Molin, L. De Goes Sterle |
7. Democratizing Prescriptive Agronomy: Quality-Preserving Edge AI for Sugar BeetsThe global sugar beet sector faces a critical production paradox where agronomic interventions designed to maximize root yield often compromise sucrose concentration and processing quality. While precision agriculture aims to navigate this delicate balance, current methodologies have reached a methodological impasse. Existing solutions are bifurcated between descriptive data-intensive machine learning (ML), which struggles to generalize across heterogeneous fields, and physiological Process-B... A. Tabbassi, S. Henkler, A. Zakhary, K. Rother |
8. PRAGMATIC - Innovative IT Platform for Yield and Cost Prediction of Agricultural ProductionThe aim of the R&D was to develop a prototype of an innovative IT platform containing algorithms for predicting yields and production costs of agricultural commodities for three reference crops, i.e.: blueberries, apples and potatoes in the supply chain from the field to the production line. The system are ... T. Wojciechowski, G. Niedbała, K. Bobran |
9. Automatic Creation of Thematic Maps and Management Zones Using Agdatabox-fast TrackPrecision agriculture encompasses the strategic application of inputs in requisite quantities at optimal times to enhance overall productivity. An essential aspect of this methodology is the formulation of thematic maps (TMs) and management zones (MZs). Despite their critical importance, delineating TMs and MZs requires substantial technical expertise in their construction, making their application challenging, particularly for smaller producers, due to the need for a specialized multidiscipl... J. Aikes Junior, E. Souza, C.L. Bazzi, R. Sobjak, E. Souza |
10. Spatio-temporal Yield Stability in Rice-soy Rotations at Farm ScaleIntegrated crop-livestock systems are facing the pressure to intensify worldwide, thus decoupling crops from pasture and reducing the amount of time under pasture, while increasing the frequency of annual grain crops. In Uruguay, rice production is commonly integrated into crop–livestock systems, generating productive and environmental advantages compared to many rice-growing regions worldwide. Recent intensification of these systems, particularly through the incorporation of soybean in... I. Macedo, &. Roel, J.J. Bonomo |
11. Standardisation Challenges in Precision Agriculture: Mapping the Landscape and Advancing Semantic InteroperabilityBackground: Precision agriculture increasingly depends on digital technologies and the exchange of data between equipment, sensors, platforms and decision support tools. A wide range of standards is available, including machine data formats such as ISOXML and semantic resources such as AGROVOC and rmAgro. Despite this variety, the overall standardisation landscape remains fragmented. Even within single countries, differences in code lists, vocabularies and data publishin... J. Tummers, F. Sijbrandij, T. Ten Den, A. Gupta, T. Bresilla, B. Veldhuisen |
12. Towards Trusted Satellite Data for Precision Farming: Mitigating Spoofing and Improving Data Integrity Using Galileo OSNMA and HAS and Copernicus Traceability ServiceBackground: Precision agriculture increasingly relies on GNSS positioning not only to execute field operations with high spatial accuracy, but also to provide trustworthy data for documentation, certification, and regulatory compliance. However, GNSS signals remain vulnerable to degradation, jamming, and especially spoofing—an intentional manipulation of satellite signals causing machinery to believe it is in a different position. Such incidents have already been observ... B. Veldhuisen, T. Bresilla, J. Tummers, F. Sijbrandij, T. Ten Den, A. Gupta, T. Van Der Wal |
13. 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 ... 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 |
14. 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 ir... A. Fonseca, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.D. Ribeiro |
15. Comparing Traditional Methods and Digital Platforms for Delineating Management Zones: A Study of Efficiency and AccuracyDigital platforms have emerged as user-friendly tools to support management zone delineation and field monitoring in precision agriculture. However, the algorithms and methods embedded in these platforms may overlook agronomic and operational constraints, limiting their effectiveness in decision-making. This study evaluated the performance of three commercial digital platforms for management zone delineation and compared them with a reference protocol and an... T. Costa Barboza, H. Oldoni, F.D. Inácio, L.R. Amaral, A. Felipe Dos Santos |
16. From Raw Yield Data to Cell-based Risk Management: a Next-generation Framework for Ultra-high Resolution Yield Stability and Yield Gap Analysis in Hungarian Arable EnvironmentA fundamental challenge in modern precision agriculture is ensuring access to raw yield data, its systematic processing, and the subsequent planning of foundational and Variable-Rate Application (VRA) maps required for decision support. This research aimed to develop a methodology suitable for the cell-level multitemporal processing of yield datasets to establish production-risk classes and quantify unrealized potential via yield gap analysis. This framework exceeds conventional precision pla... D. Szám |
17. Mobile Edge AI for Detection of Grape Clusters and Disease Symptoms in VineyardsPrecision viticulture demands accessible technological solutions that enable rapid disease diagnosis and production monitoring directly in the field. In real-world production contexts, dependence on cloud connectivity, external servers, or specialized hardware limits the adoption of computer vision tools by small and medium-sized farmers. In this context, this work presents a solution based on artificial intelligence embedded in a mobile application for the detection of grape bunches and leav... E.M. Da Silveira, F.I. Nogueira, S.D. Camargo, A. Freire Campos, J. Valiati, E.F. Leite |
18. Web Application Based on CNN for Classification of Biotic and Abiotic Stresses in Coffee LeavesThe use of digital systems can assist coffee growers and professionals in diagnosing stresses that affect coffee plantations, ensuring that crop management is carried out correctly and efficiently. Therefore, the aim of this study was to develop a web application based on a pre-trained Convolutional Neural Network to classify coffee leaf images exhibiting symptoms of biotic and abiotic stresses. Initially, a dataset consisting of coffee leaf images affected by biotic and abiotic stresses was ... D.H. Leite, D.S. Valente, P.M. Arruda, F.D. Tancredi, D. Queiroz, G. Dumbá Monteiro De Castro |
19. RAVI: A QGIS plugin for satellite remote sensing applications of Vegetation Indices and SAR data in Precision AgricultureRemote Sensing (RS) plays a fundamental role in Precision Agriculture (PA), particularly through the use of satellite imagery to identify spatial variability within the fields. Compared to traditional methods for detecting field variability, such as soil sampling, yield mapping, and proximal sensors, RS offers advantages in reduced operational costs, lower labor demands, and greater spatial coverage. Analyzing vegetation indices (VIs) over time allows to track crop phenological development, i... |
20. SPARC-AI: Synthetic Procedural Agricultural Rendering and Annotation Framework for Crop Phenotyping and AI ApplicationsBetween 20% and 40% of global agricultural production is lost annually to pests and diseases, generating economic damages estimated at over US$220 billion each year. This persistent challenge underscores the urgent need for scalable, precise, and cost-effective monitoring solutions. In this scenario, Artificial Intelligence (AI) based pathogen detection systems emerge as transformative tools, enabling high-resolution spatial and temporal monitoring of crop health. However, the perfo... R. Freitas, V.S. Mello, G.D. Dallegrave, E. Farinati Leite, J.F. Valiati |
21. An Online Decision Support Tool for Homogeneous Zone Delineation in Precision AgricultureManagement zone delineation is a key component of site-specific management in precision agriculture, enabling the spatial optimization of inputs and an improved understanding of within-field variability. Traditionally, homogeneous zones have been derived from historical yield maps or soil-related variables obtained through proximal sensing. More recently, the increasing availability of multispectral satellite imagery and derived vegetation indices has expanded the range of data sources availa... |
22. Mapping Digital Technologies, Cloud Platforms, and Artificial Intelligence in Precision Agriculture: The Software Baseline for a Citrus and Sugarcane Living Lab.The digital transformation of Precision Agriculture (PA) has been driven by the growing availability of Farm Management Information Systems (FMIS), cloud platforms, and Artificial Intelligence (AI) solutions. This study, linked to the Smart B100 Science for Development Center (CCD-SB100), funded by FAPESP and led by the Agronomic Institute of Campinas (IAC), Faac/Unesp (Bauru), in partnership with FATEC Pompeia, aimed to build a multicriteria matrix (technological inventory) of digital PA sol... M. Mazega, H. Fortinis, H. Fischer, C.K. Luvizotto, C.E. Otoboni, M.C. De Almeida |
23. AgGeoSampler: A Geospatial Open-Source Data Acquisition and Sampling Design Dashboard for Agricultural ApplicationsModern agricultural and environmental research increasingly depends on high-resolution geospatial data to support precise, site-specific decision-making. Advances in satellite remote sensing, unmanned aerial systems, and digital soil mapping have generated vast spatial datasets that capture fine-scale variability in vegetation health, soil properties, and terrain attributes. However, translating this wealth of information into effective field-sampling... A. Bhattarai, A. Jakhar, K. Poudel, A. Dhaliwal, L.M. Bastos |
24. Challenges in Integrating Digital Agriculture SolutionsAdvances in digital agriculture have increased the supply of solutions to improve the management of agricultural activity. However, the increasing number of solutions in quantity and variety also imposes barriers to their adoption by small and medium-sized family farmers reasoned by higher exposition to technical and financial limitations. High cost, low digital literacy, and little perception of the usefulness are some of the obstacles. These can be further exacerbated if producers need ... J. Da Silva, S.R. Evangelista, J.G. Barbedo, L.A. Romani |
25. Transforming Agronomic Tables into Continuous Sufficiency and Fertilizer-rate Functions for Digital Recommendation SystemsSoil-test interpretation tables and fertilizer recommendation tables are widely used in agronomic practice, but they typically classify results into discrete categories (e.g., very low, low, medium, and high). While this format is suitable for manual consultation, it introduces artificial “jumps” between classes and limits automation when implementing diagnostic and recommendation rules in computerized systems. In this study, we developed a two-step methodology to convert these ta... D. Fernandes Paiva, G.M. Chaer |
26. 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 |
27. Spatial Distribution of Coffee Leaf Miner Infestation and Its Impact on Coffee Fruit Maturation, Yield, and Beverage QualityDifferences in the maturation rate of coffee fruits can be associated with plant stress. The incidence of pests, such as the coffee leaf miner (Leucoptera coffeella), compromises the photosynthetically active area, which can reduce yield and beverage quality. Computer vision can assist in damage reduction by identifying the pest's spatial and temporal behavior. This study aimed to verify, spatially and temporally, the impact of damage caused by the coffee leaf miner on ... L.V. Lazzarini, A. , G.P. Cândido, V.M. Nunes, S.M. Hurtado, F.H. Leandro, I.D. Gonçalves |
28. Performance of Horizontal Seed Metering Technologies for Maize at Different Angular VelocitiesBrazil is a global leader in grain production, with an estimated record of 353.1 million tons for the 2025/26 harvest. Maize cultivation showed an increase in the total estimated sown area, totaling 22.7 million hectares across the three harvests, with a 4% growth expectation—rising from 21.7 million hectares in 2024/25 to 22.8 million hectares in the current season, which corresponds to an increase of 871,800 hectares. The demand for maize grain is steadily growing for both animal feed... J. Santos, V. Kaster Marini |
29. 3D Position and Size Estimation of Fruits Using an Intel RealSense D435 CameraThis work addresses the development of a computer vision algorithm for an agricultural robot whose task is to harvest tomatoes in a plantation. The ability to detect fruits, as well as to estimate their 3D position and size in the world coordinate system, is fundamental for accomplishing this task. This approach has been widely discussed in the literature, especially due to the challenge of obtaining accurate estimates of the spatial coordinates of objects. This process is strongly affected b... E. Chimuando, J.A. Fabro, S.F. Pichorim |
30. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative ApproachesWeed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. T... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza |
31. A Seeder for Sustainable Agriculture Enabling Intercropping and Multi-Variety Sowing and Adaptable to Precision Agriculture through Variable-Rate SeedingDavut Karayel*1,2 Egle Jotautiene2 Hasan Yılmaz1,2 1Akdeniz University, Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, Antalya, Turkey 2Vytautas Magnus University, Agriculture Academy, Faculty of Engineering, Department of Agricultural Engineering and Safety, Kaunas, Lithuania. * Corresponding author and presenter ... D. Karayel, E. Jotautiene, H. Yılmaz |
32. Development and Evaluation of a Novel Seeding Metering System for Mechanic Seeder Toward Precision AgricultureRecent progress in precision and digital agriculture has increasingly relied on the integration of computational modeling, sensor-based analysis, and data-driven design to improve agricultural machinery performance. Seed metering systems are central to this progress, as they regulate seed delivery for both uniform crop establishment and variable-rate seeding applications. In conventional agricultural systems, where field conditions are assumed to be relatively homogeneous, uniform seed spacin... E. Jotautienė, D. Karayel, H. Yilmaz, A. Grigas |
33. Hybrid Fuzzy–pid Control for Variable-rate Center Pivot Irrigation: an Automation-driven Approach to Precision Water ManagementPrecision agriculture increasingly relies on advanced automation and intelligent control strategies to address the spatial and temporal variability of crop water requirements while minimizing resource consumption. Center pivot irrigation systems are widely deployed in large-scale farming operations; however, their conventional control architectures are typically based on fixed schedules or linear feedback laws, which are insufficient to handle the nonlinear dynamics, uncertainties, and distur... F.R. Jimenez Lopez, A. Jimenez, I.A. Ruge Ruge, D.Y. Garcia Ramirez |
34. Spatial Variability in Mechanized Coffee Harvesting at Two Travel SpeedsWithin the scope of Precision Agriculture (PA), monitoring the spatial variability of mechanized operations is a strategy for improving operational efficiency in coffee plantations. The evaluation of mechanized harvesting should consider, in addition to the harvested volume, the proportion of coffee effectively detached in relation to fallen coffee (FC) and remaining coffee (RC), variables directly linked to operational efficiency. Harvesting was carried out at Mariano Farm, in Poços d... N.A. Zimermam, R.P. Pereira Da Silva, L.E. Zonfrilli, A. Andrade Da Silva, T.M. De Oliveira |
35. A High-Precision Laser Weeding System for Lettuce FieldsWeeds in lettuce (Lactuca sativa L.) fields compete aggressively for essential resources, significantly hindering crop productivity. To enable non-chemical, high-precision weed management, this study developed an integrated laser weeding system leveraging a novel YOLO11-GDCNet algorithm and a compact galvanometer scanning device. The proposed YOLO11-GDCNet enhances the baseline YOLO11n-pose by incorporating GSConv and DualConv modules to reduce computational overhead while improving... W. Su |
36. A Dual-Arm Machine-Vision-Guided Robotic System for High-Throughput Tissue Sampling in Potato TubersHigh-throughput molecular pathogen detection in potato tubers requires tissue sampling methods that are both sensitive and specific. A critical step in this workflow is the manual extraction of tissue cores, which is labor-intensive and time-consuming, limiting scalability for large-scale diagnostics. To address this challenge, this study developed a machine-vision-guided, dual-arm coordinated inline robotic system that integrates tuber picking, rotation, and tissue sampling mechanisms. In th... D. Loganathan Girija, S. Usama Bin Sabir, D. Rathore, L.R. Khot, C. Mattupalli, M. Karkee |
37. Effect of Terrain Slope Obtained by LiDAR on Operational Performance in Semi-mechanized Coffee Transplanting with Autopilot.The application of precision agriculture techniques has become an important tool in surveying coffee plantations, allowing for the rapid assessment of slope profiles in these areas and indicating the possibility of mechanizing the plots. Therefore, there is a need to work with quality in semi-mechanized transplanting operations using autopilot to optimize future processes related to coffee cultivation. The objective of this study was to determine the efficiency of use and mechanical availabil... R. , G. , R.D. Faria, L.S. Silva, M.D. Oliveira, E.H. Zavala |
