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Hofman, V
Xu, J.X
Hur, S
Lafond, J.A
Monroe, T
Zhou, C
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Authors
Chung, S
Kim, K
Kim, H
Choi, J
Zhang, Y
Kang, S
Han, K
Hur, S
Chung, S
Kong, J
Huh, Y
Bae, K
Hur, S
Lee, D
Chae, Y
Chung, S
Kim, K
Huh, Y
Hur, S
Ha, S
Ryu, M
Kim, H
Han, K
Denton, A.M
Mosmen, E.W
Xu, J.X
Gumiere, S.J
Périard, Y
Caron, J
Hallema, D.W
Lafond, J.A
Franzen, D.W
Casey, F
Staricka, J
Long, D
Lamb, J
Sims, A
Halvorson, M
Hofman, V
Zhou, C
Lee, W
Pourreza, A
Schueller, J.K
Liburd, O.E
Ampatzidis, Y
Zuniga-Ramirez, G
Monroe, T
Luck, J.D
Marx, S
Zhou, C
Ampatzidis, Y
Zhou, C
Ampatzidis, Y
Guan, H
Liu, W
de Oliveira Costa Neto, A
Kunwar, S
Batuman, O
Topics
Precision Horticulture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season CropVariability
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Precision Crop Protection
Artificial Intelligence (AI) in Agriculture
Robotics and Automation with Row and Horticultural Crops
Type
Poster
Oral
Year
2012
2014
2008
2022
2024
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Authors

Filter results10 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. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the Day

Several electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environment,... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae

3. Determination of Sensor Locations for Monitoring of Greenhouse Ambient Environment

In protected crop production facilities such as greenhouse and plant factory, f... S. Chung, K. Kim, Y. Huh, S. Hur, S. Ha, M. Ryu, H. kim, K. han

4. Measurement of Systematic Errors in Crop Prediction

Precision agriculture typically attempts to answer grower questions using an increasingly more fine-grained analysis.  However, some entities, such as cooperatives, can have an interest in answers that are spatially course-grained, such as obtaining an estimate of the overall crop production within a season.  Errors in factors that most influence fine-grained predictions, such as soil quality, may have a smaller impact on overall yield forecasts since their effect is likely to average... A.M. Denton, E.W. Mosmen, J.X. Xu

5. Detection Of Drainage Failure In Reconstructed Cranberry Soils Using Time Series Analysis

A cranberry farm is often a semi-closed water system, where water is applied by means of irrigation and drained using an artificial drainage system. Cranberry bogs must be drained to the water level inside the surrounding ditches in order to maintain an optimal pore pressure within the root zone, which is important for a number of reasons. First of all, Phytophthara causing root rot are commonly associated with irrigation with contaminated surface water (Oudemans, 1999)... S.J. Gumiere, Y. Périard, J. Caron, D.W. Hallema, J.A. Lafond

6. Regional Usefulness of Nitrogen Management Zone Delineation Tools

In the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman

7. Strawberry Pest Detection Using Deep Learning and Automatic Imaging System

Strawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality.  However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez

8. Development and Evaluation of a Novel Variable-orifice Nozzle Flow and Droplet Size Control System

Spray drift from crop production operations has been a critical concern across the U.S. as evidenced by the EPA’s efforts to mitigate pesticide drift. Recently, a novel spray control system was developed and evaluated which provided real-time control of both spray droplet size and flow rate. This was achieved via electromechanical control of a variable orifice nozzle along with a novel control system which incorporates real-time weather data to vary system pressure and orifice size and shape.... T. Monroe, J.D. Luck, S. Marx

9. AI-enabled 3D Vision System for Rapid and Accurate Tree Trunk Detection and Diameter Estimation

Huanglongbing (HLB) is the major threat to citrus production in Florida. Imidacloprid and oxytetracycline injections were proven to be effective in controlling HLB. The total amount of imidacloprid and oxytetracycline needs to be injected for the tree depending on the trunk diameter. Therefore, precisely measuring trunk diameter is important to effectively control the HLB. However, manually injecting imidacloprid or oxytetracycline and measuring the trunk diameter is time-consuming and labor-intensive.... C. Zhou, Y. Ampatzidis

10. Agrosense: AI-enabled Sensing for Precision Management of Tree Crops

Monitoring the tree inventory and canopy density and height frequently is critical for researchers and farm managers. However, it is very expensive and challenging to manually complete these tasks weekly. Therefore, a low-cost and artificial intelligence (AI) enhanced sensing system, Agrosense, was developed for tree inventory, canopy height measurement, and tree canopy density classification in this study. The sensing system mainly consisted of four RGB-D cameras, two Jetson Xavier NX, and one... C. Zhou, Y. Ampatzidis, H. Guan, W. Liu, A. De oliveira costa neto, S. Kunwar, O. Batuman