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Parraga, A
McMaster, G.S
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Authors
Naser, M.A
Khosla, R
Haley, S
Reich, R
Longchamps, L
Moragues, M
Buchleiter, G.W
McMaster, G.S
Naser, M.A
Khosla, R
Reich, R
Haley, S
Longchamps, L
Moragues, M
Buchleiter, G.W
McMaster, G.S
de Souza, M.R
Bertani, T.D
Parraga, A
Bredemeier, C
Trentin, C
Doering, D
Susin, A
Negreiros, M
Topics
Remote Sensing Applications in Precision Agriculture
Applications of Unmanned Aerial Systems
Type
Poster
Year
2012
2018
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Authors

Filter results3 paper(s) found.

1. Can Active Sensor Based NDVI Consistently Classify Wheat Genotypes?

ABSTRACT ... M.A. Naser, R. khosla, S. Haley, R. Reich, L. Longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster

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2. Variation in Nitrogen Use Efficiency for Multiple Wheat Genotypes across Dryland and Irrigated Cropping Systems

ABSTRACT ... M.A. Naser, R. Khosla, R. Reich, S. Haley, L. longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster

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3. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural Network

In this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros

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