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Upadhayaya, S.K
Trout, T.J
Znoj, E
Brandão, A.D
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Authors
Ahuja, L.R
Saseendran, S.A
Ma, L
Nielsen, D.C
Trout, T.J
Andales, A.A
Hansen, N.C
Upadhayaya, S.K
Udompetaikul, V
Shafii, M.S
Browne, G.T
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
Baltazar, J.D
Coelho, A.L
de Arruda Viana, L
Brandão, A.D
Valente, D.S
Furtado Jr, M.R
Topics
Modelling and Geo-Statistics
Engineering Technologies
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Agricultural Robotics, Automation, and Mechanization
Type
Oral
Poster
Year
2008
2018
2026
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Filter results4 paper(s) found.

1. Use of a Cropping System Model for Soil-specific Optimization of Limited Water

In the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen

2. A Tree Planting Site-Specific Fumigant Applicator for Orchard Crops

The goal of this research was to use recent advances in the global positioning system and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in the neighborhood of each tree planting site or tree- planting-site-specific application) to decrease the incidence of replant disease, and achieve the environmental and economical benefits of reducing the application of these toxic chemicals. In the first year of this study we retrofitted a chemical applicator... S.K. Upadhayaya, V. Udompetaikul, M.S. Shafii, G.T. Browne

3. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van Vliet

4. Performance of Autonomous Navigation in an Agricultural Tractor Using Pure Pursuit Control and Dubins Path Planning

Autopilot systems in agricultural machinery are primarily designed to ensure accurate tracking of predefined routes. However, their performance is strongly influenced by the internal parameters of the control algorithms employed, which may vary according to operational conditions. In this context, computational simulations constitute a valuable tool for investigating these interactions and identifying optimal operating configurations. This study evaluates an autopilot system based on the Pure... J.D. Baltazar, A.L. Coelho, L. De Arruda Viana, A.D. Brandão, D.S. Valente, M.R. Furtado Jr