38. Results from a Scoping Review: the Role of Autonomous Mechanical Weeding Robots in Climate-smart Soil ManagementThe growing demand for sustainable agricultural practices has driven advancements in digital agricultural technologies, which is also reflected in the emerging development and market release of agricultural field robots in the last decade. Climate-smart sustainable soil management plays a key role in sustaining soil functions related to productivity, water and nutrient cycling, biodiversity and long-term resilience. The integration of autonomous field robots, for which mechanical weeding is c... K. Grahmann, L. Rohlmann, L. Thielemann, A. Roy, C. Weltzien |
39. Monitoring, Automation, and Control System for Small Scale SilosBrazil has an important role in the global grain production scenario. However, the country’s grain storage infrastructure is usually inadequate and insufficient. The drying and storage of grains post-harvest are essential to ensure product quality, even over extended periods. In this context, research has been conducted on sensing, monitoring, and prediction of grain temperature and humidity, as well as the automation and control of the drying process. Therefore, this paper presents a s... C.C. Scharlau, C.R. Krumreich, N. Pagani Neto, H.M. Tamba , B. Culda |
40. Consolidation of Factors Influencing the Design of an Electrically Driven Seed Metering and Delivery Mechanism for High-speed Operation.The development of innovative products to address agricultural challenges has become essential for more efficient operations, resulting in increased productivity. In this context, the parameters of Design Influence Factors (DIFs) define the technical and functional guidelines of the machinery, ensuring that the final product fully meets the demands defined throughout its life cycle. This study proposes the consolidation of DIFs applied to the development of an electrically driven seed meterin... J. Santos, V. Kaster Marini |
41. Verification of the Practices of the European Union Regulatory Framework and Comparative Analysis with the Capabilities and Requirements of Good Practices in Precision Seeding in Brazil.Global precision and digital agriculture is undergoing a period of technological and regulatory transition. Faced with the growing global demand for operational efficiency, Brazilian technology for active seed metering and guidance at high speeds emerges as a high value-added solution. However, the commercialization of these components in the European market requires technical harmonization between Brazilian practices and the bloc's certification requirements. This work aims to verify the... J. Santos, V. Kaster Marini |
42. Performance of Autonomous Navigation in an Agricultural Tractor Using Pure Pursuit Control and Dubins Path PlanningAutopilot systems in agricultural machinery are primarily designed to ensure accurate tracking of predefined routes. However, their performance is strongly influenced by the internal parameters of the control algorithms employed, which may vary according to operational conditions. In this context, computational simulations constitute a valuable tool for investigating these interactions and identifying optimal operating configurations. This study evaluates an autopilot system based on the Pure... J.D. Baltazar, A.L. Coelho, L. De Arruda Viana, A.D. Brandão, D.S. Valente, M.R. Furtado Jr |
43. Impact Assessment Tool (IAT) for Robotic and XR Applications in Agriculture: Cases from AgRibot ProjectThis paper presents an Impact Assessment Tool (IAT) developed within AgRibot project which is meant to evaluate the socio-economic and environmental impact of AR/XR-integrated robotic applications in crop farming based on six use cases situated in selected European countries. While each case focuses on a target crop and operation, the impact assessment follows a modular approach with some modifications according to case specificities. The tool aims to address the challenges of quant... T.W. Tamirat, S.M. Pedersen |
44. Software Protocol Converters as Enablers for Interoperability in Heterogeneous Multi-Robot SystemsAdvancements in agricultural robotics are driving a transition toward ecosystems composed of heterogeneous platforms from multiple manufacturers. In this context, robotic platforms from multiple vendors must coexist and collaborate to perform complex tasks, including autonomous monitoring and precision weeding. However, this evolution introduces a fundamental challenge: the lack of a standardized communication stack capable of supporting cross-platform integration. The widespread use of propr... N.K. Wagner, C. Teixeira, V. Fontena, C.S. Junior, O.A. Cruz, P.H. Morgan Pereira |
