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| Filter results17 paper(s) found. |
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1. Development Of An Enterprise Level Precision Agriculture SystemDevelopment of an Enterprise Level Precision Agriculture System James Ellingson, Chih Lai University of St. Thomas, School of Engineering 2115 Summit Ave, St. Paul, MN USA elli4729@stthomas.edu; Abstract – In this paper, a plan for the development of an Enterprise Level system for Precision Agriculture (PA) is described. The ... J.L. Ellingson, B.K. Holub, S.E. Morgan, B.K. Werkmeister |
2. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft SystemsSmall Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infra... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt |
3. The TOAS Project: UAV Technology For Optimizing Herbicide Applications In Weed-Crop SystemsSite-specific weed management refers to the application of customised control treatments, mainly herbicide, only where weeds are located within the crop-field. In this context, the TOAS project is being developed under the financial support of the European Commission with the main objective of generating georeferenced weed infestation maps of certain herbaceous (corn and sunflower) and permanent woody crops (poplar and olive orchards) by using aerial images collected by an unmanned aeria... J.M. Peña, J. Torres-sanchez, A.I. De castro, J. Dorado, F. Lopez-granados |
4. Applying Conventional Vegetation Vigor Indices To UAS-Derived Orthomosaics: Issues And ConsiderationsIn recent years, unmanned airborne systems (UAS) have gained a lot of interest for their potential use in precision agriculture. While the imagery from near-infrared (NIR) enabled off-the-shelf cameras included in UAS can be directly used to facilitate crop scouting, the application in quantitative analyses remains cumbersome. The ultimate goal is to calculate (nitrogen) prescription maps from vegetation indices obtained from UAS imagery, but two main issues hamper this workflow: (1) the... J. Quaderer, J. Coonen, A. Lange, K. Pauly |
5. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management IssuesThis research project is a “proof-of-concept” demonstrating specific UAS applications in production agriculture. Project personnel will use UAS-mounted sensors to collect data of ongoing crop and livestock research projects during the 2014 crop season at the North Dakota State University (NDSU) Carrington Research Extension Center (CREC). Project personnel will collaborate with NDSU research scientists conducting research at the CREC. During the first year of the pro... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson |
6. 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 appli... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings |
7. Weed Seedlings Detection In Winter Cereals For Site-Specific Control: Use Of UAV Imagery To Overcome The ChallengeWeed management is an important part of the investments in crop production. Cost of herbicides accounts for approximately 40% of the cost of all the chemicals applied to agricultural land in Europe. In order to increase the profitability of crop production and to reduce the environmental concerns related to chemicals application, it is needed to develop site-specific weed management strategies in which herbicides are only applied in the crop zones were weeds spread. Moreover, th... J. Peña, A. De castro, F. López-granados, J. Torres-sánchez |
8. Unmanned Aerial System To Determine Nitrogen Status In MaizeMaize field production shows spatial variability during vegetative crop growth that could be used to prescribe nitrogen variable rates. The use of portable sensors mounted on high-clearance applicators is well documented, however new UAS vehicle equipped with high resolution digital cameras could be used to determine crop spatial variability with the advantage of survey extensive field areas. To our knowledge, comparisons between vegetation indices obtained by a modified digital camera a... A.C. Kemerer, S.M. Albarenque, R.J. Melchiori |
9. sUAVS Technology For Better Monitoring Crop Status For Winter CanolaThe small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus |
10. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In CornA number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) r... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon |
11. The Use Of A Multirotor And High-Resolution Imaging For Precision Horticulture In Chile: An Industry PerspectiveAs part of the prototype development of a yield forecasting and precision agriculture service for Chilean horticulture, we evaluated the use of an eight-rotor Mikrokopter for high-resolution aerial imaging to support ground-based surveys. Specific considerations for UAV and communications performance under Chilean conditions are windy conditions, limited space for take-off and landing in orchards, tree height and plantation density, and the presence of high metal contents in soils. We di... I. Zamora, D. Wulfsohn |
12. FOODIE Data Model for Precision AgricultureThe agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and ... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka |
13. Modus: a Standard for Big DataModus Standard is a system of defined terminology, agreed metadata and file transfer format that has grown from a need to exchange, merge and trend agricultural testing data. The three presenters will discuss steps taken to develop the system, benefits to data exchange, current user base and additions being made to the standard. ... D. Nerpel, J.W. Ellsworth, A. Hunt |
14. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture IndustryPrecision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena. Examples of U.S. and international laws related to data protectio... J.K. Archer, C.A. Delgadillo, F. Shen |
15. 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 |
16. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPTAgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway id... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy |
17. Rationale for and Benefits of a Community for On-Farm Data SharingMost data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger |