Proceedings :: International Society of Precision Agriculture

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Liu, Z

Laurent, P

Harnisch, W

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Authors

Marine, L

Manon, M

Claire, G

Laurent, P

Mostafa, F

Zoran, C

Naima, B

Sébastien, D

Olivier, G

Bajwa, S

Nowatzki, J

Harnisch, W

Schatz, B

Anderson, V

Liu, Z

liu, X

Tian, Y

Zhu, Y

Cao, W

Cao, Q

Topics

Sensor Application in Managing In-season Crop Variability

Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture

Big Data, Data Mining and Deep Learning

Type

Poster

Oral

Year

2012

2014

2024

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Filter results3 paper(s) found.
1. Using Multiplex® to Manage Nitrogen Variability in Champagne Vineyard ... L. Marine, M. Manon, G. Claire, P. Laurent, F. Mostafa, C. Zoran, B. Naima, D. Sébastien, G. Olivier Download paper
2. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management Issues This research project is a “proof-of-concept” demonstrating specific UAS applications in production agriculture. Project personnel will use UAS-mounted sensors to collect data of ongoing crop and livestock research projects during the 2014 crop season at the North Dakota State University (NDSU) Carrington Research Extension Center (CREC). Project personnel will collaborate with NDSU research scientists conducting research at the CREC. During the first year of the project... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson Download paper
3. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning Approach Wheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao Download paper

Filter results3 paper(s) found.

1. Using Multiplex® to Manage Nitrogen Variability in Champagne Vineyard

... L. Marine, M. Manon, G. Claire, P. Laurent, F. Mostafa, C. Zoran, B. Naima, D. Sébastien, G. Olivier

Download paper

2. Verify The Effectiveness Of UAS-Mounted Sensors In Field Crop And Livestock Production Management Issues

This research project is a “proof-of-concept” demonstrating specific UAS applications in production agriculture. Project personnel will use UAS-mounted sensors to collect data of ongoing crop and livestock research projects during the 2014 crop season at the North Dakota State University (NDSU) Carrington Research Extension Center (CREC). Project personnel will collaborate with NDSU research scientists conducting research at the CREC. During the first year of the project... S. Bajwa, J. Nowatzki, W. Harnisch, B. Schatz, V. Anderson

Download paper

3. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning Approach

Wheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao

Download paper