45. Geometric Assessment of Software-Based Path Planning for Mechanized Seeding OperationsThis study evaluated the impact of different software-based planning routines on the geometry of guidance lines for mechanized seeding operations. A controlled comparative case-study approach was implemented using two agricultural fields in Minas Gerais, Brazil. One irregular field of 33.6 ha and one predominantly rectilinear field of 107.6 ha. Two anonymized tools, Software A and Software B, were applied to identical boundary polygons, with one headland pass and 9 m line spacing. The exporte... A. Felipe Dos Santos, R.D. Borges, M.C. Arnosti, C. Marcassa Lonzi De Oliveira |
46. Orchestration of Missions for Coordination between Autonomous Agents in Agriculture.Due to technological advancement in agriculture, various autonomous agents, such as drones, mobile robots, and intelligent agricultural vehicles, are being used to automate repetitive tasks and increase agricultural production. In addition, these agents, often developed by different manufacturers and endowed with different capabilities, form a highly heterogeneous environment, imposing a central challenge to be solved: the need to manage these agents so that they can act in a coordinated and ... V. Fontena, N.K. Wagner, C. Teixeira, J. Lopes, L. Moura, C. Guimarães |
47. A Architecture for GNSS-Based Autonomous Navigation in Agricultural RobotsGlobal Navigation Satellite Systems (GNSS), especially when used with real-time correction techniques such as Real-Time Kinematic (RTK), are widely employed in precision agriculture due to their ability to provide accurate absolute positioning. This capability enables georeferenced operations such as planting, selective spraying, and autonomous navigation across large agricultural areas, even in environments with few structural references. In contrast, modern robotic navigation frameworks, su... V. Fonteca, C. Guimarães, M. Monteiro, I. Azevedo, A. Da Rosa, N.K. Wagner, C. Teixeira |
48. A Hardware Classification Matrix for Precision Agriculture: Structuring an On-Farm Living Lab in Brazilian Citrus and Sugarcane SystemsThe consolidation of Precision Agriculture (PA) in Brazilian fields depends fundamentally on the physical infrastructure deployed on-farm, including sensors, actuators, embedded controllers, and implements. Although citrus and sugarcane represent pillars of São Paulo's agribusiness, the sector still lacks a systematized inventory that catalogues and classifies PA hardware effectively adopted across different producer profiles. Integrated into the Smart B100 Advanced Research Center... R. Rolon, H. Fischer, C.E. Otoboni, C.K. Luvizotto, M.C. De Almeida |
49. Proprietary vs. Open-Source Visual-Inertial Fusion Under GNSS Degradation for Orchard-Scale 3D Fruit MappingA recent pipeline combining GNSS-visual-inertial odometry with factor-graph refinement of fruit landmarks has reported orchard-level apple counting errors below three percent against harvest totals — a result with few precedents in the agricultural SLAM literature, where GNSS-VIO fusion, landmark-level optimization, and harvest-validated yield estimation have until now appeared only in isolation. However, trajectory quality in that pipeline was ... T. Santos, D. Bharti, L. Gebler, A. De Rossi |
50. Exploring the XAG R150 UGV Capabilities: Air-Assisted vs Vertical Boom Attachment AssessmentsRobotic spraying platforms are rapidly advancing in specialty crop production; however, limited information exists regarding optimal spray parameters under different crop spacings and spray configurations. The XAG R150 robotic sprayer is a ground-based autonomous system capable of operating in both air-assisted and vertical/horizontal boom spraying modes, offering flexibility for diverse row-crop environments. This study evaluated spray performance parameters of the XAG R150 under varying cro... |
51. Development of a System for Intelligent Plant Monitoring and CultivationCultivation in protected environments and indoor systems requires continuous monitoring. Labor shortages and delays in management decisions compromise productivity, uniformity, and efficiency. Assessments of plant stand, vegetative vigor, nutritional status, and the incidence of pests and diseases still rely on visual inspections conducted over limited periods, reducing diagnostic accuracy and response time. Although automation technologies are advancing in horticultural production, available... R. Avelar, F.O. Dos Reis Silva, A.L. Carvalho, F.M. Alves Soares, C.C. Santana |