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Reinholz, A
Liping, C
Dalal, A
Liu, W
Lee, J
Lowenberg‑DeBoer, J
Ludewig, U
Xu, J
Lord, E
Xie, R
Rosen, C
Landivar-Scoot, J.L
Landivar, J.A
LENOIR, A
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Authors
Guangwei, W
Zhijun, M
Liping, C
Weiqiang, F
Jianjun, D
Nigon, T.J
Rosen, C
Mulla, D
Cohen, Y
Alchanatis, V
Rud, R
Cohen, Y
Alchanatis, V
Heuer, B
Lemcoff, H
Sprintsin, M
Rosen, C
Mulla, D
Nigon, T
Dar, Z
Cohen, A
Levi, A
Brikman, R
Markovits, T
Rud, R
Yang, C
Odvody, G.N
Fernandez, C.J
Landivar, J.A
Nichols, R.L
Huh, Y
Chung, S
Chae, Y
Lee, J
Kim, S
Choi, M
Jung, K
Momsen, E
Xu, J
Franzen, D.W
Nowatzki, J.F
Farahmand, K
Denton, A.M
Lee, K
Chung, S
Lee, J
Kim, S
Kim, Y
Choi, M
Khakbazan, M
Moulin, A
Huang, J
Michiels, P
Xie, R
Bohman, B
Mulla, D
Rosen, C
Al Amin, A
Lowenberg‑DeBoer, J
Franklin, K
Behrendt, K
LENOIR, A
VANDOORNE, B
DUMONT, B
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Mizuta, K
Zhang, J
Li, D
Weinmann, M
Nkebiwe, M
Weber, N
Bradacova, K
Morad-Talab, N
Ludewig, U
Müller, T
Neumann, G
Raupp, M
Bradacova, K
Boatswain Jacques, A.A
Diallo, A.B
Cambouris, A
Lord, E
Fallon, E
Lord, E
Boatswain Jacques, A.A
Diallo, A.B
Khakbazan, M
Cambouris, A
Cambouris, A
Duchemin, M
Lord, E
Ziadi, N
Javed, B
Nze Memiaghe, J.D
Ramirez-Gonzalez, D.A
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Kaloya, T
Sharda, A
Dalal, A
Zhou, C
Ampatzidis, Y
Guan, H
Liu, W
de Oliveira Costa Neto, A
Kunwar, S
Batuman, O
Fernandez, O
Bhandari, M
Landivar-Scoot, J.L
Eldefrawy, M
Zhao, L
Landivar, J
Schumacher, L
Flores, P
Sun, R
Reinholz, A
Topics
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Profitability and Success Stories in Precision Agriculture
In-Season Nitrogen Management
Robotics, Guidance and Automation
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Precision Crop Protection
Robotics and Automation with Row and Horticultural Crops
Data Analytics for Production Ag
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
2024
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Filter results21 paper(s) found.

1. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China in... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

2. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management

... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud

3. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial Images

Potato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud

4. Evaluating Spectral Measures Derived From Airborne Multispectral Imagery for Detecting Cotton Root Rot

Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is one of the most destructive plant diseases occurring... C. Yang, G.N. Odvody, C.J. Fernandez, J.A. Landivar, R.L. Nichols

5. Design And Construction Of An Ultrasonic Cutting Width Sensor For Full-Feed Type Mid-Sized Multi-Purpose Combines

Precision agriculture analyzes the spatial variability according to the characteristics of an optimum setting of agricultural materials. To raise the profitability of agriculture and to reduce the environmental impact, technological research and development of precision agriculture has been conducted. In Asian countries such as Japan... Y. Huh, S. Chung, Y. Chae, J. Lee, S. Kim, M. Choi, K. Jung

6. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield Prediction

Yield predictions based on remotely sensed data are not always accurate.  Adding meteorological and other data can help, but may also result in over-fitting.  Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the sugar... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton

7. Post Processing Software for Grain Yield Monitoring System Suitable to Korean Full-feed Combines

Precision agriculture (PA) has been adopted in many countries and crop and country specific technologies have been implemented for different crops and agricultural practices. Although PA technologies have been developed mainly in countries such as USA, Europe, Australia, where field sizes are large, need of PA technologies has been also drawn in countries such as Japan and Korea, where field sizes are relatively small (about 1 ha). Although principles are similar, design concept and practical... K. Lee, S. Chung, J. Lee, S. Kim, Y. Kim, M. Choi

8. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case Study

Precision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are described... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie

9. Evaluating Remote Sensing Based Adaptive Nitrogen Management for Potato Production

Conventional nitrogen (N) management for potato production in the Upper Midwest, USA relies on using split-applications of N fertilizer or a controlled release N product. Using remote sensing to adaptively manage N applications has the potential to improve N use efficiency and reduce losses of nitrate to groundwater, which are important regional concerns. A two-year plot-scale experiment was established to evaluate adaptive N-management using remote sensing compared to conventional practices for... B. Bohman, D. Mulla, C. Rosen

10. Economics of Field Size for Autonomous Crop Machines

Field size constrains spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare... A. Al amin, J. Lowenberg‑deboer, K. Franklin, K. Behrendt

11. A Low-tech Approach to Manage Within Field Variability – Toward a Territorial Scale Application

Managing within field variability is promising to achieve European objectives of sustainability in crop production. Technological development has allowed to precisely characterize fields heterogeneity in space and time. However, learnings from low adoption of yield maps in west-European context have highlighted the importance of reliable methods to support decisions. Blackmore et al. designed a delineation method considering yield as an integrative variable that reflects spatial and temporal... A. Lenoir, B. Vandoorne, B. Dumont

12. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine Learning

Precision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li

13. Bio-Effectors As a Promising Tool for Precision Agriculture and Integrated Plant Nutrition

Bio-effectors, such as microorganisms and active natural compounds, are of increasing interest as promising alternatives or substitutes to precarious agrochemicals. European and global markets (valued at 14.6 billion US$ in 2023) for agricultural biologicals (bio-pesticides, bio-fertilizers, and bio-stimulants) are predicted to grow at rates of more than 13.5 % per year. Improved availability and use efficiency of mineral nutrients, tolerance to abiotic stresses, yield and quality traits, as well... M. Weinmann, M. Nkebiwe, N. Weber, K. Bradacova, N. Morad-talab, U. Ludewig, T. Müller, G. Neumann, M. Raupp, K. Bradacova

14. Incorporating Return on Investment for Profit-driven Management Zones

Adopting site-specific management practices such as profitability zones can help to stabilize long-term profit while also favoring the environment. Profitability maps are used to standardize data by converting variables into economic values ($/ha) for different cropping systems within a field. Thus, profitability maps can be used to define management zones from several years of data and show the regions within a field which are more profitable to invest in for production, or those that can be... A.A. Boatswain jacques, A.B. Diallo, A. Cambouris, E. Lord, E. Fallon

15. Deep Learning for Predicting Yield Temporal Stability from Short Crop Rotations

Investigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris

16. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision Experimentation

Assessing the spatial variability of soil properties represents an important issue for on-farm sustainable management owing to high cost of sampling densities. Actual methods of soil properties measurement are based on conventional soil sampling of one sample per ha, followed by laboratory analysis, requiring many soil extraction processes and harmful chemicals. This conventional laboratory analysis does not allow exploring spatial variation of soil properties at desired fine spatial scale. Thus,... A. Cambouris, M. Duchemin, E. Lord, N. Ziadi, B. Javed, J.D. Nze memiaghe, D.A. Ramirez-gonzalez

17. Evaluating Different Strategies for In-season Potato Nitrogen Status Diagnosis Using Two Leaf Sensors

Accurate and efficient in-season diagnosis of potato nitrogen (N) status is key to the success of in-season N management for improved profitability and environmental protection. Sensor-based approaches will support more timely decision making compared to plant tissue-based approaches. SPAD-502 (SPAD; Konica Minolta, Tokyo, Japan) is a commonly used sensor for potato N status diagnosis. Dualex Scientific+ (Dualex; METOS® by Pessl Instruments, Weiz, Austria) is a new leaf chlorophyll... S. Wakahara, Y. Miao, S. Gupta, C. Rosen

18. Quantifying Boom Movement in Agricultural Sprayer Booms Using Neural Networks for Real-world Field Scenarios

Application rate errors in self-propelled agricultural sprayers remain a significant concern, necessitating a comprehensive understanding of boom movement during actual field operating scenarios. This study introduces new objectives to quantify boom movement across commercial sprayers when operated by different individuals and compares these movements among various machines. The goal is to develop a metric that identifies potential improvement needs for boom height control system. The approach... T. Kaloya, A. Sharda, A. Dalal

19. 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

20. Ground-based Imagery Data Collection of Cotton Using a Robotic Platform

In modern agriculture, technological advancements are pivotal in optimizing crop production and resource management. Integrating robotics and image processing techniques allows the efficient collection, analysis, and storage of high-resolution images crucial for monitoring crop health, identifying pest infestations, assessing growth stages, making precise management decisions and predicting yield potential. The objective of this project is to utilize the Farm-NG Amiga robot to develop an image... O. Fernandez, M. Bhandari, J.L. Landivar-scoot, M. Eldefrawy, L. Zhao, J. Landivar

21. North Dakota State University - Sponsor Presentation

... L. Schumacher, P. Flores, R. Sun, A. Reinholz