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Mouazen, A.M
Corrêdo, L
Eivazi, F
Melkonian, J
Maloof, J
Lamb, D
Molendijk, L.P
Quaderer, J
Struthers, R.R
Mathew, J
Mahmoudi, S
Marchant, B.P
Stephens, P
Schwalbert, R
Vories, E
Chang, Y.K
Souza, E
Lilienthal, H
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Authors
Stephens, P
Mackin, S
Holmes, G
Zaman, Q
Esau, T.J
Farooque, A.A
Schumann, A.W
Percival, D.C
Chang, Y.K
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Eivazi, F
Quaderer, J
Coonen, J
Lange, A
Pauly, K
Souza, E
Schenatto, K
Rodrigues, F
Rocha, D
Bazzi, C.L
Schenatto, K
Bazzi, C.L
Bier, V
Souza, E
Ulusoy, Y
Tümsavas, Z
Mouazen, A.M
Tekin, Y
Cosby, A.M
Falzon, G
Trotter, M
Stanley, J
Powell, K
Schneider, D
Lamb, D
Nguyen, T
Slaughter, D
Townsley, B
Carriedo, L
Maloof, J
Sinha, N
Rudolph, S
Marchant, B.P
Gillingham, V
Kindred, D
Sylvester-Bradley, R
Lilienthal, H
Wilde, P
Schnug, E
Sela, S
van-Es, H
McLellan, E
Melkonian, J
Marjerison , R
Constas, K
Gerighausen, H
Lilienthal, H
Schnug, E
Lilienthal, H
Gerighausen, H
Schnug, E
Schwalbert, R
Carneiro Amado, T.J
Horbe, T
Corassa, G.M
Gebert, F.H
Lilienthal, H
Schnug, E
Haneklaus, S
Struthers, R.R
Johannsen, C.J
Morris, D.K
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Lilienthal, H
Haneklaus, S.H
Schnug, E
Lilienthal, H
Gerighausen, H
Schnug, E
van Evert, F.K
Been, T
Booij, J.A
Kempenaar, C
Kessel, G.J
Molendijk, L.P
Souza, E
Schenatto, K
Bazzi, C
Vories, E
Jones, A
Stevens, G
Meeks, C
Plum, J
Quoitin, B
Dufrasne, I
Mahmoudi, S
Lebeau, F
Das, A
Flores, P
Zhang , Z
Friskop, A
Mathew, J
Ruma, F.Y
Munnaf, M.A
De Neve, S
Mouazen, A.M
Vories, E
Veum, K
Sudduth, K
Topics
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Precision Conservation
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Conservation Management
Proximal Sensing in Precision Agriculture
Precision Crop Protection
Engineering Technologies and Advances
Big Data Mining & Statistical Issues in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
No Group Selected
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Geospatial Data
Site-Specific Nutrient, Lime and Seed Management
Profitability and Success Stories in Precision Agriculture
Education and Outreach in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Farm Animals Health and Welfare Monitoring
Applications of Unmanned Aerial Systems
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Filter results28 paper(s) found.

1. Minimizing On-farm Point Source Contamination Of Pesticides Using The “Biobed” Method

  Microorganisms play a vital role in maintaining the environmental quality through their metabolic activities. The highly versatile metabolic capabilities of fungi and bacteria can be used to reclaim polluted ecosystems. A variety of biological, chemical, and physical methods have been used for degradation and detoxification of pesticides. However, conventional clean- up methods are costly and not always effective. Agrochemical storage and handling practices have been targeted... F. Eivazi

2. Exploiting the Dmc Satellite Constellation for Applications in Precision Agriculture

This paper presents the unique capabilities of the DMC constellation of optical sensors, and examples of how a number of organisations around the world are exploiting this powerful data source for applications in precision farming. The DMC consists of five satellites built in the UK by Surrey Satellite Technology Ltd, each carrying a wide swath (650km) optical sensor. It is an international programme of satellite ownership and groundstations, with joint campaigns being coordinated centrally... P. Stephens, S. Mackin, G. Holmes

3. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry Fields

An automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang

4. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

5. Applying Conventional Vegetation Vigor Indices To UAS-Derived Orthomosaics: Issues And Considerations

In 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

6. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means Methods

The 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

7. The Influence Of The Interpolation Method In The Management Zones Generation

The 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

8. Prediction Of Cation Exchange Capacity Using Visible And Near Infrared Spectroscopy

Cation exchange capacity (CEC) of the soil is a measure of the soil ability to hold positively charged ions and is an important indicator of soil physicochemical characteristic. It is an important property for site specific management of soil nutrients in precision agriculture. The conventional analytical methods used for the determination of CEC are expensive, difficult and time consuming, because different cations must be extracted and determined. Visible and near infrared (vis-NIR) spectroscopy... Y. Ulusoy, Z. Tümsavas, A.M. Mouazen, Y. Tekin

9. Using A Decision Tree To Predict The Population Density Of Redheaded Cockchafer (Adoryphorus Couloni) In Dairy Fields

A native soil dwelling insect pest, the redheaded cockchafer (Adoryphorus couloni) (Burmeister) (RHC) is an important pest in the higher rainfall regions of south-eastern Australia. Due to the majority of its lifecycle spent underground feeding on the roots and soil organic matter the redheaded cockchafer is difficult to detect and control. The ability to predict the level of infestation and location of redheaded cockchafers in a field may give producers the option to use an endophyte containing... A. Cosby, G. Falzon, M. Trotter, J. Stanley, K. Powell, D. Schneider, D. Lamb

10. In-field Plant Phenotyping Using Multi-view Reconstruction: an Investigation in Eggplant

Rapid methods for plant phenotyping are a growing need in agricultural research to help accelerate improvements in crop performance in order to facilitate more efficient utilization of plant genome sequences and the corresponding advancements in associated methods of genetic improvement. Manual plant phenotyping is time-consuming, laborious, frequently subjective, and often destructive. There is a need for building field-deployable systems with advanced sensors that have both high-speed and high-performance... T. Nguyen, D. Slaughter, B. Townsley, L. Carriedo, J. Maloof, N. Sinha

11. 'Spatial Discontinuity Analysis' a Novel Geostatistical Algorithm for On-farm Experimentation

Traditional agronomic experimentation is restricted to small plots. Under appropriate experimental designs the effects of uncontrolled environmental variables are minimized and the measured responses (e.g. in yields) are compared to controllable inputs (seed, tillage, fertilizer, pesticides) using well-trusted design-based statistical methods. However, the implementation of such experiments can be complex and the application, management, and harvesting of treated areas might have to... S. Rudolph, B.P. Marchant, V. Gillingham, D. Kindred, R. Sylvester-bradley

12. Proximal Hyperspectral Sensing in Plant Breeding

The use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug

13. Using the Adapt-N Model to Inform Policies Promoting the Sustainability of US Maize Production

Maize (Zea mays L.) production accounts for the largest share of crop land area in the U.S. It is the largest consumer of nitrogen (N) fertilizers but has low N Recovery Efficiency (NRE, the proportion of applied N taken up by the crop). This has resulted in well-documented environmental problems and social costs associated with high reactive N losses associated with maize production. There is a potential to reduce these costs through precision management, i.e., better application timing, use... S. Sela, H. Van-es, E. Mclellan, J. Melkonian, R. Marjerison , K. Constas

14. Non-destructive Plant Phenotyping Using a Mobile Hyperspectral System to Assist Breeding Research: First Results

Hybrid plants feature a stronger vigor, an increased yield and a better environmental adaptability than their parents, also known as heterosis effect. Heterosis of winter oilseed rape is not yet fully understood and conclusions on hybrid performance can only be drawn from laborious test crossings. Large scale field phenotyping may alleviate this process in plant breeding. The aim of this study was to test a low-cost mobile ground-based hyperspectral system for breeding research to easily... H. Gerighausen, H. Lilienthal, E. Schnug

15. First Experiences with the European Remote Sensing Satellites Sentinel-1A/ -2A for Agricultural Research

The Copernicus program headed by the European Commission (EC) in partnership with the European Space Agency (ESA) will launch up to twelve satellites, the so called “Sentinels” for earth and environmental observations until 2020. Within this satellite fleet, the Sentinel-1 (microwave) and Sentinal-2 (optical) satellites deliver valuable information on agricultural crops. Due to their high temporal (5 to 6 days repeating time) and spatial (10 to 20 m) resolutions a continuous monitoring... H. Lilienthal, H. Gerighausen, E. Schnug

16. Adjustment of Corn Population and Nitrogen Fertilization Based on Management Zones

The main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1),... R. Schwalbert, T.J. Carneiro amado, T. Horbe, G.M. Corassa, F.H. Gebert

17. 25 Years Precision Agriculture in Germany - a Retrospective

It all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus

18. Soil Moisture, Organic Matter and Potassium Influences on Eca Measurement

Spatial variability of soil physical and chemical properties is a fundamental element of site-specific soil and crop management. Since its early implementation in agriculture as a method of measuring soil salinity, the acceptance of Apparent Electrical Conductivity (ECa) in agriculture has been popular as a method of determining the spatial variability of soil physical and chemical properties that influence the ECa estimates. It was the objective of this study to examine the spatial-temporal stability... R.R. Struthers, C.J. Johannsen, D.K. Morris

19. Identifying and Filtering Out Outliers in Spatial Datasets

Outliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte

20. Frameworks for Variable Rate Application of Manure

Worldwide, nitrogen (N) and phosphorus (P) losses from agriculture are main contributors to eutrophication of water bodies so that forceful agro-technical measures are required to reduce their diffuse discharge to the environment. With view to worldwide finite mineral rock phosphates efficient standards are required to close the agricultural P cycle. In intensive agricultural livestock production manure is often treated as a waste problem rather than an organic fertilizer and source of nutrients.... H. Lilienthal, S.H. Haneklaus, E. Schnug

21. Agricultural Remote Sensing Information for Farmers in Germany

The European Copernicus program delivers optical and radar satellite imagery at a high temporal frequency and at a ground resolution of 10m worldwide with an open data policy. Since July 2017 the satellite constellation of the Sentinel-1 and -2 satellites is fully operational, allowing e.g. coverage of Germany every 1-2 days by radar and every 2-3 days with optical sensors. This huge data source contains a variety of valuable input information for farmers to monitor the in-field variability and... H. Lilienthal, H. Gerighausen, E. Schnug

22. Akkerweb: A Platform for Precision Farming Data, Science, and Practice

The concept of precision farming (PF) was formulated about 40 years ago and the scientific knowledge for some applications of PF in The Netherlands has been available for almost 20 years. Also, in many cases equipment is available to implement PF in practice. In spite of all this PF uptake is still limited. An important reason for the limited uptake of PF is in the challenges that must be overcome to let data flow from sensors to data storage, to combine data sources and process them into recommendations,... F.K. Van evert, T. Been, J.A. Booij, C. Kempenaar, G.J. Kessel, L.P. Molendijk

23. Creating Thematic Maps and Management Zones for Agriculture Fields

Thematic 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

24. Variety Effects on Cotton Yield Monitor Calibration

While modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replications... E. Vories, A. Jones, G. Stevens, C. Meeks

25. Use of Watering Hole Data As a Decision Support Tool for the Management of a Grazing Herd of Cattle

Establish grazing practices would improve the welfare of the animals, allowing them to express more natural behaviours. However, free-range reduces the ability to monitor the animals, thus increase the time needed to intervene in the event of a health problem. To ease the adoption of grazing, farmer would benefit from autonomously collected indicators at pasture that identify abnormal behaviours possibly related to a health problem in a bovine. These indicators must be individualised and collected... J. Plum, B. Quoitin, I. Dufrasne, S. Mahmoudi, F. Lebeau

26. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV Imagery

Goss Wilt has become a common disease in corn fields in North Dakota.  It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew

27. Management Zone-specific N Mineralization Rate Estimation in Unamended Soil

Since nitrogen (N) mineralization from soil organic matter is governed by basic soil properties (soil organic matter content, pH, soil texture, …) that are known to exhibit strong in-field spatial variability, N mineralization is also expected to exhibit significant spatial variability at field scale. An ideal and efficient N recommendation for precision fertilization should therefore account for potential soil mineralizable N considering this spatial variability. Therefore, this study... F.Y. Ruma, M.A. Munnaf, S. De neve, A.M. Mouazen

28. Impact of Cover Crop and Soil Apparent Electrical Conductivity on Cotton Development and Yield

Cotton is one of the major crops in the New Madrid Seismic Zone (NMSZ) of the U.S. Lower Mississippi River Valley region. Because cotton production doesn’t leave a lot of crop residue in the field, low soil organic matter levels are common. While the benefits of crop rotation are well known, cotton is often grown year after year in the same fields for economic reasons. Soils in the region are generally quite variable, with areas of very high sand content. Winter cover crops and reduced tillage... E. Vories, K. Veum, K. Sudduth