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Xie, J
Joshi, R
Pitrat, T
P.W Clevers, J.G
Crnojevic-Bengin, V
Clay, D.E
Xu, X.M
You Fu, E
Warner, D
Varco, J.J
Drewry, J
Vories, E.D
Villodre, J
Wood, B.A
Lee, W
Wallor, E
Johnson, E
Boettinger, J.L
Lupia, F
Pourshamsaei, H
Kukorelli, G
Bodnár, K.B
Weiqiang, F
López-Granados, F
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Authors
Wang, J.M
Li, C.M
Yang, X.M
Huang, W.M
Yang, H.M
Xu, X.M
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Sun, C
Ji, Z
Qian, J
Li, M
Zhao, L
Li, W
Zhou, C
Du, X
Xie, J
Wu, T
Qu, L
Hao, L
Yang, X
Guangwei, W
Zhijun, M
Liping, C
Weiqiang, F
Jianjun, D
You Fu, E
Yule, I.J
Wood, B.A
Cushnahan, M.Z
Yule, I.J
Wood, B.A
Wilson, R
Larson, J.A
Stefanini, M
Lambert, D.M
Yin, X
Boyer, C.N
Varco, J.J
Scharf , P.C
Tubaña, B.S
Dunn, D
Savoy, H.J
Buschermohle, M.J
Tyler, D.D
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
Sanches, G.M
Amaral, L.R
Pitrat, T
Brasco, T
Magalhaes, P.S
Duft, D.G
Franco, H.C
Nguyen, A.T
Thompson, A.L
Sudduth, K.A
Vories, E.D
Nguyen, A.T
Garcia-Torres, L
Peña-Barragán, J.M
Gómez-Candón, D
López-Granados, F
Jurado-Expósito, M
Franzen, D.W
Boettinger, J.L
Clay, D.E
Clay, S.A
Reicks, G
Horvath, D
P.W Clevers, J.G
Wijnholds, K.H
Jukema, J.N
Warner, D
Lacroix, R
Vasseur, E
Lefebvre, D
Pourshamsaei, H
Nobakhti, A
Bodnár, K.B
Nagy, J
Gombos, B
Pourshamsaei, H
Nobakhti, A
Tagarakis, A.C
van Evert, F
Milic, D
Crnojevic, V
Crnojevic-Bengin, V
Kempenaar, C
Ljubicic, N
Seo, Y
Lee, W
Kim, Y
Chung, S
Jang, S
Bae, I
Luck, B
Drewry, J
Chassen, E
Steffan, S
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Ha, T
Aldridge, K
Johnson, E
Shirtliffe, S.J
Ryu, S
Krys, K
Shirtliffe, S
Duddu, H
Ha, T
Attanayake, A
Johnson, E
Andvaag, E
Stavness, I
Zsebő, S
Kukorelli, G
Vona, V
Bede, L
Stencinger, D
Kovacs, A
Milics, G
Kulmany, I.M
Horváth, B
Hegedűs, G
Abdinoor, J.A
Joshi, R
Khosla, R
Mandal, D
Unruh, R
Admasu, W.A
Unruh, R
Admasu, W.A
Mandal, D
Joshi, R
Khosla, R
Kulmany, I.M
Horváth, B
Kukorelli, G
Zsebő, S
Stencinger, D
Borbás, Z
Pecze, R
Bede, L
Varga, Z
Kósa, A
Pinke, G
Hashim, Z.K
Hegedűs, G
Abdinoor, J.A
Agampodi, G.S
Topics
Remote Sensing Applications in Precision Agriculture
Information Management and Traceability
Spatial Variability in Crop, Soil and Natural Resources
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Profitability, Sustainability and Adoption
Big Data Mining & Statistical Issues in Precision Agriculture
Profitability, Sustainability and Adoption
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Precision Horticulture
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Remote Sensing Application / Sensor Technology
Farm Animals Health and Welfare Monitoring
Wireless Sensor Networks
Smart Weather for Precision Agriculture
Big Data, Data Mining and Deep Learning
Small Holders and Precision Agriculture
Precision Horticulture
Applications of Unmanned Aerial Systems
In-Season Nitrogen Management
Applications of Unmanned Aerial Systems
Scouting and Field Data collection with Unmanned Aerial Systems
In-Season Nitrogen Management
Drainage Optimization and Variable Rate Irrigation
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
2022
2024
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Filter results29 paper(s) found.

1. Estimation of Leaf Nitrogen Concentration in Barley with In Situ Hyperspectral Measurements

Leaf nitrogen concentration (LNC), a good indicator of nitrogen status in crop, is of special significance to diagnose nutrient stress and guide nitrogen fertilization in fields. Due to its non-destructive and quick advantages, hyperspectral remote sensing plays a unique role... J.M. Wang, C.M. Li, X.M. Yang, W.M. Huang, H.M. Yang, X.M. Xu

2. Applications for Precision Agriculture: the Italian Experience of SIRIUS Project

    This paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele

3. Towards a Multi-Source Record Keeping System for Agricultural Product Traceability

Agricultural production record keeping is the basis of traceability system. To resolve the problem including single method of information acquisition, weak ability of real-time monitoring and low credibility of history information in agricultural production process, the... C. Sun, Z. Ji, J. Qian, M. Li, L. Zhao, W. Li, C. Zhou, X. Du, J. Xie, T. Wu, L. Qu, L. Hao, X. Yang

4. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China in... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

5. The Central China Agricultural High-Tech Industry Development Zone

This is a presentation on precision ag opportunities in China. ... E. You fu

6. Precision Agriculture As Bricolage: Understanding The Site Specific Farmer

There is an immediate paradox apparent in precision farming because it applies all of it ‘s precision and recognition of variability to the land, yet operates under the assumption of idealism and normative notions when it comes to considering the farmer.  Precision Agriculture (PA) systems have often considered the farmer as an optimiser of profit, or maximiser of efficiency, and therefore replaceable with mathematical constructs, so that although at the centre of decision... I.J. Yule, B.A. Wood

7. Surplus Science and a Non-linear Model for the Development of Precision Agriculture Technology

The advent of ‘big data technologies’ such as hyperspectral imaging means that Precision Agriculture (PA) developers now have access to superabundant and highly  heterogeneous data.  The authors explore the limitations of the classic science model in this situation and propose a new non-linear process that is not based on the premise of controlled data scarcity. The study followed a science team tasked with developing highly advanced hyperspectral techniques for a ‘low... M.Z. Cushnahan, I.J. Yule, B.A. Wood, R. Wilson

8. Net Returns and Production Use Efficiency for Optical Sensing and Variable Rate Nitrogen Technologies in Cotton Production

This research evaluated the profitability and N use efficiency of real time on-the-go optical sensing measurements (OPM) and variable-rate technologies (VRT) to manage spatial variability in cotton production in the Mississippi River Basin states of Louisiana, Mississippi, Missouri, and Tennessee. Two forms of OPM and VRT and the existing farmer practice (FP) were used to determine N fertilizer rates applied to cotton on farm fields in the four states. Changes in yields and N rates due to OPM... J.A. Larson, M. Stefanini, D.M. Lambert, X. Yin, C.N. Boyer, J.J. Varco, P.C. Scharf , B.S. Tubaña, D. Dunn, H.J. Savoy, M.J. Buschermohle, D.D. Tyler

9. 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

10. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane Fields

One important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco

11. Automated Support Tool for Variable Rate Irrigation Prescriptions

Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS data layers of grid-based field soil texture properties and fertility needs in making management decisions. The program can automatically develop a variable rate application prescription along the lateral... A.T. Nguyen, A.L. Thompson, K.A. Sudduth, E.D. Vories, A.T. Nguyen

12. A Software for Managing Remotely Sensed Imagery of Orchards Plantations for Precision Agriculture

Agronomic and environmental characteristics of fruit orchards/ forests can be automatically assessed from remote-sensing images by a computer programme named Clustering Assessment (CLUAS®). The aim of this paper is to describe the operational procedure of CLUAS and illustrate examples of the information provided for citrus orchards and Mediterranean forest. CLUAS® works as an additional menu (“add-on”) of ENVI®, a world-wide known image-processing programme, and operates... L. Garcia-torres, J.M. Peña-barragán, D. Gómez-candón, F. López-granados, M. Jurado-expósito

13. Terrain Modeling to Improve Soil Survey in North Dakota

Users of site-specific technologies would prefer to use digitized soil survey boundaries to help in delineating management zones for nutrient application. However, the present scale of soil type does not allow meaningful zone delineation. A project was conducted to use terrain modeling and other site- specific tools to delineate smaller-scale soil type boundaries that would be more useful for directing within-field nutrient management. Topography, soil EC, yield mapping and satellite imagery were... D.W. Franzen, J.L. Boettinger

14. 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

15. Remote Sensing-based Biomass Maps for an Efficient Use of Fertilizers

For decades the main objective of farmers was to get the highest yields from their farmland. Nowadays, quality of agricultural products is becoming more and more important for the largest returns. In addition, the effects on our environment are also becoming important. These put increasing limitations on modern agriculture. So-called site-specific management can optimize the input of, for instance, nutrients and pesticides to the need of the plants. In this study, the objective was to study whether... J.G. P.w clevers, K.H. Wijnholds, J.N. Jukema

16. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning Algorithms

Machine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expensive... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre

17. A Comparative Study of Field-Wide Estimation of Soil Moisture Using Compressive Sensing

In precision agriculture, monitoring of soil moisture plays an essential role in correct decision making. In practice, regular mesh installation, or large random deployment of moisture sensors over a large field is not possible due to cost and maintenance prohibitions. Consequently, direct measurement of moisture is possible at only a few points in the field. A value for the moisture may then be estimated for the remaining areas using a variety of algorithms. It is shown that although... H. Pourshamsaei, A. Nobakhti

18. Correlations Between Meteorological Parameters and the Water Loss of Maize from Silking to Harvesting

The University of Debrecen provides outstanding conditions for the development of “Smart Weather for Precision Agriculture” programs. The reliability of research is provided by the Polyfactoral Long-term Field Experiments of Debrecen (hybrid x fertilisation x plant density x tillage x irrigation) established in 1983. Within this research program, it is possible to examine various crop cultures, cultivars and hybrids under changing natural, environmental and weather circumstances,... K.B. Bodnár, J. Nagy, B. Gombos

19. Optimal Sensor Placement for Field-Wide Estimation of Soil Moisture

Soil moisture is one of the most important parameters in precision agriculture. While techniques such as remote sensing seems appropriate for moisture monitoring over large areas, they generally do not offer sufficiently fine resolution for precision work, and there are time restrictions on when the data is available. Moreover, while it is possible to get high resolution-on demand data, but the costs are often prohibitive for most developing countries. Direct ground level measurement... H. Pourshamsaei, A. Nobakhti

20. Opportunities for Precision Agriculture in Serbia

The 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

21. Variability Analysis of Temperature and Humidity for Control Optimization of a Hybrid Dehumidifier with a Heating Module for Greenhouses

Protected horticulture using greenhouses and also recently plant factories is becoming more popular, especially for high-value crops such as paprika, tomato, strawberry, due to year-round production of high yield and better quality crops under controlled environment. Temperature and humidity are most important ambient environmental factors for not only optimum crop growth but also disease control. This study was conducted to analyze vertical and spatial variability of temperature and humidity... Y. Seo, W. Lee, Y. Kim, S. Chung, S. Jang, I. Bae

22. Unmanned Aerial Systems and Remote Sensing for Cranberry Production

Wisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Initial... B. Luck, J. Drewry, E. Chassen, S. Steffan

23. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This 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

24. Knowledge-based Approach for Weed Detection Using RGB Imagery

A workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, wild... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu

25. Establishment of a Canola Emergence Assessment Methodology Using Image-based Plant Count and Ground Cover Analysis

Manual assessment of emergence is a time-consuming practice that must occur within a short time-frame of the emergence stage in canola (Brassica napus). Unmanned aerial vehicles (UAV) may allow for a more thorough assessment of canola emergence by covering a wider scope of the field and in a more timely manner than in-person evaluations. This research aims to calibrate the relationship between emerging plant population count and the ground cover. The field trial took place at the University... K. Krys, S. Shirtliffe, H. Duddu, T. Ha, A. Attanayake, E. Johnson, E. Andvaag, I. Stavness

26. Comparison of NDVI Values at Different Phenological Stages of Winter Wheat (Triticum Aestivum L.)

The main objective of this study is to monitor, detect and quantify the presence of live green vegetation with the MicaSense RedEdge-MX Dual Camera System (MS) mounted on a DJI Matrice 210 V2 and GreenSeeker HCS 250 (GS) in winter wheat (Triticum aestivum L.) by using Normalized Difference Vegetation Index (NDVI). Surveys were conducted in the North-Western part of Hungary, in Mosonmagyaróvár on six different dates. A small-scale field trial in winter wheat was constructed as a randomized... S. Zsebő, G. Kukorelli, V. Vona, L. Bede, D. Stencinger, A. Kovacs, G. Milics, I.M. Kulmany, B. Horváth, G. Hegedűs, J.A. Abdinoor

27. Delineation of Site-Specific Management Zones using Sensor-based Data for Precision N management

Nitrogen is a critical nutrient influencing crop yield, but the common practice of uniform application of nitrogen fertilizer across a field often results in spatially variable nitrogen availability for the crop, leading to over-application in some areas and under-application in others. This imbalance can cause economic losses and significant environmental issues. Precision nitrogen application involves application of N fertilizers based on soil conditions and crop requirements. One approach for... R. Joshi, R. Khosla, D. Mandal, R. Unruh, W.A. Admasu

28. Delineating Dynamic Variable Rate Irrigation Management Zones

Agriculture irrigation strategies have traditionally been made without accounting for the natural small-scale variability in the field, leading to uniform applications that often over-irrigate parts of the field that do not need as much water. The future success of irrigated agriculture depends on advancements in the capability to account for and leverage the natural variability in croplands for optimum irrigation management both in space and time. Variable Rate Irrigation (VRI) management offers... R. Unruh, W.A. Yilma, D. Mandal, R. Joshi, R. Khosla

29. Evaluation of the Effect of Different Herbicide Treatments by Using UAV in Maise (Zea mays L.) Cultivation – First Experiences in a Long-term Experiment at Széchenyi István University, Hungary

As part of the Green Deal, the European Union has set a goal to reduce the use of chemical pesticides by 50 percent until 2030. To achieve this goal, in addition to reducing the amount of pesticide used, attention must also be paid to monitoring the temporal and spatial effects of pesticides on weeds during the cultivation of various crops. Hence, Syngenta Ltd., collaborating with researchers, aimed to monitor the effect of five different types of herbicides by UAV in two tillage treatments (CN... I.M. Kulmany, B. Horváth, G. Kukorelli, S. Zsebő, D. Stencinger, Z. Borbás, R. Pecze, L. Bede, Z. Varga, A. Kósa, G. Pinke, Z.K. Hashim, G. Hegedűs, J.A. Abdinoor, G.S. Agampodi