Proceedings
Authors
| Filter results37 paper(s) found. |
|---|
1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea CropThe software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc |
2. Spatial Variability Of Crop And Soil Properties In A Crop-livestock Integrated SystemThe knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the site specific application of lime and fertilizer. The objective of this work was to map and evaluate the spatial variability of the crop, soil chemical and physical properties. The study was conducted in 2 areas of 6.9 and 11.7 ha of a Typic Haplustox in Sao Carlos, SP, Brazil. The summer crops corn and sorghum were sowed together to the forage crop Brachiaria brizantha in the system of crop-pasture... A.C. Bernardi, C.R. Grego, R.G. Andrade, C.M. Vaz, L.M. Rabello, R.Y. Inamasu |
3. Management Of Remote Imagery For Precision AgricultureSatellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack |
4. Design Of A Data Acquisition System For Weighing LysimetersThe weighing lysimeter is an important tool for scientists to conduct... C. Zhang, X. Xue, L. Chen, W. Huang |
5. Automatic Soil Penetrometer Measurements And GIS-Based Documentation With The Autonomous Field Robot Platform BoniRobFor a sustainable agriculture, reliable measurements of soil properties and its interpretation are of highest relevance. Until today most of the measurements are carried out manually or by integrating off-line laboratories. Moreover, the number and density of measurement points is always an important aspect with respect to the statistical significance of the results. In this work a fully automatic measurement system has been developed and applied for the first time with free selectable... M. Göttinger, S. Hinck, K. Möller, A. Ruckelshausen, C. Scholz |
6. A Study On Diagnostic System Based On ISOAgLIB For Agricultural VehiclesNowadays the growth of the embedded electronics and communications has demanded the development of applications in agricultural machinery in Korean agroindustry. The root reason is that most of agricultural machineries produced in Korea does not apply international standard. Therefore, the incompatibility problem between hardware, software and data formats has become a major obstacle for exporting agricultural products made by Korea to the world. In... J. Moon, S. Kim, J. Lee, W. Yang, D. Kim |
7. Advances In Automating Individual Plant Care Of Vegetable CropsAutomation of individual crop plant care in commercial vegetable crop fields has increased practical feasibility and improved efficiency and economic benefit if a systems approach is taken in the engineering design to mechanization that incorporates precision planting techniques. In addition to the optimization in the biological productivity of crop plants when the spatial distribution of crop plants allows their uniform access to nutrients, water and light in an optimum utilization... M. Pérez ruiz, D.C. Slaughter |
8. Unmanned Aerial System Applications In Washington State AgricultureThree applications of unmanned aerial systems (UAS) based imaging were explored in row, field, and horticultural crops at Washington State University (WSU). The applications were: to evaluate the necrosis rate in potato field crop rotation trials, to quantify the emergence rates of three winter wheat advanced yield trials, and detecting canker disease-infection in pear. The UAS equipped with green-NDVI imaging was used to acquire field aerial images. In the first application,... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings |
9. Privacy Issues and the Use of UASs/Drones in MarylandAccording to the Federal Aviation Administration (FAA), the lawful use of Unmanned Aerial Vehicles (UAV), also known as Unmanned Aircraft Systems (UAS), or more commonly as drones, are currently limited to military, research, and recreational applications. Under the FAA’s view, commercial uses of drones are illegal unless approved by the Federal government. This will change in the future. Congress authorized the FAA to develop regulations for the use of drones by private... P. Goeringer, A. Ellixson, J. Moyle |
10. Developing UAV Image Acquisition System and Processing Steps for Quantitative Use of the Data in Precision AgricultureMapping natural variability of crops and land is first step of the management cycle in terms of crop production. Several methods have been developed and engaged for data recording and analyzing that generate prescription maps such as yield monitoring, soil mapping, remote sensing etc. Although conventional remote sensing by capturing images via satellites has been very popular tool to monitor the earth surface, it has several drawbacks such as orbital period, unattended capture, investment cost.... A. Tekin, M. Fornale |
11. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in BrazilGiven the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitrogen... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães |
12. Ownership and Protections of Farm DataFarm data has been a contentious point of debate with respect to ownership rights and impacts when access rights are misappropriated. One of the leading questions farmers ask deals with the protections provided to farm data. Although no specific laws or precedence exists, the possibility of trade secret is examined and ramifications for damages discussed. Farm management examples are provided to emphasize the potential outcomes of each possible recourse for misappropriating farm data. ... A. Ellixson, P. Goeringer, T. Griffin |
13. A Content Review of Precision Agriculture Courses Across the USKnowledge of what precision agriculture (PA) content is currently taught across the United States will help build a better understanding for what PA instructors should incorporate into their classes in the future. The University of Missouri partnered with several universities throughout the nation on a USDA challenge grant. Precision Agriculture faculty from 24 colleges/universities from across the U.S. shared their PA content by sharing their syllabi from 43 different courses. The syllabi were... D. Skouby, L. Schumacher, M. Yost, N.R. Kitchen |
14. Seeding and Planting Plots for Crop Performance Evaluation Using Gps-rtk Auto SteeringCrop performance evaluation plots are seeded both on and off the University of Nebraska West Central Research and Extension Center. Plots off the Center must match the producer’s rows for pesticide application, cultivation, ditching, irrigation, fertilization and any other operations performed in the fields. With row crops the producer blank-plants the plot area before we can follow up with planting the plots. This means that we have to wait for the producer to plant in the field. Blank-planting... R.N. Klein, J.A. Golus, A.S. Cox |
15. Plant and N Impacts on Corn (Zea Mays) Growth: Whats Controlling Yield?Studies were conducted in South Dakota to assess mechanisms of intraspecific competition between corn (Zea mays) plants. Treatments were two plant populations (74,500 and 149,000 plants ha-1), three levels of shade (0, 40, and 60%) on the low plant population, two water treatments (natural precipitation and natural + irrigation), and two N rates (0 and 228 kg N ha-1). In-season leaf chlorophyll content was measured. At harvest, grain and stover yields were quantified with grain 13C-discrimination... D.E. Clay, S.A. Clay, G. Reicks, D. Horvath |
16. Use of Farmer’s Experience for Management Zones DelineationIn the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this study... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães |
17. AgDataBox – API (Application Programming Interface)E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and plant... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli |
18. An On-farm Experimental Philosophy for Farmer-centric Digital InnovationIn this paper, we review learnings gained from early On-Farm Experiments (OFE) conducted in the broadacre Australian grain industry from the 1990s to the present day. Although the initiative was originally centered around the possibilities of new data and analytics in precision agriculture, we discovered that OFEs could represent a platform for engaging farmers around digital technologies and innovation. Insight from interacting closely with farmers and advisors leads us to argue for a change... S. Cook, M. Lacoste, F. Evans, M. Ridout, M. Gibberd, T. Oberthur |
19. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your BenefitsClimate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet |
20. Evaluation of HLB-Infected Citrus Rootstocks Using Ground Penetrating RadarCitrus production in Florida continues to decline steadily, since the arrival of Huanglongbing (HLB or citrus greening). HLB does not kill the tree, but HLB-infected trees become less productive. Since now, there is no cure for this disease. However, several strategies have been developed to manage and control HLB-infected citrus trees. We have developed and evaluated a heat thermotherapy system (short-term solution) for sustaining productivity of HLB-affected trees. This system heats the canopy... Y. Ampatzidis, M. Derival, S. Kakarla, U. Albrecht, X. Zhang |
21. soil2data: Concept for a Mobile Field Laboratory for Nutrient AnalysisKnowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields... V. Tsukor, C. Scholz, W. Nietfeld, T. Heinrich, T. Mosler , F. Lorenz, E. Najdenko, A. Möller, D. Mentrup, A. Ruckelshausen, S. Hinck |
22. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean YieldThe ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet |
23. GIS Web and Mobile Development with Interfaces in QGIS for Variable Rate FertilizationIn this paper we described the implementation of a GIS for Precision Agriculture for sugarcane crop in Colombia. An spatial equation for Variable Rate Fertilization Model was defined using as inputs estimated harvest data, nutrients in soil and fertilizer efficiently. Models for soil and harvest variability are also defined. A personalized plugin for precision agriculture was developed into QGIS software, there is the option of upload maps to a Web and mobile app using the Desktop software and... R. Cuitiva baracaldo, O. Munar vivas, G. Carrillo romero |
24. Real Time Precision Irrigation with Variable Setpoint for Strawberry to Generate Water SavingsWater is a precious resource that is becoming increasingly scarce as the population grows and water resources are depleted in some locations or under increased control elsewhere, due to local availability or groundwater contamination issues. It obviously affects strawberry (Fragaria x ananassa Duch.) production in populated areas and water cuts are being imposed to many strawberry growers to save water, with limited information on the impact on crop yield. Precision irrigation technologies are... J. Caron, L. Anderson, G. Sauvageau, L. Gendron |
25. On-Farm Experimentation and Decision-Support WorkshopThis 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta-analyses... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk |
26. Soil Moisture Variability on Golf Course Fairways Across the United States: an Opportunity for Water Conservation with Precision IrrigationFairways account for an average of 11.3 irrigated hectares on each of the 15,000+ golf courses in the US. Annual median water use per hectare on fairways is between ~2,800,000 and 14,000,000 liters, depending on the region. Conventional fairway irrigation relies on visual observation of the turfgrass, followed by secondary considerations of short-term weather forecasts, which oftentimes lead to “blanket” applications to the entire area. The concept of precision irrigation is a strategy... C. Straw, C. Bolton, J. Young, R. Hejl, J. Friell, E. Watkins |
27. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 DataIn recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães |
28. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 ImageryPasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães |
29. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate AnalysisHyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or pest disease detection. As sensing technology advances, measuring nutrient levels and disease detection also progresses. This study aimed to predict the levels of potassium (K) content in peach leaves with the new snapshot hyperspectral camera. The study was conducted at the Clemson University Musser Fruit Research Farm (Seneca, SC, USA, 34.61... J.J. Maja, M. Abenina, M. Cutulle, J. Melgar, H. Liu |
30. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-upThe concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta |
31. Functional Soil Property Mapping with Electrical Conductivity, Spectral and Satellite Remote SensorsProximal electrical conductivity (EC) and spectral sensing has been widely used as a cost-effective tool for soil mapping at field scale. The traditional method of calibrating proximal sensors for functional soil property prediction (e.g., soil organic matter, sand, silt, and clay contents) requires the local soil sample data, which results in a field-specific calibration. In this large-scale study consisting of 126 fields, we found that the traditional local calibration method had suffered weak... X. Xiong, D. Myers, J. Debruin, B. Gunzenhauser, N. Sampath, D. Ye, H. Underwood, R. Hensley |
32. HOPSY: Harvesting Optimization for Production of Strawberry Using Real-time Detection with YOLOv8Optimizing the harvesting process presents a continuous challenge within the strawberry industry, especially during peak seasons when precise labor allocation becomes critical for efficiency and cost-effectiveness. The conventional method for addressing this issue has been hindered by an absence of real-time data regarding yield distribution, resulting in less-than-ideal worker assignments and unnecessary expenditures on labor. In response, a novel, portable, real-time strawberry detection system... Z. Huang, W. Lee, N. Takkellapati |
33. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |
34. Assessing Crop Yield and Profitability with Site-specific Seed Rate Management in Corn and Soybean Cropping SystemsIntegrating the information about soil and topographic properties for variable rate seeding is a prerequisite for improved crop production and thus profit. However, limited studies have explored the geospatial and machine learning approaches to understand factors influencing crop yield and profit under site-specific seed rate management. The objectives of this study were to: a) observe the effect of variable seeding rate based on soil and topographic properties on soybean and corn grain yield,... J. Neupane, N. Joshi, J.P. Fulton, S. Khanal, A. B k, B. Bhattarai |
35. Satellite-based On-farm Variable Rate Nitrogen Management on and Main Spatial Drivers of Cotton Yield, Nitrogen Use Efficiency, and ProfitabilityIn the United States of America, Georgia is the second largest cotton producing state, responsible for 2.6 million bales produced in 2022. In Georgia, cotton is the most economically important row crop, with ~514,000 ha harvested and $USD 1.5 billion in economic impact in the state economy in 2022. Nitrogen (N) fertilizer is one of the main inputs required to optimize cotton lint yield and quality, while also being a large input cost representing ~25% of variable costs. As a non N-fixing crop,... L. Bastos, W. Porter, G. Scarpin |
36. Proximal, Drone, and Satellite Sensors for In-season Variable Nitrogen Rate Application in Corn: a Comparative Study of Fixed-rate and Sensor-based ApproachesEffective nitrogen (N) management is essential for optimizing corn yield and enhancing agricultural sustainability. Traditional N application methods, typically uniform split pre-plant and in-season applications, often neglect the spatial and temporal variability of N requirements across different fields and years, potentially leading to N overuse. With the rise of precision agriculture technologies, it is crucial to reassess these conventional practices. This study had two main objectives: first,... A. Jakhar, A. Bhattarai, L. Bastos, G. Scarpin |
37. North Dakota State University - Sponsor Presentation... L. Schumacher, P. Flores, R. Sun, A. Reinholz |