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Choi, J
Cammarano, D
Chang, Y
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Authors
Chung, S
Kim, K
Kim, H
Choi, J
Zhang, Y
Kang, S
Han, K
Hur, S
Chung, S
Huh, Y
Choi, J
Ryu, D
Kim, K
Kim, H
Kim, H
Zaman, Q
Chang, Y
Farooque, A.A
Schumann, A
Percival, D
Cheema, M
Esau, T.J
Basso, B
Fiorentino, C
Cammarano, D
D'Errico, A
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Kemeshi, J.O
Gummi, S
Chang, Y
Gummi, S
Kemeshi, J.O
Chang, Y
Kemeshi, J.O
Chang, Y
Yadav, P.K
Alahe, M
Alahe, M
Kemeshi, J.O
Chang, Y
Won, K
Yang, X
Sher, M
Alahe, M
Chang, Y
Kemeshi, J.O
Gummi, S
Menendez III, H
Alahe, M
Gummi, S
Kemeshi, J.O
Chang, Y
Gummi, S
Alahe, M
Chang, Y
Pack, C
Topics
Precision Horticulture
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Edge Computing and Cloud Solutions
Site-Specific Pasture Management
Precision Agriculture and Global Food Security
Robotics and Automation with Row and Horticultural Crops
Type
Poster
Oral
Year
2012
2018
2022
2024
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Authors

Filter results13 paper(s) found.

1. Remote Control System for Greenhouse Environment Using Mobile Devices

Protected crop production facilities such as greenhouse and plant factory have drawn interest and the area is increasing in Korea as well as in other countries in the world. Remote... S. Chung, K. Kim, H. Kim, J. Choi, Y. Zhang, S. Kang, K. han, S. Hur

2. Determination of Sensor Locations for Monitoring of Soil Water Content in Greenhouse

 Monitoring and control of environmental condition is highly important for optimum control of the conditions, especially in greenhouse and plant factor, and the condition... S. Chung, Y. Huh, J. Choi, D. Ryu, K. Kim, H. Kim, H. Kim

3. Spot- Application of Pre-Emergence Herbicide Using a Variable Rate Sprayer in Wild Blueberry

Wild blueberry producers apply herbicides uniformly to control grasses and weeds without considering the significant weed density variability and bare spots within fields. The repeated and excessive use of herbicides... Q. Zaman, Y. Chang, A. Farooque, A. Schumann, D. Percival, M. Cheema, T. Esau

4. Understanding Spatial and Temporal Variability of Wheat Yield: An Integrated System Approach

Spatial variation in soil water and nitrogen are often the causes of crop yield spatial variability due to their influence on the uniformity of plant stand at emergence and for in-season stresses. Natural and acquired variability in production capacity or potential within a field causes uniform agronomic management practices for the field to be correct in some parts and inappropriate in others. To achieve... B. Basso, C. Fiorentino, D. Cammarano, A. D'errico

5. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

6. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

7. R2B2 Project: Design and Construction of a Low-cost and Efficient Autonomous UGV For Row Crop Monitoring

Driving the adoption of agricultural technological advancements like Unmanned Ground Vehicles (UGVs) by small-scale farmers (SSFs) is a major concern for researchers and agricultural organizations. They aim for the adoption of precision farming (PF) by SSFs to increase crop yield to meet the increasing demand for food due to population growth. In the United States, the cost of purchasing and maintaining rugged UGVs capable of precision agricultural operations stands as a barrier to the adoption... J.O. Kemeshi, S. Gummi, Y. Chang

8. Botanix Explorer (BX1): Precision Plant Phenotyping Robot Detecting Stomatal Openings for Precision Irrigation and Drought Tolerance Experiments

Under drought conditions, the kidney-shaped organs on the epidermal surface of plants, called stomata, are crucial to plant health. During transpiration, the stomata, which resemble pores, open and close. When the rate of photosynthesis is balanced, plants can withstand droughts by decreasing their stomatal transpiration. Drought-stressed plants are characterized by a higher number of open stomata. Measuring the pore aperture ratio is essential for precisely quantifying the degree of stomatal... S. Gummi, J.O. Kemeshi, Y. Chang

9. Comparing Global Shutter and Rolling Shutter Cameras for Image Data Collection in Motion on a UGV

In a bid to drive the adoption of precision farming (PF) technology by reducing the cost of developing an Unmanned Ground Vehicle (UGV), during the Reduction-To-Below-Two grand (R2B2) project we compared Arducam’s AR0234, a global shutter camera (GSC) to their IMX462, a rolling shutter camera (RSC). Since the cost of the AR0234 is approximately three times the price of the IMX462, the comparison was done to determine the possibility of using the latter for image data collection in place... J.O. Kemeshi, Y. Chang, P.K. Yadav, M. Alahe

10. Securing Agricultural Data with Encryption Algorithms on Embedded GPU Based Edge Computing Devices

Smart Agriculture (SA) has captured the interest of both the agricultural business and the scientific community in recent years. Overall, SA aims to help the agricultural and food industry to avoid crop failures, loss of revenues as well as help farmers use inputs (such as fertilizers and pesticides) more efficiently by utilizing Internet of Things (IoT) devices and computing systems. However, rapid digitization and reliance on data-driven technologies create new security threats that can defeat... M. Alahe, J.O. Kemeshi, Y. Chang, K. Won, X. Yang, M. Sher

11. Design of an Automatic Travelling Electric Fence System for Sustainable Grazing Management

Fences are used in Precision Livestock Farming (PLF) to prevent herbivores from overgrazing and under grazing forages. While effective in controlling animal entry and exit, traditional fences are not flexible enough to meet the needs of both foraging animals and plants in terms of both nutrient availability and physiological demands. An electric fencing system is a form of traditional fencing that employs an electric charge to create a barrier and dissuade animals or people from crossing it. Even... M. Alahe, Y. Chang, J.O. Kemeshi, S. Gummi, H. Menendez iii

12. Securing Agricultural Imaging Data in Smart Agriculture: a Blockchain-based Approach to Mitigate Cybersecurity Threats and Future Innovations

Smart agriculture (SA) is a new technology that combines the Internet of Things (IoT) with a variety of smart devices, such as drones, unmanned ground vehicles (UGVs), and computer systems. The integration of technology improvements in SA has led to an increase in cybersecurity concerns, specifically pertaining to the protection of sensitive agricultural image data. It’s necessary to better understand SA network systems; establish stronger network structures; identify different types and... M. Alahe, S. Gummi, J.O. Kemeshi, Y. Chang

13. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease Detection

The early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordinated... S. Gummi, M. Alahe, Y. Chang, C. Pack