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Decision Support Systems
Precision Dairy and Livestock Management
On Farm Experimentation with Site-Specific Technologies
ISPA Community: Nitrogen
On Farm Experimentation with Site-Specific Technologies
Genomics and Precision Agriculture
Precision Crop Protection
Education of Precision Agriculture Topics and Practices
Robotics and Automation with Row and Horticultural Crops
Precision Crop Protection
Site-Specific Pasture Management
ISPA Community: OFEC
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Authors
Abd Aziz, S
Abdol Lajis, G
Abonyi, J
Abu Seman, I
Adamchuk, V
Adolwa, I
Adolwa, I
Ahamed, T
Ahmed, M
Akin, S
Akorede, B.A
Al-Busaidi, A
Alahe, M
Alheidary, M.H
Alizadeh, E
Amaral, L.R
Amely, N
Ampatzidis, Y
Andersen, P
Archontoulis, S
Ardigueri, M
Arnall, B
Aryal, B
Arzani, H
Attanayake, A.U
Azzam, T
BAdua, S
BISCAMPS, J
Badua, S
Balboa, G
Balboa, G
Barbosa, M
Barker, D
Batchelor, W.D
Batuman, O
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bean, G.M
Becker, M
Bedwell, E
Beeri, O
Behera, S
Bejo, S
Bennett, B
Benő, A
Betzek, N.M
Bhandari, M
Bojer, O.M
Bouroubi, Y
Brorsen, W
Brorsen, W
Byers, C
CAMPOS, J
Cafaro La Menza, N
Callegari, D
Camberato, J.J
Cambouris, A
Campos, L.B
Carter, P.R
Cesario Pinto, J
Chang, Y
Colley III, R
Costa Barboza, T.O
Cugnasca, C.E
DEBANGSHI, U
Da Silva, J
Dalal, A
Dalla Betta, M.M
Derrick, J
Dong, R
Dossou-Yovo, E.R
Douzals, J
Downing, B
Dua, S
Duary, B
Duchemin, M
Duddu, H.U
Dutta, W
Dynes, R
Dyrmann, M
Eberz-Eder, D
Edge, B
Eitelwein, M.T
Enger, B.D
Esau, K
Fajardo, M
Farooque, A
Felipe dos Santos, A
Ferguson, R.B
Fernández, F.G
Ferraz, M.N
Flippo, D
Foster, J
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Frimpong, K.A
Fu, X
Fulton, J
Fulton, J.P
Fulton, J.P
Fulton, J.P
Fulton, J.P
Fulton, J.P
Gadhwal, M
Garcia-Ruíz, F
Gauci, A
Gavioli, A
Gaynor, P
Ghansah, B
Gigena, B
Gil, E
Gilson, A
Gimenez, L.M
Gnatowski, T
Green, O
Guan, H
Gummi, S
Hansen, J
Harsha Chepally, R
Harsha Chepally, R
Hartschuh, J.M
Hartschuh, J.M
Hawkins, E
Hawkins, E
Hegedus, P
Henties, T
Hinze, J
Huang, L
Hunhoff, L
Jakhar, A
Javed, B
Jayasuriya, H
Jensen, N
Jermy, M
Johnson, E.U
Johnson, J
Jones, J
Jones, N
Jorgensen, R.N
Joseph, K
Jørgensen, R.N
Kabaliuk, N
Kagami Taira, F
Kaloya, T
Karkee, M
Kaur, G
Khot, L
Khuimphukhieo, I
King, W
Kitchen, N.R
Kocsis, M
Krmenec, A
Kross, A
Kulhandjian, H
Kulhandjian, H
Kulhandjian, M
Kulhandjian, M
Kunwar, S
Laboski, C.A
Lacerda, L
Lacroix, R
Lapen, D
Laurenson, S
Lee, J
Lemus, S
Leszczyńska, R
Lexow, T
Li, D
Li, H
Li, S
Li, X
Liakos, V
Liang, X
Lindsey, A
Liu, W
Loewen, S
Longchamps, L
Lord, E
Lu, J
Lu, Y
Luck, J.D
Luck, J.D
Luck, J.D
Luck, J.D
MacAuliffe, R
Magalhaes, P.G
Makarov, J
Manning, M
Martello, M
Marx, S
Matavel, C
Maxwell, B
Maxwell, B.D
May-tal, S
McLendon, A
McNairn, H
Meena, R.K
Meng, L
Meyer, T
Meyer-Aurich, A
Miao, Y
Miao, Y
Miao, Y
Michelon, G.K
Mieno, T
Mieno, T
Mieno, T
Minyo, R
Mizuta, K
Molin, J.P
Molina Cyrineu, I
Monroe, T
Morata, G.T
Mostaço, G.M
Mueller, N
Mulla, D.J
Murrell, T
Mutegi, J
Muthamia, J
Muvva, V
Mwunguzi, H
Nafziger, E.D
Nafziger, E.D
Negrini, R.P
Negrini, R.P
Neves, D.C
Ng, C
Nugent, C.I
Nze Memiaghe, J.D
Odoom, E
Oliveira, L
Oliveira, L.P
Ortiz, B.V
Paccioretti, P
Paccioretti, P
Pack, C
Pagani, A
Patterson, C
Peiretti, J
Peiretti, J
Pereira de Souza, F
Perry, C
Persch, J.R
Phillips, S
Phillips, S
Phillips, S
Piepho, H
Pitla, S
Pitla, S
Piya, N.K
Piya, N.K
Pokharel, P
Port, K
Porter, W
Post, S
Poursina, D
Poursina, D
Puntel, L
Puntel, L
Puntel, L
Quirós, J.J
Rabia, A.H
Rains, G
Raitz Persch, J
Ramasamy, R.P
Ramirez-Gonzalez, D.A
Ransom, C.J
Raz, J
Rehman, T
Roberts, A
Rocha, D
Rodrigues Alves Franchi, M
Rojo, F
Rud, R
Rudy, H
Rydahl, P
SALCEDO, R
Saito, K
Salem, M.A
Sales, L
Salunga, N.G
Samborski, S.M
Sanches, G.M
Santos, R
Sapkota, R
Sawyer, J.E
Schenatto, K
Schenatto, K
Scholz, O
Schuenemann, G.M
Schumann, A
Scott, J.L
Scudiero, E
Shanahan, J.F
Sharda, A
Sharda, A
Sharda, A
Sharda, A
Sharda, A
Sharda, A
Sharda, A
Sharry, R
Shearer, S.A
Shearer, S.A
Shearer, S.A
Shinde, S
Shirtliffe, S.U
Sinfort, C
Singh, R
Sisák, I
Skovsen, S
Sleichter, R
Sorensen, M.D
Souza, E.G
Souza, I.R
Squires, T
Starek, M
Stelford, M
Suleiman, A.A
Sunohara, M
Syed, H.H
Szabó, K
Szatylowicz, J
Sørensen, C.G
Tavares, T.R
Taylor, A
Thompson, L
Thompson, L
Thornton, M
Tietje, R
Tobaldo, B
Trefz, K
Tremblay, N
Trevisan, R.G
Tucker, M
Uhrmann, F
Upadhyaya, S
Valente, I.Q
Vellidis, G
Venkatesh, R
Virk, S
Walsh, O
Wang, J
Wang, X
Weiß, C
Werner, A
Weule, M
Whelan, B
White, M
Wilson, D
Wu, D
Wölbert, E
Xu, J
Yang, L
Zaman, Q
Zhou, C
Ziadi, N
Zingore, S
Zingore, S
Zydenbos, S
de Menezes, P.L
de Oliveira Costa Neto, A
tao, H
van Vliet, L
Topics
Precision Crop Protection
Decision Support Systems
On Farm Experimentation with Site-Specific Technologies
Robotics and Automation with Row and Horticultural Crops
Site-Specific Pasture Management
Education of Precision Agriculture Topics and Practices
Precision Crop Protection
On Farm Experimentation with Site-Specific Technologies
ISPA Community: Nitrogen
Genomics and Precision Agriculture
Precision Dairy and Livestock Management
Type
Oral
Poster
Year
2018
2024
2022
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Topics

Filter results87 paper(s) found.

1. Experimental Study Using Wind Tunnel for Measuring Variability of Spray Drift Sedimentation

Spray drift is defined as physical movement of pesticides by air action as a particle droplet and is not deposited on the intended target. Evaluation of the parameters affecting on spray drift is difficult. The accurate studies are expensive, as well as, the variability is high under field conditions due to instability in wind speed and turbulence. Wind tunnel experiments are adequate to simulate the results of field measurements for spray drift. A laboratory experiments were carried out to s... M.H. Alheidary, J. Douzals, C. Sinfort

2. Grazing System and Solar Fences, Innovation and Opportunity in Rangeland of Developing Countries

The future of the development and management of pasture resources depends on increasing the use of scientific innovations. In some countries rangeland livestock production majority relies on natural ecological processes of plant and animal production, despite the progress in all of the infrastructure, rangeland management have a little growth and base on traditional ranching management, grazing livestock is based on a free grazing system. In this study grazing system was applied and electric ... H. Arzani, E. Alizadeh

3. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry Harvesting

Wild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the p... K. Esau, Q. Zaman, A. Farooque, A. Schumann

4. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?

This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed wit... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis

5. Rapid Identification of Mulberry Leaf Pests Based on Near Infrared Hyperspectral Imaging

As one of the most common mulberry pests, Diaphania pyloalis Walker (Lepidoptera: Pyralididae) has occurred and damaged in the main sericulture areas of China. Naked eye observation, the most dominating method identifying the damage of Diaphania pyloalis, is time-wasting and labor consuming. In order to improve the identification and diagnosis efficiency and avoid the massive outbreak of Diaphania pyloalis, near infrared (NIR) hyperspectral imaging technology combined with partial least discr... L. Yang, L. Huang, L. Meng, J. Wang, D. Wu, X. Fu, S. Li

6. Optimum Spatial Resolution for Precision Weed Management

The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the object... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves

7. Real-Time Control of Spray Drop Application

Electrostatic application of spray drops provides unique opportunities to precisely control the application of pesticides due to the additional electrostatic force on the spray drops, in addition to the normally seen forces of aerodynamic drag, gravity, and inertia. In this work, we develop a computational model to predict the spray drop trajectories. The model is validated through experiments with high speed photography of spray drop trajectories, and quantification of which trajectories lea... S. Post, M. Jermy, P. Gaynor, N. Kabaliuk, A. Werner

8. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenou... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

9. Spatial Variability of Optimized Herbicide Mixtures and Dosages

Driven by 25 years of Danish, political 'pesticide action plans', aiming at reducing the use of pesticides, a Danish Decision Support System (DSS) for Integrated Weed Management (IWM) has been constructed. This online tool, called ‘IPMwise’ is now in its 4th generation. It integrates the 8 general IPM-principles as defined by the EU. In Denmark, this DSS includes 30 crops, 105 weeds and full assortments of herbicides. Due to generic qualities in both the integrat... P. Rydahl, R.N. Jorgensen, M. Dyrmann, N. Jensen, M.D. Sorensen, O.M. Bojer, P. Andersen

10. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape Attributes

One of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity i... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes

Showing 1 to 10 of 87 entries