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Fageria, N.K
Peralta, D
Evert, F.V
Tavares, T.R
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Authors
Kempenaar, C
Been, T
Evert, F.V
Fageria, N.K
Santos, A.B
Trevisan, R.G
Eitelwein, M.T
Ferraz, M.N
Tavares, T.R
Molin, J.P
Neves, D.C
Tavares, T.R
Molin, J.P
da Silva , T.R
de Carvalho , H.W
De Waele, T
Peralta, D
Shahid, A
De Poorter, E
Topics
Precision Crop Protection
Remote Sensing for Nitrogen Management
Precision Crop Protection
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2014
2008
2018
2022
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1. Use Of Vegetation Indices In Variable Rate Application Of Potato Haulm Killing Herbicides

Variable rate application (VRA) of pesticides based on measured spatial variation in crop biomass is possible with currently available crop reflection sensors (remote and proximity), GNSS technology and modern field sprayers. VRA has the potential to contribute to a more sustainable use of pesticide. Dose rates are optimized based on local requirements at a scale of about 5-50 m2, leading to less adverse side effects, less costs and higher yields. In the longer term, we... C. Kempenaar, T. Been, F.V. Evert

2. Nitrogen Management in Lowland Rice

Rice is staple diet for more than fifty percent of the world population and nitrogen (N) deficiency is one of the major yields limiting constraints in most of the rice producing soils around the world. The lowland rice N recovery efficiency is <50% of applied fertilizers in most agro-ecological regions. The low N efficiency is associated with losses caused by leaching, volatilization, surface runoff, and denitrification. Hence, improving N use efficiency is crucial for higher yields, low cost... N.K. Fageria, A.B. Santos

3. Optimum Spatial Resolution for Precision Weed Management

The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves

4. Predicting Secondary Soil Fertility Attributes Using XRF Sensor with Reduced Scanning Time in Samples with Different Moisture Content

To support future in situ/on-the-go applications using X-ray fluorescence (XRF) sensors for soil mapping, this study aimed at evaluating the XRF performance for predicting organic matter (OM), base saturation (V), and exchangeable (ex-) Mg, using a reduced analysis time (e.g., 4 s) in soil samples with different moisture contents. These attributes are considered secondary for XRF prediction because they do not present emission lines in the XRF spectrum. Ninety-nine soil samples... T.R. Tavares, J.P. Molin, T.R. Da silva , H.W. De carvalho

5. Supervised Feature Selection and Clustering for Equine Activity Recognition

In this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter