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Duff, H.D
López, J.D
Leithold, P
D.C, H
Landivar, J
Lee, K
Rascher, U
Ruckelshausen, A
Lundström, C
Li, Z
Xu, G
Dennis, S.J
Lee, J
Lee, B
Lum, C
Dima, C.S
Duarte, C
Leduc , M
Ransom, C.
Liu, Y
Laurent, P
DuPont, E.M
Dhillon, R
Reese, C.L
Lacasa, J
Ritchie, G
Remacre, A.Z
Lacroix, R
Dall'Agnol, R.W
Diaz-Zorita, M
Luchiari Junior, A
Liu, P
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Marine, L
Manon, M
Claire, G
Laurent, P
Mostafa, F
Zoran, C
Naima, B
Sébastien, D
Olivier, G
Chen, L
Zhang, R
Xu, G
Bortolon, L
Borghi, E
Luchiari Junior, A
Bortolon, E.S
Freitas, A.A
Inamasu, R.Y
Avanzi, J.C
Dhillon, R
Udompetaikul, V
Rojo, F
Upadhyaya, S
Slaughter, D
Lampinen, B
Shackel, K
Xu, G
Chen, L
Zhang, R
Guo, J
Wang, Y
L, M
Diaz-Zorita, M
Mercuri, P
Gonzalez-Mora, J
Vallespi Gonzalez, C
Ehsani, R
Dima, C.S
Duhachek, G
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Ruckelshausen, A
Dzinaj, T
Kinder, T
Bosse, D
Klose, R
Ruckelshausen, A
Alheit, K.V
Busemeyer, L
Klose, R
Linz, A
Moeller, K
Rahe, F
Thiel, M
Trautz, D
Weiss, U
Borghi, E
Luchiari Junior, A
Bortolon, L
Bortolon, E.S
Inamasu, R.Y
Bernardi, A.C
Avanzi, J.C
Rojo, F
Roach, J
Coates, R
Upadhyaya, S
Delwiche, M
Han, C
Dhillon, R
Dennis, S.J
Clarke-Hill, W
Taylor, A
Dynes, R
O'Neill, K
Jowett, T
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Li, Z
Wu, B
Meng, J
Leithold, P
Volk, T
Dammer, K
Dhillon, R
Upadhyaya, S
Roach, J
Crawford, K
Lampinen, B
Metcalf, S
Rojo, F
Hertzberg, J
Ruckelshausen, A
Wunder, E
Linz, A
Göttinger, M
Hinck, S
Möller, K
Ruckelshausen, A
Scholz, C
Crawford, K
Upadhyaya, S
Dhillon, R
Rojo, F
Roach, J
Tang, Q
Chen, L
Zhang, R
Xu, M
Xu, G
Yi, T
Lundström, C
Lindblom, J
Lum, C
Dunbabin, M
Shaw-Feather, C
Mackenzie, M
Luker, E
Muller, O
Cendrero Mateo, M.P
Albrecht, H
Pinto, F
Mueller-Linow, M
Pieruschka, R
Schurr, U
Rascher, U
Schickling, A
Keller, B
Dr., N
T, S
giriyappa, M
D.C, H
PATIL, B
Prabhudeva, D
Kombali, G
Noorasma, S
Thimmegowda, M
Lan, Y
Huang, Y
Martin, D.E
Hoffmann, W.C
Fritz, B.K
López, J.D
Sanches, G.M
Magalhães, P.S
Franco, H.C
Remacre, A.Z
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Betzek, N.M
Souza, E.G
Bazzi, C.L
Magalhães, P.G
Gavioli, A
Schenatto, K
Dall'Agnol, R.W
Lee, J
Fulton, J
Port, K
Colley III, R
Tsukor, V
Scholz, C
Nietfeld, W
Heinrich, T
Mosler , T
Lorenz, F
Najdenko, E
Möller, A
Mentrup, D
Ruckelshausen, A
Hinck, S
Muller, O
Keller, B
Zimmermanm, L
Jedmowski, C
Pingle, V
Acebron, K
Zendonadi, N
Steier, A
Pieruschka, R
Schurr, U
Rascher, U
Kraska, T
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
DuPont, E.M
Kolar, P.R
Maxwell, B.D
Hegedus, P.D
Loewen, S.D
Duff, H.D
Sheppard, J.W
Peerlinck, A.D
Morales, G.L
Bekkerman, A
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Saifuzzaman, M
Adamchuk, V
Leduc , M
Lee, K
Sudduth, K.A
Zhou, J
Karn, R
Adedeji, O
Ghimire, B.P
Abdalla, A
Sheng, V
Ritchie, G
Guo, W
Dhillon, R
Takoo, G
Sharma, V
Nagle, M
Zhen, X
Miao, Y
Feng, G
Huang, Y
Yang, Z
Liu, P
Bindish, R
Castiblanco Rubio, F.A
Arun, A
Lee, B
Balmos, A
Jha, S
Krogmeier, J
Love, D.J
Buckmaster, D
Ghimire, B
Karn, R
Adedeji, O
Ritchie, G
Guo, W
Hernandez, C
Correndo, A
Lacasa, J
Magalhaes Cisdeli, P
Nocera Santiago, G.N
Ciampitti, I
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
Sensor Application in Managing In-season Crop Variability
Engineering Technologies and Advances
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Precision Nutrient Management
Precision Horticulture
Remote Sensing Applications in Precision Agriculture
Education and Training in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Precision Crop Protection
Sensor Application in Managing In-season CropVariability
Precision Horticulture
Engineering Technologies and Advances
Precision Crop Protection
Decision Support Systems in Precision Agriculture
Unmanned Aerial Systems
Precision Agriculture and Climate Change
Precision Nutrient Management
Remote Sensing Application / Sensor Technology
Site-Specific Nutrient, Lime and Seed Management
Geospatial Data
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Robotics, Guidance and Automation
Decision Support Systems
ISPA Community: Nitrogen
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Agriculture and Global Food Security
Data Analytics for Production Ag
Weather and Models for Precision Agriculture
Wireless Sensor Networks and Farm Connectivity
Decision Support Systems
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results46 paper(s) found.

1. Study On Application Of Wireless Sensor Networks For Precision Agriculture

  Abstract: The use of sensor network to achieve soil moisture real-time detection can provide the decision-making basis for precision agriculture. In this... G. Xu, L. Chen, R. Zhang, J. Guo, Y. Wang

2. Variability In Wheat Crop Production Based On Management Zones In Humid Pampas Region, Argentina

Crop productivity within fields is heterogeneous and it responds to the variation in crop management patterns, and in previous, random, and natural crop management factors. The methodologies for the delimitation of management zones (MZ) within production fields differ based on their application objectives. The objectives... M. L, M. Diaz-zorita, P. Mercuri

3. HLB Detection Using Hyperspectral Radiometry

The need for sustainable agriculture requires the adoption of low input, long-term and cost-effective strategies to overcome the adverse impact of disease and nutritional deficiencies on citrus groves. In this context, early detection of diseased trees has become an important topic in the citrus industry. Multiple factors make field assessment of disease conditions a challenging task: the non-specific nature of many symptoms, the possibility of having localized affections in only certain areas... J. Gonzalez-mora, C. Vallespi gonzalez, R. Ehsani, C.S. Dima, G. Duhachek

4. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

5. Isobus Demonstrator And Working Environment For Agricultural Engineering Education

ISOBUS is the international standard for communication on agricultural equipment. In practice, however, a manufacturer independent tractor-implement communication is still a significant problem. This aspect has been identified as a major hindrance for the transfer of research results into products for precision farming.  As a consequence the ISOBUS standard should strongly be included in education and research, which is the focus of this work.   In... A. Ruckelshausen, T. Dzinaj, T. Kinder, D. Bosse, R. Klose

6. Sensor And System Technology For Individual Plant Crop Scouting

Sensor and system technologies are key components for automatic treatment of individual plants as well as for plant phenotyping in field trials. Based on experiences in research and application of sensors in agriculture the authors have developed phenotyping platforms for field applications including sensors, system and software development and application-specific mountings.   Sensor and data fusion have a high potential by compensating varying selectivities... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss

7. Using Multiplex® to Manage Nitrogen Variability in Champagne Vineyard

... L. Marine, M. Manon, G. Claire, P. Laurent, F. Mostafa, C. Zoran, B. Naima, D. Sébastien, G. Olivier

