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Carroll, S
Chen, L
Cue, R.I
Gavioli, A
Cosby, A
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Authors
Chen, L
Zhang, R
Xu, G
Zhang, C
Xue, X
Chen, L
Huang , W
Song, X
Zhao, C
Chen, L
Huang, W
Cui, B
Xu, G
Chen, L
Zhang, R
Guo, J
Wang, Y
Chen, L
Zhao, C
Huang, W
Chen, T
Wang , J
Guo, J
Chen, L
wang, X
Zhang, R
Zotarelli, L
Zhang, R
Chen, L
Guo, J
Warren, J.G
Warren, J.G
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Xue, X
Chen, L
Tang, Q
Chen, L
Zhang, R
Xu, M
Xu, G
Yi, T
Zhang, R
Chen, L
Yi, T
Guo, Y
Zhang, H
Betzek, N.M
Souza, E.G
Bazzi, C.L
Schenatto, K
Gavioli, A
Maggi, M.F
Gavioli, A
Souza, E.G
Bazzi, C.L
Betzek, N.M
Schenatto, K
Beneduzzi, H.M
Schenatto, K
de Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Beneduzzi, H.M
Bazzi, C.L
Araujo, R
Souza, E.G
Schenatto, K
Gavioli, A
Betzek, N.M
Hagan, B.A
Cue, R.I
Knight, C.W
Cosby, A
Trotter, M
Schenatto, K
Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Magalhães, P.S
Bazzi, C.L
Jasse, E.P
Souza, E.G
Magalhães, P.S
Michelon, G.K
Schenatto, K
Gavioli, A
Gavioli, A
Souza, E.G
Bazzi, C.L
Betzek, N.M
Schenatto, K
Betzek, N.M
Souza, E.G
Bazzi, C.L
Magalhães, P.G
Gavioli, A
Schenatto, K
Dall'Agnol, R.W
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Topics
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Modeling and Geo-statistics
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Precision Crop Protection
Unmanned Aerial Systems
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Decision Support Systems in Precision Agriculture
Precision Dairy and Livestock Management
Education and Outreach in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Big Data, Data Mining and Deep Learning
Decision Support Systems
Geospatial Data
Decision Support Systems
Type
Poster
Oral
Year
2012
2010
2016
2018
2022
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Authors

Filter results23 paper(s) found.

1. 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

2. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracting... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

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

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

4. 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

5. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton Yield

A long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

6. Spatial Variation Patterns Of Soil Properties And Winter Wheat Growth Parameters In China National Experiment Station For Precison Agriculture

Understanding of spatial patterns of soil properties and crop growth and their relationship is neccesary for variable-rate management of farmland in precision agriculture. This paper presents spatial variation patterns of soil properties such as depth of soil diagnostic horizons, cation exchange capacity, organic matter content, soil solution nutrients concentration, and winter wheat growth and yield parameters in China National Experiment Station for Precison Agriculture.... X. Xue, L. Chen

7. 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

8. Design Of A Data Acquisition System For Weighing Lysimeters

The weighing lysimeter is an important tool for scientists to conduct... C. Zhang, X. Xue, L. Chen, W. Huang

9. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

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

10. 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

11. 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

12. Rectification of Management Zones Considering Moda and Median As a Criterion for Reclassification of Pixels

Management zones (MZ) make economically viable the application of precision agriculture techniques by dividing the production areas according to the homogeneity of its productive characteristics. The divisions are conducted through empirical techniques or cluster analysis, and, in some cases, the MZ are difficult to be delimited due to isolated cells or patches within sub-regions. The objective of this study was to apply computational techniques that provide smoothing of MZ, so as to become viable... N.M. Betzek, E.G. Souza, C.L. Bazzi, K. Schenatto, A. Gavioli, M.F. Maggi

13. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis

The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi

14. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evaluate... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

15. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with better... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

16. A Tool for Monitoring Genetic Selection Differentials in Dairy Herds in Canada

A software tool was developed to allow a dairy producer and/or agricultural advisor to monitor the genetic selection differentials (GSD) that a dairy farm is making. The objectives of this study were (i) to monitor GSD in individual farms, over years, so that producers can be advised as to whether or not they are achieving their selection objectives (and hence optimizing productivity and profitability); (ii) the development of a prototype software tool and visualization model to assist producers... B.A. Hagan, R.I. Cue

17. Utilizing GPS Technology and Science to Improve Digital Literacy Among Students in Australia and the United States of America

A key issue facing regional, rural and remote communities, in both Australia and the United States of America (USA), is the low level of digital literacy among some cohorts of students. This is particularly the case for students involved in agricultural studies where it is commonly perceived that digital literacy is not relevant to their future occupation. However, this perception is far from the truth, as the reality of farming today means students who intend on entering the agricultural workforce... C.W. Knight, A. Cosby, M. Trotter

18. Use of Farmer’s Experience for Management Zones Delineation

In the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this study... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães

19. AgDataBox – API (Application Programming Interface)

E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and plant... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli

20. Variable Selection and Data Clustering Methods for Agricultural Management Zones Delineation

Delineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster analysis.... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto

21. Application of Routines for Automation of Geostatistical Analysis Procedures and Interpolation of Data by Ordinary Kriging

Ordinary kriging (OK) is one of the most suitable interpolation methods for the construction of thematic maps used in precision agriculture. However, the use of OK is complex. Farmers/agronomists are generally not highly trained to use geostatistical methods to produce soil and plant attribute maps for precision agriculture and thus ensure that best management approaches are used. Therefore, the objective of this work was to develop and apply computational routines using procedures and geostatistical... N.M. Betzek, E.G. Souza, C.L. Bazzi, P.G. Magalhães, A. Gavioli, K. Schenatto, R.W. Dall'agnol

22. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

23. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues