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Metcalf, S
Parraga, A
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Authors
Dhillon, R
Upadhyaya, S
Roach, J
Crawford, K
Lampinen, B
Metcalf, S
Rojo, F
de Souza, M.R
Bertani, T.D
Parraga, A
Bredemeier, C
Trentin, C
Doering, D
Susin, A
Negreiros, M
Topics
Sensor Application in Managing In-season CropVariability
Applications of Unmanned Aerial Systems
Type
Oral
Poster
Year
2014
2018
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Filter results2 paper(s) found.

1. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut Trees

A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo

2. 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