Proceedings
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| Filter results18 paper(s) found. |
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1. A Low Cost, Modular Robotics Tool Carrier for Precision Agriculture ResearchCurrent research within agricultural crop production focus on using autonomous robot technology to optimize the production efficiency, enhance sustainability and minimize tedious, monotonous and wearing tasks. But progress is slow partly... A. Bøgild, S.H. Nielsen, N.J. Jacobsen, C.L. Jaeger-hansen, R.N. Jørgensen, K. Jensen, O.J. Jørgensen |
2. Comparison of Algorithms for Delineating Management Zones... A.M. Saraiva, R.T. Santos, J.P. Molin |
3. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means MethodsThe generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi |
4. The Influence Of The Interpolation Method In The Management Zones GenerationThe definition of management zones (MZ) allows the concepts of precision agriculture (PA) to be used even in small producers. Methods for defining these MZ were created and are being used, obtaining satisfactory results with different crops and parameters (FLEMING & WESTFALL, 2000; ORTEGA & SANTIBÁÑEZ, 2007; MILANI et al., 2006). Through methodologies, the attributes that are influencing the productivity are selected and thematic maps are generated with the... K. Schenatto, C. Bazzi, V. Bier, E. Souza |
5. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North DakotaA recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indicated... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen |
6. Yield, Residual Nitrogen and Economic Benefit of Precision Seeding and Laser Land Leveling for Winter WheatRapid socio-economic changes in China, such as land conversion and urbanization etc., are creating new scopes for application of precision agriculture (PA). It remains unclear the application effective and economic benefits of precision agriculture technologies in China. In this study, our specific goal was to analyze the impact of precision seeding and laser land leveling on winter wheat yield,... J. Chen , P.L. Chen, J.C. Zhao, S.Y. Wang, J.C. Li, Q. Zhang, T.H. Hu, G.L. Shi |
7. Opportunities for Precision Agriculture in SerbiaThe aim of this paper is to analyze the factors leading to low adoption rate of precision farming in Serbia and to describe steps being taken by BioSense institute to increase it. The majority of the arable land in Serbia is grown by small family owned and operated farms most of which are in the range of 2 to 5 ha making them highly unsustainable. Only 16% of the arable land is managed by agricultural companies and cooperatives. We believe that the adoption of advanced technologies with the currently... A.C. Tagarakis, F. Van evert, D. Milic, V. Crnojevic, V. Crnojevic-bengin, C. Kempenaar, N. Ljubicic |
8. Using a Fully Convolutional Neural Network for Detecting Locations of Weeds in Images from Cereal FieldsInformation about the presence of weeds in fields is important to decide on a weed control strategy. This is especially crucial in precision weed management, where the position of each plant is essential for conducting mechanical weed control or patch spraying. For detecting weeds, this study proposes a fully convolutional neural network, which detects weeds in images and classifies each one as either a monocot or dicot. The network has been trained on over 13 000 weed annotations... M. Dyrmann, S. Skovsen, R.N. Jørgensen, M.S. Laursen |
9. Predicting Dry Matter Composition of Grass Clover Leys Using Data Simulation and Camera-Based Segmentation of Field Canopies into White Clover, Red Clover, Grass and WeedsTargeted fertilization of grass clover leys shows high financial and environmental potentials leading to higher yields of increased quality, while reducing nitrate leaching. To realize the gains, an accurate fertilization map is required, which is closely related to the local composition of plant species in the biomass. In our setup, we utilize a top-down canopy view of the grass clover ley to estimate the composition of the vegetation, and predict the composition of the dry matter of the forage.... S. Skovsen, M. Dyrmann, J. Eriksen, R. Gislum, H. Karstoft, R.N. Jørgensen |
10. Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural NetworksThis paper presents a method which can provide support in determining the grass-clover ratio, in grass-clover fields, based on images from an unmanned aerial vehicle. Automated estimation of the grass-clover ratio can serve as a tool for optimizing fertilization of grass-clover fields. A higher clover content gives a higher performance of the cows, when the harvested material is used for fodder, and thereby this has a direct impact on the dairy industry. An android application... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen |
11. Creating Thematic Maps and Management Zones for Agriculture FieldsThematic maps (TMs) are maps that represent not only the land but also a topic associated with it, and they aim to inform through graphic symbols where a specific geographical phenomenon occurs. Development of TMs is linked to data collection, analysis, interpretation, and representation of the information on a map, facilitating the identification of similarities, and enabling the visualization of spatial correlations. Important issues associated with the creation of TMs are: selection of the... E. Souza, K. Schenatto, C. Bazzi |
12. Ground Vehicle Mapping of Fields Using LiDAR to Enable Prediction of Crop BiomassMapping field environments into point clouds using a 3D LIDAR has the ability to become a new approach for online estimation of crop biomass in the field. The estimation of crop biomass in agriculture is expected to be closely correlated to canopy heights. The work presented in this paper contributes to the mapping and textual analysis of agricultural fields. Crop and environmental state information can be used to tailor treatments to the specific site. This paper presents the current results... M.P. Christiansen, M.S. Laursen, R.N. Jørgensen, S. Skovsen, R. Gislum |
13. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer ManagementDetermination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi |
14. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield PotentialThis paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez |
15. AgDataBox-IoT - Managing IoT Data and Devices on Precision AgricultureThe increasing global population has resulted in a substantial demand for nourishment, which has prompted the agricultural sector to investigate ways to improve efficiency. Precision agriculture (PA) uses advanced technologies such as the Internet of Things (IoT) and sensor networks to collect and analyze field information. Although the advantages are numerous, the available data storage, management, and analysis resources are limited. Therefore, creating and providing a user-friendly web application... C.L. Bazzi, W.K. Oliveira, R. Sobjak, K. Schenatto, E. Souza, A. Hachisuca, F. Franz |
16. Geographic Database in Precision Agriculture for the Development of AI ResearchAgriculture 4.0 has profoundly transformed production processes by incorporating technologies such as Precision Agriculture, Artificial Intelligence, the Internet of Things, and telemetry. This evolution has enabled more accurate and timely decision-making in agriculture. In response to this movement, the Precision Agriculture Laboratory (AgriLab) of UTFPR, located in Medianeira, proposes the establishment of a consistent and standardized database. This database is continually updated with surveys... E.N. Avila, C.L. Bazzi, W.K. Oliveira, K. Schenatto, R. Sobjak, D.M. Rocha |
17. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop ProtectionIn the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen |
18. Vegetation Coverage Specific Flower Density Estimation in Blackberry Using Unmanned Aerial Vehicle (UAV) Remote SensingThe effective management of agricultural systems relies on the utilization of accurate data collection techniques to analyze essential crop attributes to enhance productivity and ensure profits. Data collection procedures for specialty horticultural crops are mostly subjective, time consuming and may not be accurate for management decisions in both phenotypic studies and crop production. Reliable and repeatable standard methods are therefore needed to capture and calculate attributes of horticultural... A. Tagoe, C. Koparan, A. Poncet, D.M. Johnson, M. Worthington, D. Wang |