8. Probabilistic Relational Model-based Scheduling Approach for Farmland Soil Sensor Network

  Energy efficiency is one of the core issues of farmland soil sensor network (FSSN). For battery powered FSSN, the energy constraint restricts lifetime of WSN, which poses great challenged to its large scale application. Prior work has suggested approaches to optimize the RF module and communication protocols to reduce power consumption of FSSN. Although shown to be effective... L. Chen, R. Zhang, G. Xu

9. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, Brazil

Although precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi

10. Evaluation of the Sensor Suite for Detection of Plant Water Stress in Orchard and Vineyard Crops

A mobile sensor suite was developed and evaluated to predict plant water status by measuring the leaf temperature of nut trees and grapevines. It consists of an infrared thermometer to measure leaf temperature along with relevant ambient condition sensors to measure microclimatic variables in the vicinity of the leaf. Sensor suite was successfully evaluated in three crops (almonds, walnuts and grapevines) for both sunlit and shaded leaves. Stepwise linear regression models developed for shaded... R. Dhillon, V. Udompetaikul, F. Rojo, S. Upadhyaya, D. Slaughter, B. lampinen, K. Shackel

11. Adoption Level Of Precision Agriculture For Brazilian Farmers - 2011/12 Crop Year

Although Precision Agriculture (PA) concepts and technologies are widespread in Brazil, its application still little used in some important crop production regions. The purpose of this study was to survey the current adoption level of PA by printed and online questionnaire. We started making a specific questionnaire to farmers and PA service companies using some technology related to PA. The questionnaires were developed based on the methodology of Whipker and Akridge (2009),... E. Borghi, A. Luchiari junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi

12. Development And Evaluation Of A Leaf Monitoring System For Continuous Measurement Of Plant Water Status In Almond And Walnut Crops

Abstract: Leaf temperature measurements using handheld infrared thermometers have been used to predict plant water stress by calculating crop water stress index (CWSI). However, for CWSI calculations it is recommended to measure canopy temperature of trees under saturated, stressed and current conditions simultaneously, which is not very practical while using handheld units. An inexpensive, easy to use sensing system was developed to predict plant water status for tree crops by measuring... F. Rojo, J. Roach, R. Coates, S. Upadhyaya, M. Delwiche, C. Han, R. Dhillon

13. Estimating Spatial Variation In Annual Pasture Yield

Yield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers.   Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett

14. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

15. Design, Development And Application Of A Satellite-Based Field Monitoring System To Support Precision Farming

The factual base of precision agriculture (PA) - the spatial and temporal variability of soil and crop factors within or between different fields has been recognized for centuries. Field information on seeding suitability, soil & crop nutrition status and crop mature date is needed to optimize field management. How to acquire the spatially and temporally varied field parameters accurately, efficiently and at affordable cost has always been the focus of the researches in the field.... Z. Li, B. Wu, J. Meng

16. Fungiprecise - A German Project For Precise Real-Time Fungicide Application In Winter Wheat

Regarding to real-time or online technologies in recent years, new technologies has been introduced into practical farming especially in the field of nitrogen application. These technologies are based on sensors mainly detecting the canopy reflectance. In the field of plant protection, although few sensor-based real-time technologies in weed control and growth regulator application are marked available, solutions for fungicide application are mostly missing currently. Amongst others... P. Leithold, T. Volk, K. Dammer

17. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut Trees

A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo

18. Autonomous Service Robots For Orchards And Vineyards: 3D Simulation Environment Of Multi Sensor-Based Navigation And Applications

In order to fulfill economical as well as ecological boundary conditions information technologies and sensor are increasingly gaining importance in horticulture.  In combination with the reduced availability of human workers automation technologies thus play a key role in the international competition in vinicultures and orchards and have the potential to reduce the costs as well as environmental impacts.   The authors are working in the... J. Hertzberg, A. Ruckelshausen, E. Wunder, A. Linz

19. Automatic Soil Penetrometer Measurements And GIS-Based Documentation With The Autonomous Field Robot Platform BoniRob

For a sustainable agriculture, reliable measurements of soil properties and its interpretation are of highest relevance. Until today most of the measurements are carried out manually or by integrating off-line laboratories. Moreover, the number and density of measurement points is always an important aspect with respect to the statistical significance of the results. In this work a fully automatic measurement system has been developed and applied for the first time with free selectable... M. Göttinger, S. Hinck, K. Möller, A. Ruckelshausen, C. Scholz

20. An Inexpensive Aerial Platform For Precise Remote Sensing Of Almond And Walnut Canopy Temperature

Current irrigation practices depend largely on imprecise applications of water over fields with varying degrees of heterogeneity. In most cases, the amount of water applied over a given field is determined by the amount the most water-stressed part of the field needs. This equates to over-watering most of the field in order to satisfy the needs of one part of the field. This approach not only wastes resources, but can have a detrimental effect on the value of that crop. A system to... K. Crawford, S. Upadhyaya, R. Dhillon, F. Rojo, J. Roach

21. Airspeed and Pressure Affect Spray Droplet Spectrum from an Aerial Nozzle for Fixed-wing Applications

The atomization of the droplets generated by a flat fan nozzle has been studied in the IEA-I high speed wind tunnel at NERCIEA with Marvern Spraytec Laser Diffraction system. The measurement point is set at 0.15m, 0.25m and 0.35m away from the orifice of the nozzle. The wind speed range is from 150km/h to 305km/h, and the tube pressure is set about 0.3MPa, 0.4MPa and 0.5MPa. The measuring distance from the orifice of the nozzle is found important to the diameter and relative span of the droplets.... Q. Tang, L. Chen, R. Zhang, M. Xu, G. Xu, T. Yi

22. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision Agriculture

Agriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in technology... C. Lundström, J. Lindblom

23. Multispectral Imaging and Elevation Mapping from an Unmanned Aerial System for Precision Agriculture Applications

As the world population continues to grow, the need for efficient agricultural production becomes more pressing.  The majority of farmers still use manual techniques (e.g. visual inspection) to assess the status of their crops, which is tedious and subjective.  This paper examines an operational and analytical workflow to incorporate unmanned aerial systems (UAS) into the process of surveying and assessing crop health.  The proposed system has the potential to significantly reduce... C. Lum, M. Dunbabin, C. Shaw-feather, M. Mackenzie, E. Luker

24. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate Change

Phenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller

25. Precision Nutrient Management Through Drip Irrigation in Aerobic Rice

A field experiment was conducted during kharif 2015 to asses the spatial variability and precision nutrient management through drip irrigation in aerobic rice at ZARS, GKVK, Bangalore. The experimental field has been delineated into 48 grids of 4.5 m x 4.5 m using geospatial technology. Soil samples from 0-15 cm depth were collected and analysed. There was spatial variability for available nitrogen (154 to 277 kg ha-1), phosphorous (45 to 152 kg ha-1) and potassium... N. Dr., S. T, M. Giriyappa, H. D.c, B. Patil, D. Prabhudeva, G. Kombali, S. Noorasma, M. Thimmegowda

26. Development of an Airborne Remote Sensing System for Aerial Applicators

An airborne remote sensing system was developed and tested for recording aerial images of field crops, which were analyzed for variations of crop health or pest infestation. The multicomponent system consists of a multi-spectral camera system, a camera control system, and a radiometer for normalizing images. To overcome the difficulties currently associated with correlating imagery data with what is actually occurring on the ground (a process known as ground truthing); a hyperspectral reflectance... Y. Lan, Y. Huang, D.E. Martin, W.C. Hoffmann, B.K. Fritz, J.D. López

27. Potential of Apparent Soil Electrical Conductivity to Describe Soil Spatial Variability in Brazilian Sugarcane Fields

The soil apparent electrical conductivity (ECa) has been highlighted in the literature as a tool with high potential to map the soil fertility of fields. However, sugarcane fields still lack results that show the applicability of this information to define the soil spatial variability and its fertility conditions. The objective of the present paper was to provide a comprehensive assessment of the relationship between ECa, evaluated by electromagnetic induction (EMI) sensor, and the spatial variability... G.M. Sanches, P.S. Magalhães, H.C. Franco, A.Z. Remacre

28. Identifying and Filtering Out Outliers in Spatial Datasets

Outliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte

29. Application of Routines for Automation of Geostatistical Analysis Procedures and Interpolation of Data by Ordinary Kriging

