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Andrade, P
Espinas, A
Fernandez, O
Hoffmann, W.C
Kabir, M.S
Zhang, Y
Armstrong, P
Henry, D
Wilson, J.W
Kwon, H
Hu, Q
Santi, A.L
Kickinger, F
Maritan, E
EMİNOĞLU, B.M
Sales, L
Fleming, K
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Authors
Tumenjargal, E
Badarch, L
Ham, W
Kwon, H
Tumenjargal, E
Badarch, L
Ham, W
Kwon, H
Huang, Y
Hoffmann, W.C
Lan, Y
Thomson, S.J
Fritz, B.K
Lan, Y
Zhang, H
Yang, C
Martin, D
Lacey, R
Huang, Y
Hoffmann, W.C
Moulton, P
Lan, Y
Hoffmann, W.C
Westbrook, J
Zaller, M
Zhang, Y
Tremblay, N
Bishop-Hurley, G
Overs, L
Brosnan, S
Krumpholz, A
Henry, D
Yegul, U
TALEBPOUR, B
TÜRKER, U
EMİNOĞLU, B.M
SEYHAN, G.T
ÇOLAK, A
Amado, T.J
Santi, A.L
Corassa, G.M
Bisognin, M.B
Gaviraghi, R
Pires, J.L
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
Roland, L
Lidauer, L
Sattlecker, G
Kickinger, F
Auer, W
Sturm, V
Efrosinin, D
Drillich, M
Iwersen, M
Berger, A
Iwersen, M
Reiter, S
Schweinzer, V
Kickinger, F
Öhlschuster, M
Lidauer, L
Auer, W
Drillich, M
Berger, A
Krieger, S
Oczak, M
Lidauer, L
Kickinger, F
Öhlschuster, M
Auer, W
Drillich, M
Iwersen, M
Berger, A
Schweinzer, V
Lidauer, L
Kickinger, F
Öhlschuster, M
Auer, W
Drillich, M
Iwersen, M
Berger, A
Nagel, P
Fleming, K
Dallago, G.M
Figueiredo, D
Santos, R
Andrade, P
Santos, D
Swe, K.M
Kim, Y
Jeong, D
Lee, S
Chung, S
Kabir, M.S
Dallago, G.M
Figueiredo, D
Santos, R
Andrade, P
Santschi, D.E
Lacroix, R
Lefebvre, D.M
Bhandari, S
Raheja, A
Chaichi, M.R
Green, R.L
Do, D
Ansari, M
Wolf, J.G
Espinas, A
Pham, F.H
Sherman, T.M
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Fleming, K
Schottle, N
Nagel, P
Koch, G
Barbosa, M
Oliveira, L
Tyson, C
Shirley, A
Santos, R
Sales, L
Vargas, R
Han, M
Zhang, N
Armstrong, P
Barbosa, M
Santos, R
Sales, L
Oliveira, L
Topics
Engineering Technologies and Advances
Guidance, Robotics, Automation, and GPS Systems
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Modeling and Geo-statistics
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Precision Dairy and Livestock Management
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Standards & Data Stewardship
Precision Dairy and Livestock Management
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Big Data, Data Mining and Deep Learning
Profitability and Success Stories in Precision Agriculture
Precision Horticulture
Wireless Sensor Networks and Farm Connectivity
Robotics and Automation with Row and Horticultural Crops
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results24 paper(s) found.

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

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

2. 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

3. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton Production

  Crop models simulate growth and development, and provide relevant information for the routine management of the crop.  The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global positioning... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller

4. Evaluation Of The Multiplex® Fluorescence Sensor For The Assessment Of Corn Nitrogen Status

The Multiplex® is a new hand-held optical fluorescence sensor for non-destructive measurement of about 20 parameters descriptive of plant physiological status. The Multiplex is of potential value for in-season assessment of crop nitrogen status, but no evaluation has been released for that matter as of yet. An experiment was therefore conducted which consisted of four nitrogen fertilization treatments with 0, 20, 50... Y. Zhang, N. Tremblay

5. Implementation of ECU For Agricultural Machines Based On IsoAgLib Open Source

In this paper work, we consider implementation of electronic control unit (ECU) for agricultural machineries. Software implementation is based on IsoAgLib library developed by OSB&IT Engineering Company. We modify IsoAgLib and upgrade it for our target system. The IsoAgLib is an object oriented C++ library that has the communication services and management systems according to the ISO 11783 standard. This library allows building ISOBUS compatible equipment without the protocols implementation... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon

6. Design and Implementation of Virtual Terminal Based On ISO11783 Standard for Agricultural Tractors

The modern agricultural machinery most common use of the embedded electronic and remote sensing technology demands adoption of the Precision Agriculture (PA). One of the common devices is the Virtual Terminal (VT) for tractor. The VT’s functions and terminology are described in the ISO11783 standard. This work presents the control system design and implementation of the VT and some Electronic Control Units (ECU) for agricultural vehicles based on the ISO 11783 standard. The VT development... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon

7. Capturing, Demonstrating And Delivering Value From Integrating Real-Time On-Farm Sensing With External Information Flows

The requirement for significant productivity gains in the agricultural sector is undeniable. Sustainable, viable industries must be capable of consistently producing a margin above the base costs of production. This is particularly challenging for the extensive grazing enterprises in Australia as the operating environment has become increasingly complex, dynamic and challenging and there is a continual and increasing need to demonstrate improved efficiency to the wider community... G. Bishop-hurley, L. Overs, S. Brosnan, A. Krumpholz, D. Henry

8. Development of Sensor Reflection Indices To Predict Yield And Protein Content Based On In-Season N Status

Environmental and economic demands make it necessary for farmers to adopt   management systems that improve Nitrogen Use Efficiency. The premium paid to producers has made farmers striving for maximum grain protein levels because protein is a very important quality component of grains and an important attribute in the market place. The protein content of wheat grains approximately ranges from 8 to 20%. The optimization of nitrogen (N) fertilization is the object of intense research efforts... U. Yegul, B. Talebpour, U. TÜrker, B.M. EmİnoĞlu, G.T. Seyhan, A. Çolak

9. Response of Soybean Cultivars According to Management Zones in Southern Brazil

The positioning of soybean cultivars on fields according your environmental response is new strategy to obtain high soybean yields. The aim of this study was to investigate the agronomic response of six soybean cultivars according management zones in Southern Brazil. The study was conducted in 2013/2014 and in two fields located in Boa Vista das Missões, Rio Grande do Sul, Brazil. The experimental design was a randomized complete block in a factorial arrangement (3x6), with three management... T.J. Amado, A.L. Santi, G.M. Corassa, M.B. Bisognin, R. Gaviraghi, J.L. Pires

10. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

11. A Pilot Study on Monitoring Drinking Behavior in Bucket Fed Dairy Calves Using an Ear-Attached Tri-Axial Accelerometer

Accelerometers support the farmer with collecting information about animal behavior and thus allow a reduction in visual observation time. The milk intake of calves fed by teat-buckets has not been monitored automatically on commercial farms so far, although it is crucial for the calves’ development. This pilot study was based on bucket-fed dairy calves and intended (1) to evaluate the technical feasibility of using an ear-attached accelerometer (SMARTBOW, Smartbow GmbH, Weibern, Austria)... L. Roland, L. Lidauer, G. Sattlecker, F. Kickinger, W. Auer, V. Sturm, D. Efrosinin, M. Drillich, M. Iwersen, A. Berger

12. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy Cows

The objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger

13. Ear-Attached Accelerometer as an On-Farm Device to Predict the Onset of Calving in Dairy Cows

The objective of this study on an ear-attached accelerometer in dairy cows was (1) to determine activity, rumination and lying time of the dams prior to calving, and include group level of measured variables (2) use the data to develop an algorithm to predict calving and (3) to test the performance of this algorithm. Video observations (24h/d) were used as reference for these events. Four weeks before expected calving, an ear-tag integrated tri-axial accelerometer (SMARTBOW system) was attached... S. Krieger, M. Oczak, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger

14. Evaluation of the Ear-Tag Sensor System SMARTBOW for Detecting Estrus Events in Indoor Housed Dairy Cows

Livestock farming technologies have a tremendous potential to improve and support farmers in herd management decisions, in particular in reproductive management. Nowadays, estrus detection in cows is challenging and many detection tools are available. The company Smartbow (Weibern, Austria) developed a novel ear-tag sensor, which consists of a 3D-accelerometer that records head and ear movements of cows as basis for algorithm development and further analyses. Estrus detection by the SMARTBOW system... V. Schweinzer, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger

15. Changing the Cost of Farming: New Tools for Precision Farming

Accurate prescription maps are essential for effective variable rate fertilizer application.  Grid soil sampling has most frequently been used to develop these prescription maps.  Past research has indicated several technical and economic limitations associated with this approach.  There is a need to keep the number of samples to a minimum while still allowing a reasonable level of map quality.  As can be seen, precision agriculture management... P. Nagel, K. Fleming

16. Exploring Relationships Between Dairy Herd Improvement Metrics in Minas Gerais – Brazil Dairy Herds

The objective of the present study was to apply principal component analysis (PCA) on Brazilian Dairy Herd Improvement (DHI) data to discover the subset of most meaningful variables to describe complete lactations. The Holstein Livestock Breeders Association of Minas Gerais provided data collected between 2005 and 2016 from 122 dairy farms located in the State of Minas Gerais – Brazil. Twelve numerical variables were selected from the original dataset and four additional variables were created.... G.M. Dallago, D. Figueiredo, R. Santos, P. Andrade, D. Santos

17. Sensor Comparison for Yield Monitoring Systems of Small-Sized Potato Harvesters

Yield monitoring of potato in real time during harvesting would be useful for farmers, providing instant yield and income information. In the study, potentials of candidate sensors were evaluated with different yield measurement techniques for yield monitoring system of small-sized potato harvesters. Mass-based (i.e., load cell) and volume-based (i.e., CCD camera) sensors were selected and tested under laboratory conditions. For mass-based sensing, an impact plate instrumented with load cells... K.M. Swe, Y. Kim, D. Jeong, S. Lee, S. Chung, M.S. Kabir

18. Relationships Between First Test Day Metrics of First Lactation Cows to Evaluate Transition Period

The objective of this study was to apply principal component analysis (PCA) and multiple correspondence analysis (MCA) on Dairy Herd Improvement (DHI) data of animals on their first lactation to discover the most meaningful set of variables that describe the outcome on the first test day. Data collected over 4 years were obtained from 13 dairy herds located in Québec – Canada. The data set was filtered to contain only information from first test day of animals on their first lactation,... G.M. Dallago, D. Figueiredo, R. Santos, P. Andrade, D.E. Santschi, R. Lacroix, D.M. Lefebvre

19. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water Stresses

This paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman

20. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier

21. You Can Not Manage What You Dont Measure

The problem of variability in soil nutrient analysis has been studied for years by a number of industry experts; unable to decipher and commercialize hyperspectral soil sensing. Many studies have taken years of testing to account for variability thathas a dramatic impacts on precision of recommendations. The main tradeoff we have identified is between accuracy and precision. Large quantities of raw data are required... K. Fleming, N. Schottle, P. Nagel, G. Koch

22. UAV Multispectral Data As a Suitable Tool for Predicting Sweetness, Size, and Yield of Vidalia Onions

Vidalia onions is a specialty crop cultivated solely within the southeastern region of Georgia. The key distinguishing characteristic of Vidalia onions is its high sugar content, making them highly prized and widely consumed. Ten thousand acres are grown with Vidalia Onions each year approximately, and the market value (~$150Mi/year) makes the crop very important for the State of Georgia. Traditionally, the planting, weeding, spraying, harvesting, and post-harvesting operations are usually done... M. Barbosa, L. Oliveira, C. Tyson, A. Shirley, R. Santos, L. Sales, R. Vargas

23. Optimizing the Connectivity of Wireless Underground Sensor Networks

In the rapidly evolving field of wireless communication, extending this technology into subterranean realms presents a frontier replete with unique challenges and opportunities. This study explores the intricate dynamics of establishing reliable connectivity in underground environments, a critical component for applications in diverse fields including precision agriculture and environmental monitoring. The distinct characteristics of underground settings impose significant obstacles for wireless... M. Han, N. Zhang, P. Armstrong

24. Advancements in Agricultural Robots for Specialty Crops: a Comprehensive Review of Innovations, Challenges, and Prospects

The emergence of robot technology presents a timely opportunity to revolutionize specialty crop production, offering crucial support across various activities such as planting, supporting general traits, and harvesting. These robots play a pivotal role in keeping stakeholders up-to-date of developments in their production fields, while providing them the capability to automate laborious tasks. Then, to elucidate the advancements in this domain, we present the results of a comprehensive review... M. Barbosa, R. Santos, L. Sales, L. Oliveira