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1. Design, Error Characterization And Testing Of A System To Measure Locations Of Fruits In Tree CanopiesMapping the variability of fruit size and quality within tree canopies in commercial orchards is an important tool for implementing precision horticulture. To do so at a reasonably fast rate requires localization technologies that offer sufficient speed and accuracy, at a range long enough to cover entire trees – or several trees at a time. Existing approaches for measuring fruit locations include: manual (centimeter accuracy and measurement time in the order of minutes per... S.G. Vougioukas, F.J. Jimenez, F. Khosro anjom, R. Elkins, C. Ingels, R. Arikapudi |
2. Application of Semantic Sensor Web in AgricultureIn July 2013, heavy rainstorms across the Midwestern region of the US caused many rivers to breach their banks. Residents of Valley Park, a small town along the Meramec River, Missouri, had to decide whether to rely on a newly constructed levee or abandon their homes for higher ground. Although the levee held, many chose the latter option and fled their homes; it was a chaotic situation that might have been avoided through access to better situational knowledge... Y. Zhang, T. Chen |
3. Static and Kinematic Tests for Determining Spreaders Effective WidthSpinner box spreaders are intensively used in Brazil for variable rate applications of lime in agriculture. The control of that operation is a challenging issue because of the complexity involved on the interactions between product and machine. Quantification of transverse distribution of solids thrown from the spinner box spreaders involves dynamic conditions tests where the material deposited on trays is evaluated along the pass of the machinery. There is a need of alternative testing methods... L. Maldaner, T. Canata, J. Molin, B. Passalaqua, J.J. Quirós |
4. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in CornRemotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia |
5. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial VehicleAbove-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas |
6. Use of MLP Neural Networks for Sucrose Yield Prediction in SugarbeetINTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes |
7. Enhancing Spatial Resolution of Maize Grain Yield DataGrain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops. Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used to... J. Siegfried, R. Khosla, D. Mandal, W. Yilma |
8. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming ContextThe increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an... |
9. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |