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Laboski, C
Kisekka, I
Kiel, A
Hoffmann, W.C
Amado, T.J
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Authors
Hoffmann, W.C
Lan, Y
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Amado, T.J
Santi, A.L
Corassa, G.M
Bisognin, M.B
Gaviraghi, R
Pires, J.L
Corassa, G.M
Amado, T.J
Schwalbert, R.A
Reimche, G.B
Dalla Nora, D
Horbe, T.
Tabaldi, F.M
Kyveryga, P.M
Fey, S
Connor, J
Kiel, A
Muth, D
Drechsler, K
Kisekka, I
Upadhyaya, S
Sapkota, A
Roby, M
Chen, C
Kisekka, I
Topics
Precision Aerial Application
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Agriculture for Sustainability and Environmental Protection
Type
Poster
Oral
Year
2012
2016
2018
2024
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Filter results7 paper(s) found.

1. Current Status and Future Directions of Precision Aerial Application For Site-Specific Crop Management In The USA

Precision agriculture includes different technologies that allow agricultural professional to use information management tools to optimize agriculture production. The new technologies allow aerial application applicators to improve application accuracy and efficiency, which saves time and money for the farmer and the pilot. The USDA-ARS-Aerial Application Technology group has an active research component in precision... W.C. Hoffmann, Y. Lan

2. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

3. 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

4. High-resolution Mapping with On-the-go Soil Sensor and Its Relation with Corn Yield and Soil Acidity in a Dystrophic Red Oxisol

Spatial representations of soil attributes with low resolution can lead to gross errors of recommendation and compromise the efficiency of soil corrections and consequently the grain yield. However, obtaining the spatial variability of soil attributes with high resolution by soil sampling is not recommended because of its large time spent and high cost of laboratory analysis what makes difficult their large-scale application. This way, the on-the-go soil sensing has been used in precision agriculture... G.M. Corassa, T.J. Amado, R.A. Schwalbert, G.B. reimche, D. Dalla nora, T. . horbe, F.M. tabaldi

5. Within-field Profitability Assessment: Impact of Weather, Field Management and Soils

Profitability in crop production is largely driven by crop yield, production costs and commodity prices. The objective of this study was to quantify the often substantial yet somewhat illusive impact of weather, management, and soil spatial variability on within-field profitability in corn and soybean crop production using profitability indices for profit (net return) and return-on-investment (ROI) to produce estimates. We analyzed yield and cropping system data provided by 42 farmers within Central... P.M. Kyveryga, S. Fey, J. Connor, A. Kiel, D. Muth

6. A Comprehensive Stress Index for Evaluating Plant Water Status in Almond Trees

This study evaluated a comprehensive plant water stress index that integrates the canopy temperature and the environmental conditions that can assist in irrigation management. This index—Comprehensive Stress Index (CSI)—is based on the reformulation of the leaf energy balance equation. Specifically, CSI is the ratio of the temperature difference between a dry leaf (i.e. a leaf with a broken stem) and a live leaf (on the same tree) [i.e. Tdry-Tleaf] and the difference between the vapor... K. Drechsler, I. Kisekka, S. Upadhyaya

7. Estimating Spatial and Temporal Variability in Soil Respiration Using UAV-based Multispectral and Thermal Images in an Irrigated Pistachio (Pistachia Vera L.) Orchard

Soil respiration (Rs) accounts for the autotrophic and heterotrophic respiration happening in the soil and is a major component of the carbon budget of agricultural ecosystems. Rs is controlled by various interactive factors, including soil moisture, temperature, soil properties, and vegetation productivity. To quantify the carbon budget of climate-smart agriculture systems, it is necessary to understand how irrigation and cover cropping management practices impact... A. Sapkota, M. Roby, C. Chen, I. Kisekka