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1. AgDataBox-Map: Web Application for Spatial Analysis and Delineation of Management Zones for Dynamic Fruit Harvesting in Precision AgricultureHarvest maps are fundamental tools in precision agriculture, as they allow for the evaluation of whether corrective actions taken before and during the harvest have had the planned effect, through visualization of the heterogeneity of production within the cultivated area. However, in fruit growing, due to the extensive use of manual labor for harvesting to the detriment of mechanization, the generation of thematic maps has always been a problem. In Brazil, initiatives developed by the Federa... C.B. De faria, L. Gebler, L. De ross marchioretto, C.L. Bazzi |
2. Enhanced Deep Learning Framework Driven Grape Berry Temperature Estimation and 72-h Forecasting for Precision Heat Stress ManagementThe increasing frequency of extreme summer heat events poses a significant threat to grape production in the Pacific Northwest (PNW), U.S., and globally. Elevated temperatures can induce sunburn, accelerate organic acid degradation, and cause anthocyanin loss, ultimately reducing berry quality. Berry surface temperature (BST), which can exceed ambient air temperature by up to 15 °C, is a primary indicator of heat stress severity. However, BST dynamics are governed by complex, nonlinear th... |
3. Influence of Application Rate and Flight Orientation on Droplet Deposition by Remotely Piloted Aircraft (RPA) in ‘Gala’ Apple OrchardsApple production is a cornerstone of the fruit industry, with the ‘Gala’ variety holding a prominent position due to its commercial value. However, this cultivar is highly susceptible to apple scab (Venturia inaequalis), requiring application technologies of fungicides that ensure canopy protection, especially during flowering. In this sense, precision horticulture has sought alternatives to optimize the application of crop protection products, aiming to ... L. Espindola müller, T. Buchener, B. Nogueira, R. Silva, S.J. Silveira, C. Bredemeier |
4. Applying Precision Agriculture Principles to Assess Spatial Variability of Soil Fertility Profiles in Coffee Farms at a Regional Scale.In the last two decades, the development and increasing efficiency of Precision and Digital Agriculture technologies has been observed in a broad range of farming systems. One of the consequences of this was the popularization of digital data collection, resulting in the current scenario where agricultural companies usually have large georeferenced databases concerning climate, soil and plant traits. These datasets are also produced by agricultural cooperatives such as the Cooxupé (Reg... H.F. Gebler, B.R. Silva costa, J.P. Molin |
5. Evaluation of an Ai-Driven High-Precision Spraying System for Targeted Weed Control in OnionsWeeds are a persistent challenge in the Vidalia onion production region, where limited herbicide options make placement and selectivity critical. AI-based high-precision spraying systems may reduce herbicide use and crop injury by targeting only weeds and non-crop areas. This study compared the Ecorobotix ARA high-precision sprayer operating in an all-but-the-crop mode with a conventional broadcast application for weed control, crop phytotoxicity, and onion performance. A field trial was cond... R. Dos santos, L. Oliveira, L.D. Sales, M. Barbosa, C.T. Tyson |
6. 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 spr... R.P. Oliveira, J.P. Silva, J.V. Martins, R. Dos santos, M. Barbosa, L. Oliveira |
7. Non-destructive Detection of Herbicide Damage in Curly Lettuce Using Spectral Data and Machine Learning AlgorithmsCurly lettuce (Lactuca sativa var. crispa) is a prominent horticultural crop due to its high demand for both production and human consumption. It plays a vital role in creating healthier, more balanced diets. However, the application of phytosanitary products, such as herbicides, whether applied by air or land, can lead to chemical drift into adjacent areas, negatively impacting sensitive crops. This drift can cause phytotoxicity and, in severe cases, result in total crop loss, depending on f... F. Morlin carneiro, T. Vidigal maciel, G. Albuquerque araujo, H. De oliveira cavalheiro, B. Matwijou, M.A. Da silva, A. Lopes de brito filho, M.G. Da silva brochado, J.D. Rodrigues oliveira |
8. Temporal Variations in Leaf Nutrient Concentrations and Photosynthetic Nutrient Use Efficiency in DurianThis study assessed leaf nutrient concentration in durian leaves and evaluated the photosynthetic use efficiency of nitrogen (N), phosphorus (P), and potassium (K) on durian trees over two fruiting seasons. This study also provided nutrient recommendations for durian fertilization using the Diagnosis and Recommendation Integrated System (DRIS) and optimal nutrient management range. A total of 63 mature trees were selected for leaf sampling. All samples were collected at two growth stages in e... M.F. Omar, S.K. Balasundram, N.E. tajidin |
9. A New Method for Yield Mapping in Commercial Wine Grape Vineyards of CaliforniaVariable rate management (VRM) has been slow to advance in wine grape vineyards, in part due to the lack of commercially available implements or solutions capable of reacting to within vineyard variability. However, the lack of yield maps in vineyards constrain growers’ ability to understand the return on investment, making the cost of VRM difficult to justify. Previous yield monitors mounted on the discharge belts of mechanized grape harvesters were difficult and costly to maintain. A ... B. Sams, M. Aboutalebi |
10. Soil Factors Affecting Severity of Verticillium Wilt in Kiwifruit (Actinidia Deliciosa)Verticillium wilt, caused by the soil-borne fungal pathogens Verticillium albo-atrum and V. dahliae, represents a highly destructive vascular disease in kiwifruit, with pronounced impact on gold kiwi (Actinidia chinensis). The disease manifests as acute wilting, shoot dieback, foliar necrosis, and, in severe cases, complete plant mortality. Conversely, green kiwi (Actinidia deliciosa) exhibits greater resistance to Verticillium wilt; while the disease does not typically cause vine death, it a... H. Poblete, R.A. Ortega, M.M. Martinez, I. Ortega |
11. Economic Assessment of Soil Sampling Densities for Variable-Rate Fertilizer PrescriptionSoil sampling and laboratory analysis represent a substantial share of operational costs in precision agriculture, making sampling density a crucial management parameter. Sampling density defines the resolution at which soil spatial variability is captured and directly influences the accuracy of spatial interpolation and fertilizer prescription maps. Due to high operational costs, reduced sampling densities are commonly adopted in practice, despite their known effects on map quality. This stu... L. Delgado bejarano, B. , A. Novaes da silva, L.R. Amaral |
12. A Simplified Optical Sensor-Based Approach for Variable Rate Nitrogen Recommendation Using Vegetation Indices and Yield PotentialVariable rate nitrogen (VRN) management using active optical sensors has been widely studied as a strategy to improve nitrogen use efficiency and reduce environmental impacts. Most current methodologies are based on complex multi-step models that estimate in-season yield from vegetation indices, crop stage and multiple equations, which often results in unrealistic yield predictions and limits adoption by farmers and consultants. This study presents a simplified and robust approach for VR... F. Povh, L.M. Gimenez, L.S. Flugel |
13. A Commercially Feasible Approach to Estimating Spatially Varying Plateau Functions with On-Farm Experiment DataAs technology in precision agriculture continues to advance, unprecedented volumes of high-resolution agronomic data are now available across years, farms, and regions. The availability of this data creates opportunities to improve both the economic and environmental performance of crop production through variable-rate nitrogen (VRN) recommendations tailored to site-specific yield response. However, widespread adoption of VRN remains elusive, in part because existing algorithms are either too... W.H. Duncan, W. Brorsen |
14. Variable Seeding Rate to Manage Within-field VariabilityWithin-field variability can strongly influence final crop yield and the efficiency of agricultural inputs such as seeds, fertilizer, water, and agrochemicals, thus managing spatial variability through precision agriculture to optimize input use and improve sustainability can yield significant gains, provided that the mechanisms driving field variability are understood. Despite extensive research on the relationship between seeding density and yield, relatively little attention has been given... B. Maestrini, L.P. Pott, D. Bamberg, T. Liska, T. Rosado, L. Sander, T. Ruiz moreno, N. Garcia dutrez, F. Doeler, T. Van der wal, V. , T. Amado, Nieuwenhuizen |
15. Impact of Soil Heterogeneity and Precision Air Seed Drill Settings on Maize Emergence Uniformity: Toward Sensor-based Predictive ModelsSoil spatial heterogeneity at the intra-field scale strongly constrains crop establishment. This heterogeneity in soil texture, strength, and moisture often leads to uneven seed-soil contact and inconsistent emergence, reducing yield potential. Extreme climatic conditions, such as soil saturation or drought, amplify these challenges and further compromise uniform crop emergence. Although this issue is widely acknowledged, accounting for soil h... A. Veiga, H. De araujo, L. Tetard, M. Faucon, C. Ugarte |
16. Evaluating Response-Based Management Units for Variable-Rate Nitrogen Application Using On-Farm ExperimentsSite-specific nitrogen (N) management in precision agriculture is commonly based on management zones derived from soil properties and vegetation indices, implicitly assuming that spatial patterns in yield potential correspond to spatial patterns in crop response to N. However, yield level and marginal yield response to N represent distinct agronomic characteristics and may not coincide. This study evaluates whether conventional potential-based zones adequately capture spatial variability in N... C. Matavel, A. Meyer-aurich |
17. Integrating Variable Rate Nitrogen Fertilization and Traffic Intensity Thresholds for Site-Specific Management in Mechanized Sugarcane SystemsPrecision Agriculture (PA) has primarily focused on site-specific input management to improve resource-use efficiency; however, in highly mechanized cropping systems, soil physical degradation induced by machinery traffic remains a critical constraint to system performance. This study integrates two complementary approaches developed in commercial sugarcane production systems in Colombia: (i) variable rate nitrogen fertilization (VRT) as a strategy for rational fertilizer use, and (ii) a maxi... O. Chaparro anaya, S. Saavedra rincon |
18. The Agronomic and Bioeconomic Aspects of Site-Specific Seeding Rates and Depths for Winter Wheat in LithuaniaPrecision seeding is one of the most important agrotechnological solutions for smart agriculture. It exploits the variability of soil properties in the field to increase the agronomic and economic efficiency of crops. This study investigated the impact of site-specific seeding (SSS) on the yield and productivity parameters of winter wheat in Lithuania, as well as its economic benefits, compared with conventional uniform rate seeding (URS). Experiments were conducted in a field divided into fi... Z. Kriauciuniene, M. Kazlauskas, K. Romaneckas, S. Buragiene, I. Bručienė, E. Šarauskis |
19. Do Precision and Climate Concerns Shape Fertilizer Usage Proportions? Evidence from DenmarkFarmers are constantly facing pressure to enhance crop productivity while minimizing environmental and climate impacts through efficient input management. In Denmark, because of concerns over nitrogen leaching, greenhouse gas emissions, and water quality degradation, there are tight regulations to fertilizer use. This makes precision farming technologies a key to the efficient management of nutrients through site-specific input application based on crop and soil variability. However, adoption... N. Yenibehit, S.M. Pedersen, T.W. Tamirat |
20. Effect of Post-processing on the Performance of Clustering Algorithms for Delineating Management Zones for Precision Soil SamplingSoil nutrient variability directly influences crop yield; therefore, site-specific management requires maps that can depict variability within the fields. Here, management zone (MZ) approaches have been used, typically derived from clustering analyses applied to low-cost environmental variables. There is still no consensus on zone delineation strategies that maximize the reduction of soil variability, nor on the relative performance of clustering algorithms. Moreover, post-processing of... D.D. Melo, L.R. Amaral, L. Bastos, S. Virk |
21. Cotton Yield Response to Seed Density in Contrasting Productive Potential ZonesABSTRACT: Brazilian cotton farming has high economic and agricultural importance. However, it faces challenges related to management practices that consider the spatial variability of productivity across different yield potential zones within a field. In this sense, precision agriculture tools have great potential to optimize and rationalize input use in areas with spatial variability in productive potential, especially through the use of variable rate seeding. Nevertheless, ... G. , C. Bredemeier, R. , D. |
22. 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 ... G.V. Bedum, A. Colaço, M. Gelain, R. Canal filho, J.P. Molin, E. Otavio da silva |
23. Seeing What Sampling Misses: Integrating High-Resolution pH, Compaction, and EC Sensing for Improved Soil ManagementTraditional laboratory soil sampling remains foundational for nutrient measurement and provides reliable chemical analysis at the point of collection. However, the combined cost of laboratory analysis and labor-intensive sample collection often constrains sampling density, resulting in maps that are accurate at discrete locations but interpolated across large unsampled areas. In addition, laboratory testing primarily characterizes chemical properties and does not often measure physical soil c... E. Lund, C.R. Maxton, T. Lund |
24. Silage Corn Production Under Different Management Strategies: Conventional and 4.0Agriculture 4.0 has emerged as a strategic tool to maximize operational efficiency and environmental sustainability in agricultural production. The integration of telemetry, automation, and spatial data analysis facilitates more precise management, reducing input waste and enhancing production predictability relative to traditional methods. In this context, the objective of this study was to evaluate the impact of adopting Agriculture 4.0 technologies on the agronomic performance and producti... F. Aguiar jordão, D.J. Santos, G.D. Dalevedo, L.A. Gaion, I.M. Pascoaloto, E. Fernandes, J. , T.F. Lemos |
25. Agronomic and Economic Performance of Early Maize and Weed Management Under Agriculture 4.0 versus Conventional SystemsAgriculture 4.0 stands as a crucial strategy to optimize operational efficiency and environmental sustainability in maize cultivation, enabling rationalized input use through automation and data management. However, limited comparative data exist regarding its agronomic efficacy against conventional practices under tropical conditions. Thus, this study aimed to compare vegetative development and weed infestation in conventional and Agriculture 4.0 cropping systems. The experiment was conducte... P. Colleta de abreu moral, L.A. Gaion, C.C. Gaspareto filho, I.M. Pascoaloto, E. Fernandes, J. , T.F. De lemos |
26. Evaluating the Potential Benefits of Variable-rate Sulfur Management in Minnesota Corn Using Machine-learning AnalysisSulfur (S) management in corn is complicated by strong within-field variability in crop response, driven by interactions among soil properties, landscape position, and prior management. As a result, uniform S applications can create unnecessary input costs in nonresponsive areas while undersupplying responsive zones. We developed and demonstrated a practical machine-learning (ML) workflow to estimate within-field agronomic optimum sulfur rate (AOSR) and economic optimum sulfur rate (EOSR) on ... R.P. Negrini, Y. Miao |
27. Less Nitrogen, Same Yield: Evidence from 45 Site-Years of Sensor-Based Maize Nitrogen Management in the U.S. MidwestImproving nitrogen use efficiency (NUE) while maintaining maize productivity remains a central challenge for irrigated corn systems in the U.S. Midwest. Sensor-based, in-season nitrogen (N) management has been around for many years. Yet, US Midwest farmers reported that a lack of information about the value of this approach and fear of yield loss when reducing the N rate were the top barriers to adoption. In-season N management enables better synchronization of N supply with crop demand, yet ... G. Balboa, P. Paccioretti, J.D. Luck |
28. Sensor-based Variable Rate Nitrogen Recommendations: Comparing Proximal, Drone, and Satellite Sensors in CornNitrogen (N) represents 20–25% of corn (Zea mays L.) production costs, yet 15–65% is lost through volatilization and leaching. Conventional uniform-rate application ignores spatial variability and seasonal demand. Sensor-based variable rate nitrogen (VRN) addresses this by using real-time reflectance data, but the influence of sensing platform proximal, drone, or satellite on economic outcomes under varying N stress remains under-researched. The objective of this study at Iron Hor... A. Jakhar, L. Bastos, A. Bhattarai, K. Poudel, A. Dhaliwal |
29. Evaluation of Variable and Uniform Rate Prescriptions of Potassium Fertilizing for Small Plots in Family-run Coffee FarmsBrazil plays a central role in the global coffee supply as one of the primary providers for strategic international markets. As extreme weather threats, prolonged droughts, and international agricultural commodity price volatility increase, enhancing economic efficiency in input use has become fundamental for the sustainability and resilience of coffee production systems. Thus, efficiency in the use of agricultural inputs transcends economic concerns, becoming part of the broader discussion o... N. De s. ludovico almeida, B.S. Costa, J.L. Favarin, J.P. Molin |
30. Enhancing Corn Management with Variable Rate Fertilizer Maps: A Spatial Evaluation of Cover CropsFarmers and agronomists need accurate, efficient methods for evaluating cover crop (CC) biomass and nutrient content to optimize fertilization strategies and improve soil health. Traditional biomass assessments are labor-intensive and time-consuming, often delaying timely data-driven management decisions. While multispectral cameras, including near-infrared (NIR) and RedEdge sensors, provide high-accuracy data for this purpose, their high cost limits accessibility for many farmers. This study... |
31. Systematic Multi-criteria Assessment of Soil Analysis Technologies for an Agricultural Living Lab: Readiness Levels and Field Applicability for Citrus and Sugarcane ProductionPrecision Agriculture (PA) fundamentally depends on accurate and timely edaphic diagnostics for site-specific decision-making. Within the scope of the Smart B100 Advanced Research Center (CCD-SB100/IAC), funded by FAPESP, an agricultural Living Lab is being structured. While the project's initial focus includes citrus and sugarcane in São Paulo State, the foundational soil sensing technologies evaluated are crop-agnostic. Currently, traditional laboratory methods for soil analysis ... J. Sanches , H. Fischer, M.C. De almeida, C.K. Luvizzoto, C.E. Otoboni |
32. Assessing Soil Fertility Inequality at Regional Scale to Support Plot-level Site-specific ManagementIn accordance with Precision Agriculture (PA) principles, site-specific management could be performed in small-scale farming systems, assuming a cell-size approach where between-plot variability is manageable, rather than the within-plot variability. This framework is particularly useful for fertilization strategies within a single farm and may be extended to a macro scale when georeferenced datasets from multiple plots and farms across a region of interest are available. However, when dealin... B. Costa, B.B. Barreto, H. Fantin gebler, J.P. Molin |
33. Evaluating On-Farm Variable Rate Seeding Trials with Causal Inference and Machine Learning.Identifying field-specific economically optimal seeding rates (EOSR) is central to profitable crop production, yet conventional analytical approaches applied to on-farm trial data frequently conflate association with causation, limiting their utility for generating actionable site-specific management recommendations and constraining broader adoption of variable rate seeding (VRS) technology. Mixed-model ANOVA and quadratic response surface methods calculate a single average EOSR, masking spat... B. Adeyemi, Y. Miao, A. Kechchour |
34. 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 r... G. Kaefer seganfredo, L.G. Kern, L. Silveira pavão, A. Müllich, I. Maldaner, J. Sgarbossa, L. , E. Rolim farias da silva, M.S. Farias |
35. Evaluation of DC-based Equipment for Apparent Soil Electrical Conductivity MeasurementApparent soil electrical conductivity (ECa) is a soil parameter used for precision agriculture applications where the knowledge of spatial variability of soil attributes is one important aspect to be known. Researchers have concluded that ECa is a powerful for spatial heterogeneity characterization of several physico-chemical properties, identify edaphic and anthropogenic factors that may influence crop yield, and provides a viable approach for delineating areas ... R. Zandonadi, S.C. Rosa, D.S. Valente |
36. Spatial Variability of Foliar Nutrient Contents in a Vineyard of the Campanha Gaúcha RegionLeaf analysis is an essential tool for understanding nutrient availability, absorption, and redistribution processes in plants, providing technical support for decision-making in precision viticulture systems. The spatial variability of nutrient contents in leaf tissue is associated with soil heterogeneity, topographic conditions, and vineyard management practices. The objective of this study was to evaluate the spatial variability of macronutrients in grapevine leaf tissue, identifying distr... R. Balsamo brondani, B.T. Paese, J.M. Moura-bueno, A.A. Kokkonen, G. Brunetto |
37. As-applied Maps of Planter Performance During Corn Planting – How the Numbers Looks Like After Plant EmergenceHigh-quality planting operations are important for high yield crops. Poor distribution compromises emergence and plant development, thus affecting crop productivity. Therefore, uniformity of seed distribution in the soil, with adequate depth and spacing, is essential for high yield. Moreover, embedded electronics on modern planters allow data collection from sensors that provide information regarding planter performance such as measurements of seed spacing quality (doubles, skips, singularity... D. Ferreira dos santos, S.C. Rosa, R. Zandonadi |
38. On-farm Precision Experimentation in Western Canada: A Case Study Focused on Adoption, Challenges, and Practical ResultsOn-farm experimentation can improve management practices by providing localized results that align with the environment, genetics, and management of a specific field, farm, or region. However, operational challenges, such as the time required to implement and harvest an experiment and analyze results, can be barriers to adoption. The technology available in modern machinery (e.g., variable-rate technology and yield monitors) can overcome operational challenges by autonomously implementing and... F. Hoffmann silva karp, B. Bateman, H. Simons, J. Boychyn |
39. Development and Field Validation of SMART-C: A Geostatistics and PCA-Based Decision Framework for Site-Specific Cocoa Management in the Brazilian AmazonCocoa production plays a major socioeconomic role in Pará State, Brazil’s largest producing region, with annual output exceeding 140 thousand tons. Although Brazil ranks among the world’s leading cocoa producers, most production systems are still managed using field-average approaches that disregard within-field spatial variability of soil attributes and crop performance. This limitation restricts input efficiency and long-term system sustainability in perennial tropical sy... |
40. Agroclimatic and Topographic Zoning for the Sustainable Expansion of Peanut Production in the State of Georgia, USASustainable agricultural production depends on a detailed analysis of environmental conditions to support decision-making. This study aimed to develop a topoclimatic zoning for peanut production in Georgia, USA, using climatic data from the PRISM Climate Group and topographic data from OpenTopography. The water deficit was calculated using the Thornthwaite and Mather methodology. The methodology included the reclassification of variables into three suitability classes for cultivation, based o... I. De oliveira vieira, S. Luns, R.C. Mendes, L. Bastos, R.P. Silva |
41. Evaluation of Kriging Models and Variogram Structures for Daily Weather Interpolation Across Georgia, United StatesSpatial interpolation fills gaps between scattered weather stations to create continuous maps of variables like temperature. In Georgia, USA—a state with rolling hills in the north, coastal plains in the south, and the Appalachian foothills—this process is vital for accurate climate monitoring, irrigation scheduling, and crop-yield forecasting. Without reliable grids, downstream models suffer from bias or uncertainty. This study aimed to a... |
42. To Mist or Not to Mist: Using Site-Specific Sensed Data to Evaluate Infrastructure Needs in a VineyardThis study explores the use of high-resolution site-specific data to understand how sensors can impact infrastructure purchases in a real-world precision agriculture growing operation. Since 2023, over 60 sensors have been deployed at Laurel Grove Wine Farm, a vineyard in Winchester, Virginia, including information on weather (temperature, humidity, sunlight, and rainfall) and soil (moisture content and pH). The Sensor Collection and Remote Environment Care Reasoning Operation (SCARECRO) syst... M. Everett, K. Wing, D. Onyeoguzoro, D. Mommen, J. Shovic |
43. An AI-Ready Smart Adapter Architecture for Integrating Heterogeneous Agricultural IoT Systems Across the Edge–Cloud ContinuumThe increasing adoption of Internet of Things (IoT) technologies in smart agriculture has resulted in highly heterogeneous environments composed of diverse sensors, communication protocols, and distributed computing layers. Agricultural systems typically operate across the edge–cloud continuum, encompassing field devices, intermediate processing nodes, and cloud-based platforms. While IoT platforms provide essential services for data ingestion and device management, they often face limi... D. Silva, A. Heideker, R. Bianchi, C. Kamienski |
44. Autonomous Edge Computing Station for Precision Soil and Climate Monitoring in Remote and Low-Connectivity EnvironmentsThe expansion of Precision Agriculture (PA) into remote rural areas, particularly in developing countries like Brazil, is frequently hindered by severe infrastructure constraints. Large-scale adoption of digital tools faces the dual challenge of limited 4G/5G connectivity at the field level (the "talhão") and the high costs associated with conventional electrification and industrial-grade equipment. These barriers disproportionately affect small and medium-sized farmers, crea... M. Andrade, R. Toledo |
45. Scalable Offline Infrastructure for Agriculture 4.0: A Linux-Gateway Architecture for Edge Connectivity and Data SovereigntyBrazilian agribusiness has consolidated itself as an economic pillar, representing approximately 25% of the national GDP. However, the full rise of Agriculture 4.0 - characterized by the integration of IoT, Artificial Intelligence, and smart sensors -faces a scenario of profound technological inequality. Recent data indicate a disparate adoption of digital tools: while large-scale farms possess the financial capacity for complex infrastructures, small and medium-sized producers face connectiv... M. Andrade, C. Soares de souza |
46. Development of a Label-free Electrochemical Biosensor for Detection of Infectious Hepatitis a VirusOne of the leading causes of foodborne viral illnesses in the world is Hepatitis A Virus, which is frequently involved in causing outbreaks linked to contaminated produce and shellfish (e.g., green onions and berries) due to contamination during cultivation, processing, or handling. HAV is highly stable in environment capable of remaining infectious on food matrices and in water for extended periods. Humans get infected primarily via the fecal-oral ro... D. Kaur, R.P. Ramasamy, M. Esseili |
47. A Decentralized Digital Twin Architecture for Interoperable Digital Agriculture SystemsThe increasing digitalization of agriculture has driven the widespread adoption of heterogeneous sensing systems, autonomous platforms, and data-driven decision-support tools. Despite these advances, interoperability limitations at both the syntactic and semantic levels remain a major challenge, hindering the scalable integration and coordinated operation of agricultural assets. Current agricultural systems are often developed as vertical, vendor-specific solutions, resulting in fragment... P.H. Morgan pereira, G. Costa piazza, K. Usman, L. Santos comelli da silveira, V. Cella ceriotti, Y. De souza pazin, E. Pignaton de freitas |
48. Development of a LoRaWAN Network for Remote Sensing in Precision AgricultureThe modernization of agriculture through Agriculture 4.0 requires the use of advanced sensors and wireless communication networks for the precise monitoring of environmental variables and process optimization. However, the implementation of these Internet of Things (IoT) technologies in rural areas frequently faces the challenge of limited infrastructure over large territorial expanses. In this scenario, Low-Power Wide-Area Networks (LPWAN), specifically the LoRaWAN protocol, stand out for th... M. Hermes, M. Albuquerque, A. Andreoli, C. , C. Chaves |
49. Satellite-IoT Integration for Digital Agriculture: Advances and ChallengesAgriculture is an essential pillar of global food security, demanding continuous digital integration from seed selection and planting to post-harvest logistics and crop distribution. In this scenario, seamless communication is the primary enabler for data-driven decision-making, ensuring that critical information regarding environmental variables, soil moisture, and direct plant health indicators reaches processing platforms fast enough for agile operational responses. However, the expansion ... M. Feldman, O.R. Da cruz, N.K. Wagner, C. Glier, I. Müller |
50. Application for Pixel-level Segmentation and Quantification of Lignified Fibers (Sclerenchyma) and Parenchyma in Microscopic Images of Sugarcane CulmsQuantifying lignified tissues in sugarcane culms (Saccharum spp.) is essential for anatomical characterizations and for inferences related to biomass quality and the potential uses of plant material. Conventional methods may require specific laboratory procedures and manual steps in digital analysis, increasing processing time and reliance on skilled operators. In this context, computer vision techniques applied to microscopic images constitute an accessible and reproducible alternat... G.F. rubio, J.F. Rubio, L.E. Pereira, J.R. Marques, A.R. Tech, M.F. Logli |
51. Evaluation of Variable-Rate Application of Growth Regulator in CottonThe application of plant growth regulators in cotton is widely used to control excessive vegetative growth and improve plant architecture. However, the spatial variability present in agricultural fields may reduce the efficiency of conventional fixed-rate application, making variable-rate application (VRA) a promising alternative. The objective of this study was to evaluate the effect of fixed-rate and variable-rate application of the growth regulator mepiquat chloride on plant height, leaf a... B. Costalonga vargas, M.R. Furtado junior, G.O. Paula, A.L. Coelho, M.C. Moreira, F.R. Carvalho |
52. An Open-Source, Universal Arduino Library for LoRaWAN Integration with Low-Cost, Long-Range Agricultural Sensor NetworksThe Data-Gator is a low-cost, open-source sensor platform built on the ESP32 microcontroller. It supports I2C, analog, and Bluetooth Low Energy (BLE) sensor interfaces and can be configured without writing any code. It has been tested at a vineyard and an organic orchard, where it collects readings from a number of sensors at regular intervals. While the platform performs well in these settings, it currently relies on WiFi to send data back from the field. This l... K. Wing, D. Onyeoguzoro, M. Everett, J.C. Shovic |
53. Use of Profitability Maps in Precision Agriculture As a Strategic Tool for Decision-makingBrazilian agribusiness plays a significant role in the national economy, accounting for approximately 27% of the Gross Domestic Product, while operating in an environment characterized by substantial exposure to climatic, operational, and market risks. In commodity-based production systems, where farmers act as price takers, economic efficiency fundamentally depends on effective cost and revenue management, as well as the proper allocation of productive resources. In this context, this study ... W. Nart macedo, L. Gebler |
54. Economic and Ecological Performance and Farm-level Adoption of Market-available Tools for Variable-rate Nitrogen Management in a Region of Small-to-medium-scale AgricultureThe proposed contribution combines the results of extensive multi-year field trials on variable rate-nitrogen fertilization (VRN) of winter wheat with the results of a series of farmer surveys, and findings drawn from a government investment subsidy program. All three data sources (field trials, surveys, investment subsidy program) cover roughly the same period and agricultural area. The field trials were conducted from 2023 to 2025, the surveys in 2020, 2022, and 2025, and data on the invest... M. Gandorfer, B. Vinzent, J. Pfrombeck, J. Garnitz, F. Maidl |
55. Farm-level Economic Viability Site-specific Weed Management (SSWM)Background: Site-specific weed management (SSWM) is promoted as a strategy to reduce herbicide inputs without compromising crop yield. Despite rapid advances in offline and online AI-based weed mapping, the farm-level economic viability of SSWM under real-world weed patchiness and imperfect detection remains uncertain. Methods: A grid-based (1x1m, 50x50cm and 25x25cm) economic decision model for SSWM was developed and evaluated using 31 empirical weed... M. Gandorfer, J. Pfrombeck, V. Pitsyk, D. Pannell |