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Magalhães, P.S
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Authors
Schenatto, K
Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Magalhães, P.S
Bazzi, C.L
Jasse, E.P
Souza, E.G
Magalhães, P.S
Michelon, G.K
Schenatto, K
Gavioli, A
Pereira, F.R
Dos Reis, A.A
Freitas, R.G
Oliveira, S.R
Amaral, L.R
Figueiredo, G.K
Antunes, J.F
Lamparelli, R.A
Moro, E
Pereira, N.D
Magalhães, P.S
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Topics
On Farm Experimentation with Site-Specific Technologies
Big Data, Data Mining and Deep Learning
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Type
Poster
Oral
Year
2018
2022
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Authors

Filter results4 paper(s) found.

1. Use of Farmer’s Experience for Management Zones Delineation

In the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this study... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães

2. AgDataBox – API (Application Programming Interface)

E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and plant... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli

3. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 Data

In recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães

4. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães