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Coates, A
Cavayas, F
Parashuramegowda, C.C
Flint, E.A
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Authors
Parashuramegowda, C.C
Tremblay, N
Khun, K
Vigneault, P
Bouroubi, M.Y
Cavayas, F
Codjia, C
Adams, C
Coates, A
Khun, K
Vigneault, P
Fallon, E
Tremblay, N
Codjia, C
Cavayas, F
Flint, E.A
Yost, M
Hopkins, B.G
Topics
Spatial Variability in Crop, Soil and Natural Resources
Unmanned Aerial Systems
Applications of Unmanned Aerial Systems
In-Season Nitrogen Management
Type
Poster
Oral
Year
2014
2016
2018
2022
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Filter results5 paper(s) found.

1. Soil And Crop Spatial Variability In Cotton Grown On Deep Black Cotton Soils

Soil spatial variation is observed under similar management situation in cotton growing soils of Northern Karnataka. In view of this an experiment was conducted to study the spatial variability in soil with respect soil reaction (pH), Electrical conductivity (Ec), Organic carbon (OC%), all major (N,P,K), secondary (Ca, Mg and S) and micronutrients (Fe, Zn, Cu and Mn) by assessing soil nutrients in deep black cotton soils of the experimental station for... C.C. Parashuramegowda

2. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in Corn

Remotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia

3. Using UAV Imagery for Crop Analytics

UAV imagery was collected in April and July of 2017 over a grape vineyard in California’s San Joaquin Valley. Using spectral signatures, a landcover classification was performed to isolate table grapes from the background vegetation and soil. A novel vegetation index was developed based off the unique spectral characteristics of the yellowing effects of chlorosis within the table grape vines. Spatial statistics were run only on the pixels containing grape plants, and a relative vegetation... C. Adams, A. Coates

4. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial Vehicle

Above-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas

5. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping System

Nitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application—with... E.A. Flint, M. Yost, B.G. Hopkins