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Murdoch, A
Muller, O
Melo, D.D
Cutulle, M
Moon, H
Mizgirev, A
Cui, B
Federizzi , L.C
Dorado, J
Magalhaes, P.S
Mohamed, M.M
Carcedo, A
Mennuti, D
Cabrera Dengra, M
Molina Cyrineu, I
Marchant, B
Kechadi, M
Pack, C
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Authors
Garcia, A.H
Rodrigues Júnior, F.H
Bastos, A.H
Magalhaes, P.S
Silva, M.J
Song, X
Zhao, C
Chen, L
Huang, W
Cui, B
Peña, J.M
Torres-Sanchez, J
de Castro, A.I
Dorado, J
Lopez-Granados, F
Anselmi, A.A
Federizzi , L.C
Bredemeier, C
Molin, J.P
Muller, O
Cendrero Mateo, M.P
Albrecht, H
Pinto, F
Mueller-Linow, M
Pieruschka, R
Schurr, U
Rascher, U
Schickling, A
Keller, B
Jeon, C
Kim, H
Han, X
Moon, H
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Ngo, V.M
Le-Khac, N
Kechadi, M
Kindred, D
Sylvester-Bradley, R
Clarke, S
Roques, S
Hatley, D
Marchant, B
Muller, O
Keller, B
Zimmermanm, L
Jedmowski, C
Pingle, V
Acebron, K
Zendonadi, N
Steier, A
Pieruschka, R
Schurr, U
Rascher, U
Kraska, T
Mohamed, M.M
Zaman, Q
Esau, T
Farooque, A
Cabrera Dengra, M
Ferraz Pueyo, C
Pajuelo Madrigal, V
Moreno Heras, L
Inunciaga Leston, G
Fortes, R
Karampoiki, M
Todman, L
Mahmood, S
Murdoch, A
Paraforos, D
Hammond, J
Ranieri, E
Maja, J.J
Abenina, M
Cutulle, M
Melgar, J
Liu, H
Capolicchio, J
Mennuti, D
Milani, I
Fortunato, M
Petix, R
Reyes Gonzalez, J
Sunkevic, M
Amaral, L.R
Oldoni, H
Melo, D.D
Rosin, N.A
Alves, M.R
Demattê, J.M
Gummi, S
Alahe, M
Chang, Y
Pack, C
Carcedo, A
Antunes de Almeida, L.F
Horbe, T
Corassa, G
Pott, L.P
Ciampitti, I
Hintz, G.D
Hefley, T
Schwalbert, R.A
Prasad, V
Lingua, L.N
Carcedo, A
Gimenez, V
Maddonni, G
Ciampitti, I
Rodrigues Alves Franchi, M
Molina Cyrineu, I
Kagami Taira, F
Hunhoff, L
Gimenez, L.M
Topics
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Profitability, Sustainability and Adoption
Precision Agriculture and Climate Change
Engineering Technologies and Advances
Precision Nutrient Management
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Profitability and Success Stories in Precision Agriculture
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Agriculture and Global Food Security
Geospatial Data
Robotics and Automation with Row and Horticultural Crops
Weather and Models for Precision Agriculture
Data Analytics for Production Ag
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
2024
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Filter results20 paper(s) found.

1. Assembly of an Ultrasound Sensors System for Mapping of Sugar Cane Height

In Precision Agriculture, the use of sensors provides faster data collection on plant, soil, and climate, allowing collecting larger sample sets with better information quality. The objective of this study was the development of a system for plant height measurement in order to mapping of sugar cane crop, so that regions with plant growth variation and grow failures could be identified... A.H. Garcia, F.H. Rodrigues júnior, A.H. Bastos, P.S. Magalhaes, M.J. Silva

2. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

  ... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui

3. The TOAS Project: UAV Technology For Optimizing Herbicide Applications In Weed-Crop Systems

Site-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 aerial... J.M. Peña, J. Torres-sanchez, A.I. De castro, J. Dorado, F. Lopez-granados

4. Factors Related To Adoption Of Precision Agriculture Technologies In Southern Brazil

The adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin

5. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate Change

Phenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller

6. Development of a Crop Edge Line Detection Algorithm Using a Laser Scanner for an Autonomous Combine Harvester

The high cost of real-time kinematic (RTK) differential GPS units required for autonomous guidance of agricultural machinery has limited their use in practical auto-guided systems especially applicable to small-sized farming conditions. A laser range finder (LRF) scanner system with a pan-tilt unit (PTU) has the ability to create a 3D profile of objects with a high level of accuracy by scanning their surroundings in a fan shape based on the time-of-flight measurement principle. This paper describes... C. Jeon, H. Kim, X. Han, H. Moon

7. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

8. An Efficient Data Warehouse for Crop Yield Prediction

Nowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi

9. Supporting and Analysing On-Farm Nitrogen Tramline Trials So Farmers, Industry, Agronomists and Scientists Can LearN Together

Nitrogen fertilizer decisions are considered important for the agronomic, economic and environmental performance of cereal crop production. Despite good recommendation systems large unpredicted variation exists in measured N requirements. There may be fields and farms that are consistently receiving too much or too little N fertilizer, therefore losing substantial profit from wasted fertilizer or lost yield. Precision farming technologies can enable farmers (& researchers) to test appropriate... D. Kindred, R. Sylvester-bradley, S. Clarke, S. Roques, D. Hatley, B. Marchant

10. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

11. Design of Ground Surface Sensing Using RADAR

Ground sensing is the key task in harvesting head control system. Real time sensing of field topography under vegetation canopy is very challenging task in wild blueberry cropping system. This paper presents the design of an ultra-wide band RADAR sensing, scanning device to recognize the soil surface level under the canopy structure. Requirements for software and hardware were considered to determine the usability of the ultra-wide band RADAR system.An automated head elevation... M.M. Mohamed, Q. Zaman, T. Esau, A. Farooque

12. Use of MLP Neural Networks for Sucrose Yield Prediction in Sugarbeet

INTRODUCTION 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

13. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri

14. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate Analysis

Hyperspectral 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

15. Agriculture Machine Guidance Systems: Performance Analysis of Professional GNSS Receivers

GNSS (Global Navigation Satellite Systems) plays nowadays a major role in different civilian activities and is a key technology enabling innovation in different market sectors. For instance, GNSS-enabled solutions are widespread within the Precision Agriculture and, among them, applications in the field of machinery guidance are commonly employed to optimize typical agriculture practices. The scope of this paper is to present the outcomes of the agriculture testing campaign performed,... J. Capolicchio, D. Mennuti, I. Milani, M. Fortunato, R. Petix, J. Reyes gonzalez, M. Sunkevic

16. Yield Potential Zones and Their Relationship with Soil Taxonomic Classes and Management Zones

The 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. For... L.R. Amaral, H. Oldoni, D.D. Melo, N.A. Rosin, M.R. Alves, J.M. Demattê

17. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease Detection

The early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordinated... S. Gummi, M. Alahe, Y. Chang, C. Pack

18. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico Approach

Water stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad

19. Environmental Characterization for Rainfed Maize Production in the US Great Plains Region

Identifying regions with similar productivity and yield-limiting climatic factors enables the design of tailored strategies for rainfed maize (Zea mays L.) production in vulnerable environments. Within the United States (US) Great Plains region, rainfed maize production in Kansas is susceptible to weather fluctuations. This study aims to delimit environmental regions with similar crop growth conditions and to identify the main climatic factors limiting rainfed maize yield, using the state... L.N. Lingua, A. Carcedo, V. Gimenez, G. Maddonni, I. Ciampitti

20. On-farm Experimentation Case Study in Brazil: Evaluation of Soybean Seeding Rate Using Resources Available at the Farm

In order to maximize grain yield in soybean (Glycine max [L.] Merr.) it is necessary that the plant population is correctly defined. Production environments differ spatially, and cultivar holders suggest plant populations across macroregions and in broad ranges. Refinements of planting seasons and populations are carried out through tests on many properties, often costly and sometimes unrepresentative of most fields. Tools for managing spatial variability are ways to conduct more... M. Rodrigues alves franchi, I. Molina cyrineu, F. Kagami taira, L. Hunhoff, L.M. Gimenez