Ordinary kriging (OK) is one of the most suitable interpolation methods for the construction of thematic maps used in precision agriculture. However, the use of OK is complex. Farmers/agronomists are generally not highly trained to use geostatistical methods to produce soil and plant attribute maps for precision agriculture and thus ensure that best management approaches are used. Therefore, the objective of this work was to develop and apply computational routines using procedures and geostatistical... N.M. Betzek, E.G. Souza, C.L. Bazzi, P.G. Magalhães, A. Gavioli, K. Schenatto, R.W. Dall'agnol

30. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of this... J. Lee, J. Fulton, K. Port, R. Colley iii

31. soil2data: Concept for a Mobile Field Laboratory for Nutrient Analysis

Knowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields... V. Tsukor, C. Scholz, W. Nietfeld, T. Heinrich, T. Mosler , F. Lorenz, E. Najdenko, A. Möller, D. Mentrup, A. Ruckelshausen, S. Hinck

32. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

33. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

34. Synchronized Windrow Intelligent Perception System (SWIPE)

The practice of bale production, in forage agriculture, involves various machines that include tractors, tedders, rakers, and balers. As part of the baling process, silage material is placed in windrows, linearly raked mounds, to drive over with a baler for easy collection into bales. Traditionally, a baler is an implement that is attached on the back of a tractor to generate bales of a specific shape. Forage agricultural equipment manufacturers have recently released an operator driven, self-propelled... E.M. Dupont, P.R. Kolar

35. Decision Support from On-field Precision Experiments

Empirically driven adaptive management in large-scale commodity crop production has become possible with spatially controlled application and sub-field scale crop monitoring technology. Site-specific experimentation is fundamental to an agroecosystem adaptive management (AAM) framework that results in information for growers to make informed decisions about their practices. Crop production and quality response data from combine harvester mounted sensors and internet available remote sensing data... B.D. Maxwell, P.D. Hegedus, S.D. Loewen, H.D. Duff, J.W. Sheppard, A.D. Peerlinck, G.L. Morales, A. Bekkerman

36. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US Midwest

Effective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan

37. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter Survival

Alfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc

38. Hay Yield Estimation Using UAV-based Imagery and a Convolutional Neural Network

Yield monitoring systems are widely used commercially in grain crops to map yields at a scale of a few meters. However, such high-resolution yield monitoring and mapping for hay and forage crops has not been commercialized. Most commercial hay yield monitoring systems only obtain the weight of individual bales, making it difficult to map and understand the spatial variability in hay yield. This study investigated the feasibility of an unmanned aerial vehicle (UAV)-based remote sensing system for... K. Lee, K.A. Sudduth, J. Zhou

39. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep Learning

Crop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo

40. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean Yield

Climate is one of the primary factors that affects agricultural production.  Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo

41. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang

42. OATSmobile: a Data Hub for Underground Sensor Communications and Rural IoT

Wireless Underground Sensor Networks (WUSNs) play a crucial role in precision agriculture by providing information about moisture levels, temperature, nutrient availability, and other relevant factors. However, the use of radio-frequency identification (RFID) devices for WUSNs has been relatively unexplored despite their benefits such as low power consumption. In this work, we develop a hardware platform, called OATSMobile, that enables radio-frequency identification (RFID) communications in WUSNs.... F.A. Castiblanco rubio, A. Arun, B. Lee, A. Balmos, S. Jha, J. Krogmeier, D.J. Love, D. Buckmaster

43. Simulating Climate Change Impacts on Cotton Yield in the Texas High Plains

Crop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo

44. From Scientific Literature to the End User: Democratizing Access to Data Products Through Interactive Applications

In recent years, the sustained advance in the creation of powerful programming libraries is allowing not only the creation of complex models with predictive capabilities but also revolutionizing visualization processes and the deployment of interactive applications. Some of these tools, such as Streamlit or Shiny frameworks in languages such as Python or R, allow us to create from simple applications with friendly interfaces to complex tools. These interactive digital decision dashboards allow... C. Hernandez, A. Correndo, J. Lacasa, P. Magalhaes cisdeli, G.N. Nocera santiago, I. Ciampitti

45. 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

46. 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