Proceedings

Find matching any: Reset
Pordesimo, L.O
Lamker, D
Maldaner, L
Pramanik, S
Kalmar, J
M. Rabello, L
Add filter to result:
Authors
Romier, C
Hyrien, M
Lamker, D
M. Rabello, L
R. D. Pereira, R
C. Lopes, W
Y. Inamasu, R
V. de Sousa, R
Maldaner, L
Molin, J.P
Canata, T.F
Maldaner, L
Canata, T
Molin, J
Passalaqua, B
Quirós, J.J
Nyeki, A
Milics, G
Kovacs, A.J
Neményi, M
Kalmar, J
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Bari, M.A
Bakshi, A
Witt, T
Caragea, D
Jagadish, K
Felderhoff, T
Pramanik, S
Choton, J
Armstrong, P.R
Pordesimo, L.O
Siliveru, K
Gerken, A.R
Serfa Juan, R.O
Topics
Education and Training in Precision Agriculture
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Precision Agriculture and Climate Change
Geospatial Data
Big Data, Data Mining and Deep Learning
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2016
2018
2024
Home » Authors » Results

Authors

Filter results8 paper(s) found.

1. A New Approach to Yield Map Creation

    One of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field.  Numerous data errors in the way the data is collected, poor calibration habits on the part of operators... C. Romier, M. Hyrien, D. Lamker

2. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil

... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa

3. Processing Yield Data from Two or More Combines

Erroneous data affect the quality of yield map. Data from combines working close to each other may differ widely if one of the monitors is not properly calibrated and this difference has to be adjusted before generating the map. The objective of this work was to develop a method to correct the yield data when running two or more combines in which at least one has the monitor not properly calibrated. The passes of each combine were initially identified and three methods to correct yield data were... L. Maldaner, J.P. Molin, T.F. Canata

4. Static and Kinematic Tests for Determining Spreaders Effective Width

Spinner box spreaders are intensively used in Brazil for variable rate applications of lime in agriculture. The control of that operation is a challenging issue because of the complexity involved on the interactions between product and machine. Quantification of transverse distribution of solids thrown from the spinner box spreaders involves dynamic conditions tests where the material deposited on trays is evaluated along the pass of the machinery. There is a need of alternative testing methods... L. Maldaner, T. Canata, J. Molin, B. Passalaqua, J.J. Quirós

5. Climate Sensitivity Analysis on Maize Yield on the Basis of Precision Crop Production

In this paper by prediction we have defined maize yield in precision plant production technologies according to five different climate change scenarios (Ensembles Project) until 2100 and in one scenario until 2075 using DSSAT v. 4.5.0. CERES-Maize decision support model. Sensitivity analyses were carried out. The novelty of the method presented here is that precision, variable rate technologies from relatively small areas (in our case 2500 m2) enable a large amount of data to be collected... A. Nyeki, G. Milics, A.J. Kovacs, M. Neményi, J. Kalmar

6. Identifying and Filtering Out Outliers in Spatial Datasets

Outliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte

7. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging Techniques

The precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and automated... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan

8. Deep Learning to Estimate Sorghum Yield with Uncrewed Aerial System Imagery

In the face of growing demand for food, feed, and fuel, plant breeders are challenged to accelerate yield potential through quick and efficient cultivar development. Plant breeders often conduct large-scale trials in multiple locations and years to address these goals. Sorghum breeding, integral to these efforts, requires early, accurate, and scalable harvestable yield predictions, traditionally possible only after harvest, which is time-consuming and laborious. This research harnesses high-throughput... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff