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| Filter results26 paper(s) found. |
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1. Technological Improvement on Sugar Cane Yield MonitorThis paper presents the technological improvement on sugar cane yield monitor. The system designed employs load cells as an instrument for weighing billets, set up on the side conveyor of the harvester before the sugar cane billets are dropped into a field transport wagon. This data, along with the information gathered by GPS installed on the harvester, enabled the elaboration of a digital yield map using GIS. In order to improve the yield monitor a re-design of the first prototype was accomp... D.G. Cerri, G.R. Gray, P.S. Magalhães |
2. A Tree Planting Site-Specific Fumigant Applicator for Orchard CropsThe goal of this research was to use recent advances in the global positioning system and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in the neighborhood of each tree planting site or tree- planting-site-specific application) to decrease the incidence of replant disease, and achieve the environmental and economical benefits of reducing the application of these toxic chemicals. In the first year of this study we retrofitted a chemical applicato... S.K. Upadhayaya, V. Udompetaikul, M.S. Shafii, G.T. Browne |
3. Correlations Between Meteorological Parameters and the Water Loss of Maize from Silking to HarvestingThe University of Debrecen provides outstanding conditions for the development of “Smart Weather for Precision Agriculture” programs. The reliability of research is provided by the Polyfactoral Long-term Field Experiments of Debrecen (hybrid x fertilisation x plant density x tillage x irrigation) established in 1983. Within this research program, it is possible to examine various crop cultures, cultivars and hybrids under changing natural, environmental and weather circu... K.B. Bodnár, J. Nagy, B. Gombos |
4. Managing the Kansas Mesonet for Site Specific Weather InformationWeather data has become one of the most widely discussed layers in precision agriculture especially in terms of agricultural ‘big data’. However, most farmers (and even other researchers outside of meteorology) are not likely aware of the complexities required to maintain weather stations that provide data. These stations are exposed to the elements 24/7 and provide unique challenges for sustainment during extreme weather conditions. Based upon decades of experience, this paper di... T. Griffin, C. Redmond, M. Knapp |
5. Grassland System Impacts on Spatial Variability of Soil Phosphorus in Eastern CanadaPhosphorus (P) is an essential nutrient for plants, including grasslands. However, continuous applications of P fertilizer result in P accumulations in the soil, increasing the risk of P losses through runoff and erosion. Since 2008, more than 31 million tonnes of organic fertilizers, representing more than 95,000 tonnes of P2O5, were applied to agricultural fields in Eastern Canada. Thus, grassland systems were fertilized intensively using organic fertilizers with high ... J.D. Nze memiaghe, A. Cambouris |
6. A Data Retrieval System to Support Observational Research of On-Farm ExperimentationObservational research is a powerful methodology, capable of rapidly identifying trends and patterns present in complex systems. New work seeks to apply these techniques to agronomic production systems. While data generated from on-farm experimentation are often considered anecdotal, these data hold significant importance for farmers because they originate from their distinctive agricultural systems. Combining the large volumes of farmer-collected data with remote sensing, environmental, and ... P. Lanza, A. Yore, L. Longchamps |
7. Yield Potential Zones and Their Relationship with Soil Taxonomic Classes and Management ZonesThe use of management zones (MZ) to subdivide agricultural areas based on the variability of yield potential and production factors is increasingly being explored by scientific research and demanded by farmers. However, there is still much uncertainty about which layers of information and procedures should be adopted for this purpose. Thus, our goal was to demonstrate whether simplistic approaches to creating MZ can satisfactorily address the variability of yield potential and soil classes. F... L.R. Amaral, H. Oldoni, D.D. Melo, N.A. Rosin, M.R. Alves, J.M. Demattê |
8. Precision Agriculture: Forage Chopper Noise Level As an Estimator of Corn Silage Production in Small FarmsThe objective of the work carried out in the Registro County, SP, Brazil, in the year 2021, was to study the forage chopper noise level as an estimator of corn silage production in small farms. The corn crop study and characterization were measured plant height (PH), height of first ear insertion (HEI) and green mass production of plants (GM) were studied. The noise (NO) produced by the forage machine during ensiling was collected by recording, considering it as a potential yield estimator du... W.J. Souza, A.N. Silva |
9. Securing Agricultural Data with Encryption Algorithms on Embedded GPU Based Edge Computing DevicesSmart Agriculture (SA) has captured the interest of both the agricultural business and the scientific community in recent years. Overall, SA aims to help the agricultural and food industry to avoid crop failures, loss of revenues as well as help farmers use inputs (such as fertilizers and pesticides) more efficiently by utilizing Internet of Things (IoT) devices and computing systems. However, rapid digitization and reliance on data-driven technologies create new security threats that can def... M. Alahe, J.O. Kemeshi, Y. Chang, K. Won, X. Yang, M. Sher |
10. Increasing the Resilience and Performance of AI-based Services Through Hybrid Cloud Infrastructures and the Use of Mobile Edge in AgricultureAgriculture, as an essential part of food production, belongs to the Critical Infrastructures (CRITIS). Accordingly, the systems used must be designed for fail-safe operation. This also applies to the software used in agricultural operations, which must meet security and resilience criteria. However, there is an increase in software that requires a permanent Internet connection, i.e., a stable connection to servers or cloud applications is required for operation. This represents a significant... D. Eberz-eder |
11. Developing Geospatial Method for Autopilot Harvester Trampling Evaluation in Colombian Sugarcane FieldsSugarcane is a crop of great importance for the geographical valley of the Cauca River in Colombia, where it covers approximately 241,000 hectares and is cultivated by 13 sugar mills and about 4,200 cultivators. This region is characterized by its favorable climate, which enables year-round sugarcane harvesting and its high productivity, making it a global leader in this sector. This achievement is largely attributed to the technological advances developed by Colombia Sugarcane Research Cente... J.D. Ome narvaez, D.F. Sandoval, S.A. Galeano, H.B. Tarapues, A. Estrada, J.P. Zuñiga, J.M. Valencia-correa |
12. Soybean Production Components As Indicators of Soil Variability As a Subsidy for Precision AgricultureThe soil variability in its physical, chemical and biological parameters can be analyzed using direct methods applicable to each variable studied. Plant responses, manifested in the establishment of the final population, biomass production and grain productivity can reflect the soil conditions, associating them with the variability observed in the area. Localized soil management and the use of machines with variable rate applications, including drones for applications in specific sites, depen... E. Apolinário, W.J. Souza |
13. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, RiversideFunded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus |
14. Fostering Student Engagement and Leadership Development in Integrative Precision Agriculture Across BordersEfforts to advance integrative precision agriculture technologies are growing exponentially across the globe with the common interest of upholding food security and developing more sustainable food and fiber production systems. Countries such as the United States and Brazil are among the biggest crop producers in the world and will play an even bigger role in food security in the next decades. It is of utmost importance that countries can advance together to overcome future food production ch... L. Lacerda, A. Felipe dos santos, E. Bedwell, A. Jakhar, T.O. Costa barboza, M. Ardigueri |
15. Semiautomatization in Open Source Software of a Method for Monitoring the Land Cover Change with GEE and Sentinel-2Land cover change is a dynamic process that unfolds spatially and temporally. As such, it is imperative to develop semi-automatic methods within freely available software to enhance processing efficiency and reduce costs. The amalgamation of open-source applications, platforms, and software for satellite image processing has emerged as a compelling alternative, fostering advancements in land cover change classification and monitoring. This study introduces a semi-automated methodology using t... S.A. Rubaino sosa, Y. Rubiano, J.H. Bernal riobo |
16. Using the Open Data Farm As a Digital Twin of a Farm in an Innovative School Setting to Increase Data Literacy and AwarenessIn recent years, the number of digital applications and data streams has steadily increased, but knowledge and expertise in dealing with them has not increased to the same extent. The Open Data Farm is intended to make a significant contribution to education and training in order to increase data literacy in agriculture. The Open Data Farm (ODF) represents a twin of a real agricultural business as a 3D model in which existing data streams in various branches of the business are visu... D. Eberz-eder, E. Wölbert, J. Hinze, C. Weiß |
17. Use of Radar SAR Images to Assess Soil Moisture in Cane Crops: Practical Implications in Agricultural OperationSugar cane cultivation in the geographical region of the Cauca River Valley is a key industry for the local economy. However, this crop faces constant challenges related to the management of agricultural machinery for soil cultivation in conditions of high soil moisture. In this context, the synthetic aperture radar (SAR Radar) of the Sentinel 1 satellite emerges as a promising technology. The purpose of this work is to explore the use of the Sentinel 1 satellite SAR radar sensor in su... O.J. Munar-vivas, S. Anderson guerrero, D.F. Angrino chiran, J.F. Mateus-rodriguez |
18. Method to Optimize Soil Survey for Multiple Soil PropertyThe sugarcane production system in Colombia, spanning an area of 241,000 hectares in the geographical valley of the Cauca River, is recognized worldwide due to its high productivity, adoption of advanced technologies, and sustainable management. The natural soil and climate conditions in this region result in significant variability in the chemical and physical soil properties. Consequently, determining the soil variability is crucial to achieving its maximum productive potential through diff... D.F. Sandoval, D.F. Perdomo |
19. Avena: an Event-driven Software Framework for Informed Decisions and Actions in Cropping SystemsInteroperability is one of the enabling factors of real-time communications and data exchange between asynchronous data actors. Interoperability can be attained by introducing events to systems that extract data from consumed ground-truth event streams that utilize application-specific structures. Events are specific occurrences happening at a particular time and place. Event-data are observations of phenomena, or actions, as seen by different systems in Internet of Things (IoT) deployments, ... F.A. Castiblanco rubio, M. Basir, A. Balmos, J. Krogmeier, D. Buckmaster |
20. A Multi-level Filtering Approach for Yield Data Cleaning and Automated Analysis Using R ProgrammingIn the realm of on-farm studies, a recurring challenge surfaces in the form of disparities between field implementation and experimental design within Rx treatment plots. This disjunction underscores the critical need for intensive data cleaning and analysis to generate precise outcomes for the experiments. Complicating matters is the absence of readily available ground truth data for comparative analyses, making it particularly challenging to ascertain the extent of necessary data cleaning a... S. Vinod, J.D. Luck |
21. Using Remote Sensing to Quantify Biomass in AlfalfaSatellite images are a useful decision support tool to optimize management practices at on-farm scale. Based on this, the development of predictive tools to estimate pasture biomass can be a promising framework to determine the best cutting time, maximizing biomass without compromising yield parameters. Therefore, the main objective of this study was to develop a regression model that allows estimating a value of biomass to give as a recommendation to farmers. To collaborate in their decision... M.F. Lucero, A. Zajdband, C. Hernandez, I. Ciampitti, A. Carcedo |
22. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWANThe widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenti... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen |
23. Ohio State Food, Agricultural and Biological Engineering (FABE) Certificate Program for Digital Agriculture-moving from the Classroom to Online.Digital Agriculture encompasses Precision Agriculture, Precision Livestock Farming, Controlled Environment Agriculture, On-Farm Research, and Enterprise Agriculture. We started developing teaching modules focused on Precision Agriculture. To start with, we are creating a series of modules focused on Variable Rate Technology (VRT) and Variable Rate Application (VRA). These initial modules were distilled from existing for credit courses offered by FABE and other extension and professi... K. Trefz, J.P. Fulton, S.A. Shearer, R. Venkatesh |
24. The Ohio State University - Sponsor Presentation... J.P. Fulton |
25. University of Georgia's Institute for Integrative Precision Agriculture - Sponsor Presentation... R.P. Ramasamy |
26. University of Nebraska-Lincoln - Sponsor Presentation... J.D. Luck |