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Rose, D
Bhardwaj, M
Yule , I
Feng, H
Prince Czarnecki, J.M
Bhandari, M
Ellingson, J.L
Pacher, B
Blocker, A.K
Canata, T.F
Kunnas, A
Gamble, A
Franzen, D
Kempenaar, C
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Authors
Suokannas, A
Backman, J
Visala, A
Kunnas, A
Yule , I
Eastwood, C
Pullanagari, R
Yule, I
Tuohy, M
Hedley, M
King, W
Dynes, R
Hedley, C
Yule, I
Draganova, I
Yule, I
Stevenson, M
Mayer, W
Pacher, B
Ellingson, J.L
Holub, B.K
Morgan, S.E
Werkmeister, B.K
Martello, L.S
Canata, T.F
Sousa, R.V
Prince Czarnecki, J.M
Reynolds, D.B
Moorhead, R.J
Maldaner, L
Molin, J.P
Canata, T.F
Canata, T.F
Molin, J.P
Colaço, A.F
Trevisan, R.G
Fiorio, P.R
Martello, M
Kempenaar, C
van Evert, F
Been, T
Kocks, C
Westerdijk, K
Nysten, S
Maja, J.M
Blocker, A.K
Stuckey, E.G
Sell, S.G
Tuttle, G
Mueller, J
Andrae, J
Kumar, S
Singh, M
Mirzakhaninafchi, H
Modi, R.U
Ali, M
Bhardwaj, M
Soni, R
Xu, X
Li, Z
Yang, G
Gu, X
Song, X
Yang, X
Feng, H
Kitchen, N.R
Yost, M.A
Ransom, C.J
Bean, G
Camberato, J
Carter, P
Ferguson, R
Fernandez, F
Franzen, D
Laboski, C
Nafziger, E
Sawyer, J
Prince Czarnecki, J.M
Wasson, L.L
Irby, J.T
Scholtes, A.B
Carver, S.M
Ortiz, B.V
Lena, B.P
Morlin , F
Morata, G
Duarte de Val, M
Prasad, R
Gamble, A
Palla, S
Bhandari, M
Zhoa, L
Ghansah, B
Khuimphukhieo, I
Scott, J.L
Bhandari, M
Foster, J
Da Silva, J
Li, H
Starek, M
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Fernandez, O
Bhandari, M
Landivar-Scoot, J.L
Eldefrawy, M
Zhao, L
Landivar, J
Topics
Engineering Technologies and Advances
Precision Dairy and Livestock Management
Proximal Sensing in Precision Agriculture
Information Management and Traceability
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Dairy and Livestock Management
Unmanned Aerial Systems
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Decision Support Systems in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Small Holders and Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Applications of Unmanned Aerial Systems
Drainage Optimization and Variable Rate Irrigation
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Genomics and Precision Agriculture
Artificial Intelligence (AI) in Agriculture
Data Analytics for Production Ag
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results22 paper(s) found.

1. Integrated Land Management – ICT Solutions & Business Models

  PROGIS and Adcon have developed a comprehensive solution to address the major challenges of our time: improve daily agricultural practice on all levels, increase and secure food supplies, take care of the environment and manage ever increasing risks, while last not least assist in fighting global warming.   In all of the above agriculture is playing a key role, but the methods of the past will no longer be adequate. Information technology is the name... W. Mayer, B. Pacher

2. Optimization of Forage Harvesting By Automatic Speed Control and Additive Application

Efficient use of machines is especially important in forage harvesting due to the short harvesting period and expensive machinery. To achieve the best efficiency, a harvesting machine, such as a loader wagon, should be used with optimal loading. Whereas overloading the machine can cause blockages in the cut-and-feed unit, underloading consumes more time and reduces the quality of the resulting silage. In addition, the quality can be improved by optimizing the dosage of the additive. Since the... A. Suokannas, J. Backman, A. Visala, A. Kunnas

3. Challenges and Opportunities for Precision Dairy Farming in New Zealand.

A study was commissioned by DairyNZ, a dairy industry good organisation in New Zealand, to identify some of the key challenges and opportunities in the precision dairy space. In New Zealand there has been an increasing research focus on the use of information and communication technologies (ICT) ... I. Yule , C. Eastwood

4. Proximal Sensing Tools to Estimate Pasture Quality Parameters.

To date systems for estimating pasture quality have relied on destructive sampling with measurement completed in a laboratory which was very time consuming and expensive. Results were often not received until after the pasture was grazed which defeated the point of the measurement, as farmers required the information to make decisions about grazing strategies to effectively... R. Pullanagari, I. Yule, M. Tuohy, M. Hedley, W. King, . Dynes

5. Farmer Uptake of Variable Rate Irrigation Technologies in New Zealand

Cost effective technological advances in recent years have allowed the uptake of variable rate irrigation (VRI) systems in New Zealand. Typically an existing sprinkler irrigator is modified for variable rate irrigation, irrigation management zones are defined using EM (electromagnetic)... C. Hedley, I. Yule

6. The Use of Sensing Technologies to Monitor and Track the Behavior of Cows on a Commercial Dairy Farm

New Zealand farmers are facing rapidly increasing pressure to reduce nutrient losses from their farming enterprises to the environment caused by grazing ruminants. Research... I. Draganova, I. Yule, M. Stevenson

7. Development Of An Enterprise Level Precision Agriculture System

Development of an Enterprise Level Precision Agriculture System   James Ellingson, Chih Lai University of St. Thomas, School of Engineering 2115 Summit Ave, St. Paul, MN USA elli4729@stthomas.edu;   Abstract – In this paper, a plan for the development of an Enterprise Level system for Precision Agriculture (PA) is described. The basic... J.L. Ellingson, B.K. Holub, S.E. Morgan, B.K. Werkmeister

8. Application Of Infrared Thermography For Assessing Beef Cattle Comfort Using A Fuzzy Logic Classifier

... L.S. Martello, T.F. Canata, R.V. Sousa

9. Use of Unmanned Aerial Vehicles to Inform Herbicide Drift Analysis

A primary advantage of unmanned aerial vehicle-based imaging systems is responsiveness.  Herbicide drift events require prompt attention from a flexible collection system, making unmanned aerial vehicles a good option for drift analysis.  In April 2015, a drift event was documented on a Mississippi farm.  A combination of corn and rice fields exhibited symptomology consist with non-target injury from a tank mix of glyphosate and clethodim.  An interesting observation was the... J.M. Prince czarnecki, D.B. Reynolds, R.J. Moorhead

10. Processing Yield Data from Two or More Combines

Erroneous data affect the quality of yield map. Data from combines working close to each other may differ widely if one of the monitors is not properly calibrated and this difference has to be adjusted before generating the map. The objective of this work was to develop a method to correct the yield data when running two or more combines in which at least one has the monitor not properly calibrated. The passes of each combine were initially identified and three methods to correct yield data were... L. Maldaner, J.P. Molin, T.F. Canata

11. Measuring Height of Sugarcane Plants Through LiDAR Technology

Sugarcane (Saccharum spp.) has an important economic role in Brazilian agriculture, especially in São Paulo State. Variation in the volume of plants can be an indicative of biomass which, for sugarcane, strongly relates to the yield. Laser sensors, like LiDAR (Light Detection and Ranging), has been employed to estimate yield for corn, wheat and monitoring forests. The main advantage of using this type of sensor is the capability of real-time data acquisition in a non-destructive way, previously... T.F. Canata, J.P. Molin, A.F. Colaço, R.G. Trevisan, P.R. Fiorio, M. Martello

12. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

13. Development of a Small Tracking Device for Cattle Using IoT Technology

The US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef.  This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the current... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae

14. Practical and Affordable Technologies for Precision Agriculture in Small Fields: Present Status and Scope in India

The objective of this review paper is to find out practical and affordable precision agriculture(PA) technologies present status and scope in India that are suitable for small fields. The judicious use of inputs like water, fertilizers, herbicides, pesticides and better management of farm equipments will increase the net profit for farmers. The important components of PA in India which are being used for small lands are Geographic Information System(GIS), laser land leveler, leaf color chart,... S. Kumar, M. Singh, H. Mirzakhaninafchi, R.U. Modi, M. Ali, M. Bhardwaj, R. Soni

15. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter Wheat

Nitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng

16. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer Response

Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer

17. Soybean Maturity Stage Estimation with Unmanned Aerial Systems

Many agronomic decisions in soybean production systems revolve around crop maturity. The primary objective of this research was to evaluate the ability of UAS to determine when soybeans have reached maturity stage sufficient for harvest aid application. A producer typically applies harvest aid chemicals when he or she perceives the crop has reached a critical level of maturity (R6.5) based on a subjective assessment. A convention is to apply harvest aids when 65% of soybean pods reach a mature... J.M. Prince czarnecki, L.L. Wasson, J.T. Irby, A.B. Scholtes, S.M. Carver

18. Can Topographic Indices Be Used for Irrigation Management Zone Delineation

Soil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble

19. Growth Analysis on Cotton Using Unoccupied Aerial Systems (UAS) Based Multi-temporal Canopy Features

The use of Unoccupied Aerial Systems (UAS) is rapidly evolving to generate imagery to determine crop growth patterns. A field experiment was conducted with thirty cotton varieties in 2016 and forty-two cotton varieties in 2021. The main objectives were (i) to perform growth analysis by using Canopy Cover (CC) and Canopy Height (CH) measurements obtained from UAS, (ii) to extract growth parameters from CC and CH data, (iii) to assess the relationship between the yield of cotton... S. Palla, M. Bhandari

20. High Throughput Phenotyping of the Energy Cane Crop UAV-based LiDAR, Multispectral and RGB Data

Energy cane is a hybrid of sugarcane cultivated for their high biomass and fiber instead of sugar. It is used for production of biofuels and as feedstock for animals. As a relatively new crop, accurate knowledge of biophysical parameters such as height and biomass of different genotypes are pertinent to cultivar development. Such knowledge is also crucial to manage crop health, understand response to environmental effects, optimize harvest schedules, and estimate bioenergy yield. Nonetheless,... B. Ghansah, I. Khuimphukhieo, J.L. Scott, M. Bhandari, J. Foster, J. Da silva, H. Li, M. Starek

21. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySat

Satellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari

22. 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