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Zhang, R
Trotter, M.G
Shanahan, J.F
Westfall, D
Huang, Y
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Authors
Huang, Y
Thomson, S.J
Chen, L
Zhang, R
Xu, G
Huang, Y
Hoffmann, W.C
Lan, Y
Thomson, S.J
Fritz, B.K
Roberts, D.F
Shanahan, J.F
Fergugson, R.B
Adamchuk, V.I
Kitchen, N.R
Ortiz, B
Thomson, S.J
Huang, Y
Reddy, K
Moshia, M.E
Khosla, R
Davis, J
Westfall, D
Xu, G
Chen, L
Zhang, R
Guo, J
Wang, Y
Trotter, M.G
Lamb, D.W
Hinch, G.N
Guppy, C.N
Lamb, D.W
Trotter, M.G
Schneider, D
Shaver, T
Khosla, R
Westfall, D
Shiratsuchi, L
Ferguson, R.B
Shanahan, J.F
Adamchuk, V.I
Slater, G
Guo, J
Chen, L
wang, X
Zhang, R
Zotarelli, L
Sauer, B
Guppy, C.N
Trotter, M.G
Lamb, D.W
Delgado, J.A
Zhang, R
Chen, L
Guo, J
Warren, J.G
Warren, J.G
Lan, Y
Zhang, H
Yang, C
Martin, D
Lacey, R
Huang, Y
Hoffmann, W.C
Moulton, P
Donald, G.E
Trotter, M.G
Lamb, D.W
Levow, G
van Es, H.M
Peterson, G
Westfall, D
Sherrod, L.A
Deng, W
Wang, X
Zhao, C
Huang, Y
Trotter, M.G
Cosby , A.M
Tang, Q
Chen, L
Zhang, R
Xu, M
Xu, G
Yi, T
Zhang, R
Chen, L
Yi, T
Guo, Y
Zhang, H
Lu, J
Miao, Y
Huang, Y
Shi, W
Huang, Y
Brand, H
Pennington, D
Reddy, K
Thomson, S.J
Zhen, X
Miao, Y
Feng, G
Huang, Y
Yang, Z
Liu, P
Bindish, R
Miao, Y
Kechchour, A
Sharma, V
Flores, A
Lacerda, L
Mizuta, K
Lu, J
Huang, Y
Topics
Precision Aerial Application
Engineering Technologies and Advances
Engineering Technologies and Advances
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Precision Livestock Management
Sensor Application in Managing In-season Crop Variability
Precision Carbon Management
Precision Crop Protection
Profitability, Sustainability and Adoption
Precision Crop Protection
Unmanned Aerial Systems
Remote Sensing Applications in Precision Agriculture
Weather and Models for Precision Agriculture
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2010
2014
2016
2024
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Filter results25 paper(s) found.

1. Response and Positioning Accuracy of a Variable-Rate Aerial Application System and Use of Enhanced Imagery for Creation of Prescription Maps

Experiments were conducted to evaluate a variable rate aerial application system in the field, and experiences with iterative system improvement are outlined. Spray cards placed in the field determined application accuracy, and system... Y. Huang, S.J. Thomson

2. Probabilistic Relational Model-based Scheduling Approach for Farmland Soil Sensor Network

  Energy efficiency is one of the core issues of farmland soil sensor network (FSSN). For battery powered FSSN, the energy constraint restricts lifetime of WSN, which poses great challenged to its large scale application. Prior work has suggested approaches to optimize the RF module and communication protocols to reduce power consumption of FSSN. Although shown to be effective... L. Chen, R. Zhang, G. Xu

3. Development Of Unmanned Aerial Vehicles For Site-specific Crop Production Management

... Y. Huang, W.C. Hoffmann, Y. Lan, S.J. Thomson, B.K. Fritz

4. A Crop And Soil Strategy For Sensor-based Variable-rate Nitrogen Management

Crop-based active canopy sensors and soil-based management zones (MZ) are currently being studied as tools to direct in-season variable-rate N application. Some have suggested the integration of these tools as a more robust decision tool for guiding spatially variable N rates. The objectives of this study were to identify (1) soil variables useful for MZ delineation and (2) determine if MZ could be useful in identifying field areas with... D.F. Roberts, J.F. Shanahan, R.B. Fergugson, V.I. Adamchuk, N.R. Kitchen

5. Determination Of Crop Injury From Aerial Application Of Glyphosate Using Vegetation Indices And Geostatistics

Injury to crops caused by off-target drift of glyphosate can seriously reduce growth and yield, and is of great concern to farmers and aerial applicators. Determining an indirect method for assessing the levels and extent of crop injury could support management decisions. The objectives of this study were to evaluate multiple vegetation indices (VIs) as surrogate variables for glyphosate injury identification and to evaluate the combined use of Geostatistical methods and the VIs to assess... B. Ortiz, S.J. Thomson, Y. Huang, K. Reddy

6. Precision Manure Management: It Matters Where You Put Your Manure

“Precision fertilizer management” has been around for more than a decade and is practiced widely in Colorado and elsewhere. By precision, we mean application of fertilizer at the right time, in the right place, and in the right amount. However, “Precision Manure Management” is a relatively new concept that converge the best manure management practices with precision nutrient management practices, such as variable rate nutrient application across site-specific management... M.E. Moshia, R. Khosla, J. Davis, D. Westfall

7. Study On Application Of Wireless Sensor Networks For Precision Agriculture

  Abstract: The use of sensor network to achieve soil moisture real-time detection can provide the decision-making basis for precision agriculture. In this... G. Xu, L. Chen, R. Zhang, J. Guo, Y. Wang

8. GNSS Tracking Of Livestock: Towards Variable Fertilizer Strategies For The Grazing Industry

This study reveals the potential for GPS tracking in the grazing industry. By monitoring the locations and movement of livestock, times of peak grazing activity can be identified and these can in turn produce maps of preferred grazing areas, and by examining residency times provide an indication of spatial variability in grazing pressure. A comparison of grazing preference can be made to similarly inferred camping areas to understand the potential redistribution of nutrients within a paddock.... M.G. Trotter, D.W. Lamb, G.N. Hinch, C.N. Guppy

9. Ultra Low Level Aircraft (ULLA) As A Platform For Active Optical Sensing Of Crop Biomass

Crop producers requiring crop biomass maps to support timely application of in-season fertilisers, pesticides or growth regulators rely on either on-ground active sensors or airborne/satellite imagery. Active crop sensing (for example using Yara N-SensorTM, GreenseekerTM or CropcircleTM) can only be used when the crop is accessible by person or vehicle, and extensive, high-resolution coverage is time consuming. On the other hand, airborne or satellite imaging is... D.W. Lamb, M.G. Trotter, D. Schneider

10. Development Of A Nitrogen Requirement Algorithm Using Ground-based Active Remote Sensors In Irrigated Maize

Studies have shown that normalized difference vegetation index (NDVI) from ground-based active remote sensors is highly related with leaf N content in maize (Zea mays). Remotely sensed NDVI imagery can provide valuable information about in-field N variability in maize and significant linear relationships between sensor NDVI and maize grain yield have been found suggesting that an N recommendation algorithm based on NDVI could optimize N application. Therefore, a study was conducted using the two... T. Shaver, R. Khosla, D. Westfall

11. Comparison Of Spectral Indices Derived From Active Crop Canopy Sensors For Assessing Nitrogen And Water Status

... L. Shiratsuchi, R.B. Ferguson, J.F. Shanahan, V.I. Adamchuk, G. Slater

12. The Effect Of Variable-Rate Fertilizer Nitrogen Decision-Making On Winter Wheat

Precision ... J. Guo, L. Chen, X. Wang, R. Zhang, L. Zotarelli

13. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol Soil

Crop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado

14. Energy-efficient Wireless Sensor Network System For Soil Moisture Information Collecting

Collecting field soil moisture information is the foundation of auto-irrigation. This paper introduced a soil moisture information collecting system based on wireless sensor network (WSN) technology and with application background of automatic drip irrigation for cotton field. Firstly, application background was analyzed and application requirement was defined. The system worked together with a drip irrigation system in cotton field. After study, it was found that the output of soil moisture sensor... R. Zhang, L. Chen, J. Guo, J.G. Warren, J.G. Warren

15. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field Mapping

  A wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by synthesizing... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton

16. Precision Livestock Management: An Example Of Pasture Monitoring In Eastern Australian Pastures Using Proximal And Remote Sensing Tools

  Pasture monitoring Australian rangelands by Remote Sensing   G.E.Donald.  CSIRO Livestock Industries, Locked Bag 1, Armidale NSW, 2350 Australia     A series of spatial models and datasets were jointly developed to estimate pasture biomass as feed on offer (FOO®) and pasture growth rate (PGR®) in the south-west... G.E. Donald, M.G. Trotter, D.W. Lamb, G. Levow, H.M. Van es

17. Landscape Position And Climatic Gradient Impacts On Carbon Turnover in Dryland Cropping Systems in Colorado

  Soil organic carbon has decreased in cultivated wheat-fallow systems due to increased carbon oxidation, low carbon input and soil erosion.  Implementation of more intensive cropping with no-till management has reversed the trend in soil carbon loss.  Our objective in this presentation is to review the effects of landscape position on soil carbon status as related to intensification of cropping system.  Our analysis will... G. Peterson, D. Westfall, L.A. Sherrod

18. Weed Identification From Seedling Cabbages Using Visible And Near-Infrared Spectrum Analysis

Target identification is one of the main research content and also a key point in precision crop protection. The main purpose of the study is to choose the characteristic wavelengths (CW for short) to classify the cabbages and the weeds at their seedling stage using different data analysis methods. Using a handheld full-spectrum FieldSpec-FR, the canopies of the seedling plants, cabbage ‘8398, cabbage ‘zhonggan’, Barnyard grass, green foxtail, goosegrass,... W. Deng, X. Wang, C. Zhao, Y. Huang

19. Introducing Precision Agriculture To High School Students In Australia

There is a growing need for tertiary qualified graduates in the Australian agricultural industry with only 7% of those employed in the sector holding a tertiary qualification compared to over 25% for the national workforce. With the need to greatly increase food and fibre production to feed and clothe a growing global population, and the adoption of precision agriculture technologies playing a huge part in this task, it is worrying that the demand for tertiary courses in agriculture in Australia... M.G. Trotter, A.M. Cosby

20. Airspeed and Pressure Affect Spray Droplet Spectrum from an Aerial Nozzle for Fixed-wing Applications

The atomization of the droplets generated by a flat fan nozzle has been studied in the IEA-I high speed wind tunnel at NERCIEA with Marvern Spraytec Laser Diffraction system. The measurement point is set at 0.15m, 0.25m and 0.35m away from the orifice of the nozzle. The wind speed range is from 150km/h to 305km/h, and the tube pressure is set about 0.3MPa, 0.4MPa and 0.5MPa. The measuring distance from the orifice of the nozzle is found important to the diameter and relative span of the droplets.... Q. Tang, L. Chen, R. Zhang, M. Xu, G. Xu, T. Yi

21. Development of a PWM Precision Spraying System for Unmanned Helicopter

Application of protection materials is a crucial component in the high productivity of agriculture. Motivated by the needs of aerial precision application, in this paper we present a pulse width modulation (PWM) based precision spraying system for unmanned helicopter. The system is composed of the tank, pipelines, pump, nozzles and the automatic control unit. The system can spray with a constant rate automatically when the speed of the UAV fluctuates between 1 m/s to 8 m/s. The application rate... R. Zhang, L. Chen, T. Yi, Y. Guo, H. Zhang

22. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote Sensing

Active crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing system... J. Lu, Y. Miao, Y. Huang, W. Shi

23. Assessing Soybean Injury from Dicamba Using RGB and CIR Images Acquired on Small UAVs

Dicamba is an herbicide used for postemegence control of several broadleaf weeds in corn, grain sorghum, small grains, and non-cropland. Currently, dicamba-tolerant (DT) soybean and cotton are under development, which provide new options to combat weeds resistant to glyphosate, the most widely used herbicide.  With the use of DT-trait cotton and soybean, off-target dicamba drift onto susceptible crops will become a concern. To relate soybean injury to different rates of dicamba applications,... Y. Huang, H. Brand, D. Pennington, K. Reddy, S.J. Thomson

24. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang

25. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote Sensing

For irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang