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Chiang, R
Magalhães, P.G
Warner, D
Bolten, A
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Authors
Gnyp, M.L
Panitzki, M
Reusch, S
Jasper, J
Bolten, A
Bareth, G
Warner, D
Lacroix, R
Vasseur, E
Lefebvre, D
Lai, C
Min, C
Chiang, R
Hafferman, A
Morgan, S
Betzek, N.M
Souza, E.G
Bazzi, C.L
Magalhães, P.G
Gavioli, A
Schenatto, K
Dall'Agnol, R.W
Topics
Remote Sensing Applications in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Type
Oral
Poster
Year
2016
2018
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1. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted to... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

2. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning Algorithms

Machine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expensive... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre

3. Precision Agriculture Research Infrastructure for Sustainable Farming

Precision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan

4. Application of Routines for Automation of Geostatistical Analysis Procedures and Interpolation of Data by Ordinary Kriging

Ordinary kriging (OK) is one of the most suitable interpolation methods for the construction of thematic maps used in precision agriculture. However, the use of OK is complex. Farmers/agronomists are generally not highly trained to use geostatistical methods to produce soil and plant attribute maps for precision agriculture and thus ensure that best management approaches are used. Therefore, the objective of this work was to develop and apply computational routines using procedures and geostatistical... N.M. Betzek, E.G. Souza, C.L. Bazzi, P.G. Magalhães, A. Gavioli, K. Schenatto, R.W. Dall'agnol