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1. Factors Related To Adoption Of Precision Agriculture Technologies In Southern BrazilThe adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin |
2. Assessing Definition Of Management Zones Trough Yield MapsYield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two methods... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan |
3. Measuring Height of Sugarcane Plants Through LiDAR TechnologySugarcane (Saccharum spp.) has an important economic role in Brazilian agriculture, especially in São Paulo State. Variation in the volume of plants can be an indicative of biomass which, for sugarcane, strongly relates to the yield. Laser sensors, like LiDAR (Light Detection and Ranging), has been employed to estimate yield for corn, wheat and monitoring forests. The main advantage of using this type of sensor is the capability of real-time data acquisition in a non-destructive way, previously... T.F. Canata, J.P. Molin, A.F. Colaço, R.G. Trevisan, P.R. Fiorio, M. Martello |
4. Sources of Information to Delineate Management Zones for CottonCotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this work... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin |
5. Prediction of Sugarcane Yields in Commercial Fields by Early Measurements with an Optical Crop Canopy SensorAs a grass (Poaceae), sugarcane needs supplemental mineral nitrogen (N) to achieve high yields on commercial production areas. In Brazil, N recommendations for sugarcane ratoons are based on expected yield and the results of N response trials, as soil N analyses are not a suitable basis for decisions on optimum N fertilizer rates under tropical conditions. Since the vegetative parts in sugarcane are harvested, yield components such as the number of stalks and stalk height are directly correlated... G. Portz, J. Jasper, J.P. Molin |
6. Optimum Spatial Resolution for Precision Weed ManagementThe occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves |
7. Yield Analysis in Sugarcane Harvesters Using Design of Experiments (DoE) MethodologyThe sugarcane crop is highlighted in national agribusiness, Brazil is the world’s largest producer of the plant, and the prospection of specialists is of strong growth for the next years. However, in order to increase productivity, technological interventions through of precision agriculture must be implemented. Among them, the management of inputs guided by yield spatial variability for otmizing production and income. This project approaches the implementation of the methodology of analysis... M.L. Da Silva, J. . Alves De Lima, A. Balbinot, J.P. Molin |
8. 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 |
9. 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 |
10. Assessing the Capability of Apparent Soil Electrical Conductivity to Replace Soil Texture in the Delineation of Management Zones: a Case StudyThe delimitation of management zones (MZ) depends on the appropriate selection of information layers used in the clustering process. Traditionally, soil physical attributes with greater temporal stability, such as texture, have been widely employed due to their direct influence on water retention and nutrient availability. However, the acquisition of soil texture data is generally costly, time-consuming, and based on point sampling. In contrast, apparent soil electrical conductivity (ECa) has... M. Gelain, L. De Goes Sterle, J.P. Molin |
11. 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 sensors,... M. Gelain, J.P. Molin, L. De Goes Sterle |
12. Artificial Intelligence for Management Zone Delineation: A Bibliometric Review (2008-2025)This bibliometric review aims to map research trends, key terms, and leading institutions in the use of artificial intelligence (AI) methods, with emphasis on Machine Learning (ML), Deep Learning (DL), and Neural Networks, applied to the delineation of management zones (MZs) in Precision Agriculture (PA). The analysis was conducted using the Scopus database, applying a structured search string to titles, abstracts, and keywords. Metadata were collected on September 26, 2025. The initial search... L. De Goes Sterle, J.P. Molin, R. Fray Da Silva |
13. 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 |
14. Machine Learning and Causal Analysis to Support Improved Crop Decision-makingWhile machine learning (ML) models, particularly Extreme Gradient Boosting (XGBoost) and Random Forest (RF), have demonstrated potential in generating accurate crop yield predictions, their practical adoption for on-farm decision support remains limited. A key challenge lies in their fundamentally associative nature, which, without additional tools, can reduce interpretability and diminish practitioner confidence. Explainable Artificial Intelligence (XAI) techniques like SHAP values address one... M. Chan Fu Wei, J.P. Molin, A. Colaço, L. Longchamps |
15. Generating Data Via Operational Monitoring of Backpack Equipment on Small FarmsThe Brazilian coffee industry, a global leader in production and exports, faces the challenge of increasing production efficiency to meet growing worldwide demand while preserving natural resources. Precision Agriculture (PA) offers essential tools for this data-driven sustainable intensification; however, its adoption in regions with rugged topography and by family-based growers is severely limited by the scarcity of accessible technologies, particularly for spatial yield measurement. The semi-mechanized... V. Ferraz, L. Mariotto Nabarro, R. Castanho Fernandes, B.B. Barreto, B. Ricardo Silva Costa, J.P. Molin |
16. Definition of Flight Height for Image Monitoring of Pupunha Palm CultivationThe use of Unmanned Aerial Vehicles (UAVs) associated with computer vision has expanded the applications of precision agriculture, especially in perennial crops that require detailed spatial monitoring. In the peach palm tree, the automated detection of clumps from aerial images is an efficient alternative to traditional methods, contributing to management and production estimates. Thus, the objective of this study was to evaluate the influence of flight height on the performance of YOLO... D.A. Botta De Siqueira, J.P. Molin, B.B. Barreto, M.L. Silva, P.R. Fiorio |
17. Harmonic Modeling of Coffee Biennial Bearing to Quantify Between-plot Variability: a Precision Agriculture Approach for Small-scale AgriculturePrecision Agriculture (PA) practices rely on detecting spatiotemporal variability within a plot to delineate subplots by pixels or by management zones (MZs). This paradigm has been assumed for large-scale plots, yet their adoption in smallholder systems, such as coffee crops under family-based agriculture, remains limited. In this context, within-plot variability is often less operationally relevant than between-plots divergency. Therefore, we assume each plot as a MZ and focus on manage them... J.P. Molin, B. Costa, B. Barreto |
18. 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 (Regional... H.F. Gebler, B.R. Silva Costa, J.P. Molin |
19. 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 |
20. 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 |
21. Co-registration of RGB UAV Orthomosaics Through a Semi-automated Affine Method Based on Ground Control Points and Phase Correlation ValidationUAV images are crucial for Precision Agriculture (AP) purposes which require the monitoring of spatial variability regarding plant growth, especially to assess variation at plant level over time in perennial crops, such as banana plantations. However, spatial misalignments between orthomosaics from different dates requires post-processing image matching, i.e., co-registration, to ensure reliable spatiotemporal variability analysis. This study proposes a method for the co-registration of RGB UAV... B.R. Costa, J.P. Molin, B. Barreto |
22. Individualization of Banana Canopies Using Multispectral Vegetation Index and the Watershed AlgorithmThe individualization of canopies in perennial crops is an essential step in precision agriculture, enabling plant counting, vigor monitoring, yield prediction, pest management, and harvest planning. Banana (Musa spp.), characterized by large leaves, closed canopy, and high biomass, presents specific challenges for automated segmentation. This study evaluated the performance of the watershed algorithm for canopy individualization, using different multispectral vegetation index, between... B.R. Costa, J.P. Molin, B. Barreto |
23. Accuracy Analysis of C/A Code-based GNSS Receivers in Kinematic ConditionPrecision agriculture has emerged as a strategic approach to optimize input use and maximize crop productivity. One of the key pillars of this practice is the collection of georeferenced data, essential for the monitoring and efficient management of cultivated areas. This report aims to compare the performance of different positioning signal reception technologies under dynamic conditions. Three C/A code navigation receivers integrated into smartphones, one conventional navigation GPS receiver,... S. Ribeiro, G. Sanches, C.N. Ricci, J. Regazzo, J.P. Molin |
24. Evaluation of Filtering Approaches and Spatial Relationships with Gaps in Sugarcane Yield MapsYield maps represent indispensable tools in Precision Agriculture for the quantitative and qualitative characterization of crops. However, data derived from yield monitors do not always reflect actual field yield, as they are subject to measurement errors, operational errors, and/or equipment malfunctions. The presence of such distorted information compromises analytical accuracy and, consequently, decision-making. Given this challenge, the present study aimed to evaluate the performance of filtering... Y. De Lacerda Barbosa, V. Ferraz, E. Rafael Otavio Da Silva, J.P. Molin |
25. Impact of Sampling Density on the Spatial Prediction of Soil Chemical Attributes Using Geostatistics and Machine LearningSoil sampling at high grid densities represents a significant economic barrier to the adoption of Precision Agriculture (PA) in Brazil. This study evaluates the trade-off between sampling density and interpolation quality by comparing geostatistical methods and machine learning algorithms. Three distinct approaches were statistically assessed: Ordinary Kriging (OK), Random Forest (RF), and the hybrid Random Forest Regression Kriging (RFRK). The analysis was conducted across six fields totaling... S. Ribeiro, H. Fantin Gebler, J.P. Molin, R.F. Da Silva |
26. 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 on... N. De S. Ludovico Almeida, B.S. Costa, J.L. Favarin, J.P. Molin |
27. 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 |
28. 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 dealing... B. Costa, B.B. Barreto, H. Fantin Gebler, J.P. Molin |
29. Challenges in Adapting Precision Agriculture to Specific Contexts in Latin America... J.P. Molin |
30. Panelist Question and Answers... J.P. Molin, D. Cammarano, S. Virk, B.V. Ortiz |