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Li, Y
Janz, A
TORGBOR, B.A
Recke, G
McClintick-Chess, J
Diago, M
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Authors
Borchert, A
Recke, G
Dabbelt, D
Trautz, D
Olfs, H
Li, Y
Walsh, O.S
Belmont, K
McClintick-Chess, J
Marshall, J
Jackson, C
Thompson, C
Swoboda, K
Walsh, O.S
Belmont, K
McClintick-Chess, J
Saiz-Rubio, V
Diago, M
Tardaguila, J
Gutierrez, S
Rovira-Más, F
Alves, F
Fu, W
Dong, J
Cong, Y
Gao, N
Li, Y
Meng, Z
TORGBOR, B.A
Rahman, M.M
Robson, A
Brinkhoff, J
Thomas, L
Jakimow, B
Janz, A
Hostert, P
Lajunen, A
Topics
Precision Nutrient Management
Precision Carbon Management
Precision Nutrient Management
Sensor Application in Managing In-season Crop Variability
Robotics, Guidance and Automation
Precision Agriculture and Global Food Security
Precision Horticulture
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2016
2018
2022
2024
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Filter results8 paper(s) found.

1. Application Of Precision Agriculture In Carbon Farming Practices Using The Real-time Soil Sensor

... Y. Li

2. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions

... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs

3. UAV-based Crop Scouting for Precision Nutrient Management

Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of wheat... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda

4. Sensor-based Technologies for Improving Water and Nitrogen Use Efficiency

 Limited reports exist on identifying the empirical relationships between plant nitrogen and water status with hyperspectral reflectance. This project is aiming to develop effective system for nitrogen and water management in wheat. Specifically: 1) To evaluate the effects of nitrogen rates and irrigation treatments on wheat plant growth and yield; 2) To develop methods to predict yield and grain protein content in varying nitrogen and water environments, and to determine the minimum nitrogen... O.S. Walsh, K. Belmont, J. Mcclintick-chess

5. Canopy Temperature Mapping with a Vineyard Robot

The wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an opportunity... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves

6. Development of Farmland-Terrain Simulation System for Consistency of Seeding Depth

A farmland-terrain simulation system suitable for rugged topography was designed to study the irregularities of farmland surface morphology led by both topographic fluctuation and terrain tilt. The system consists of terrain simulation mechanism, hydraulic system, control system, etc. The terrain simulation mechanism is connected to the rack through hydraulic cylinder to simulate farmland surface fluctuation. The hydraulic system controls the hydraulic cylinder to drive the terrain simulation... W. Fu, J. Dong, Y. Cong, N. Gao, Y. Li, Z. Meng

7. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern Ghana

The rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retrieved... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff

8. Spectral Imaging Deep Learning Mapper for Precision Agriculture

With the growing variety of RGB cameras, spectral sensors, and platforms like field robots or unmanned aerial vehicles (UAV) in precision agriculture, there is a demand for straightforward utilization of collected field data. In recent years, deep learning has gained significant attention and delivered impressive results in the realm of computer vision tasks, such as semantic segmentation. These models have also found extensive applications in research related to precision agriculture and spectral... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen