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Lundström, C
Eyster, R
Láng, V
Lee, J
Reeg, P
Rabello, L.M
Deng, W
Durand, P
Dalla Betta, M.M
Xiongkui, H
Laurent, P
Reznik, T
Erickson, B
Landivar, J
Luciano, A.C
Ellingson, J.L
Luchiari Junior, A
Rekhi, M
Rai, S
Love, D.J
Rattalino, J
Lum, C
Rosenberg, O
Donald, G.E
Robinette , M
Elvir Flores, A
Dandrifosse, S
Lu, P
Roberts, P
Delgadillo, C.A
Eigenberg, R.A
Reicks, G
Dua, S
Laursen, M.S
Lessl, J
Duff, H
Lambur, M
Lange, A
Daroub, S.H
Lewis, K
Dobbins, R
Ettema, J.F
Erazo, E
Devine, J
Ruiz Diaz, D
Rainbow, R
Endres, G
Rains, G
Lu, Y
Roach, J
Regen, C
Rontani, F
Li, B
Rojo, F
Rodrigues, F
Dima, C
English, P.J
De Waele, T
Rousseau, J
Emmi, L
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Authors
Zhao, C
Zhou, J
Deng, W
Marine, L
Manon, M
Claire, G
Laurent, P
Mostafa, F
Zoran, C
Naima, B
Sébastien, D
Olivier, G
de Oliveira, R.P
Bernardi, A.C
Benites, V.D
Rabello, L.M
Inamassu, R.Y
Midtiby, H.S
Jørgensen, R.N
Krüger, N
Laursen, M.S
Pantoja, J.L
Daroub, S.H
Diaz, O.A
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
Deng, W
Wu, G
Bedard, F
Reichert, G
Dobbins, R
Pantel, M
Smith, J
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Douche, H
Rousseau, J
Ortiz, B
Perry, C
Sullivan, D.G
Kemerait, R.C
Davis, R.F
Lu, P
Smith, A
Sankaran, S
Ehsani, R
Mishra, A
Dima, C
Donald, G.E
Trotter, M.G
Lamb, D.W
Levow, G
van Es, H.M
Lambur, M
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
Ellingson, J.L
Holub, B.K
Morgan, S.E
Werkmeister, B.K
Deng, W
Wang, X
Zhao, C
Huang, Y
De Kleine, M
Karkee, M
Zhang, Q
Lewis, K
Reeg, P
Kyveryga, P.M
Mueller, T.A
Dhillon, R
Upadhyaya, S
Roach, J
Crawford, K
Lampinen, B
Metcalf, S
Rojo, F
Quaderer, J
Coonen, J
Lange, A
Pauly, K
Souza, E
Schenatto, K
Rodrigues, F
Rocha, D
Bazzi, C.L
Zhao, C
Li, B
Crawford, K
Upadhyaya, S
Dhillon, R
Rojo, F
Roach, J
Rosenberg, O
Alchanatis, V
Saranga, Y
Bosak, A
Cohen, Y
Lundström, C
Lindblom, J
Kizer, E
Upadhyaya, S.K
Rojo, F
Ozmen, S
Ko-Madden, C
Zhang, Q
Zude-Sasse, M
Regen, C
Käthner, J
Pourreza, A
Lee, W
Lu, J
Roberts, P
Lum, C
Dunbabin, M
Shaw-Feather, C
Mackenzie, M
Luker, E
Charvat, K
Reznik, T
Charvat jr., K
Lukas, V
Horakova, S
Kepka, M
Charvat, K
Reznik, T
Lukas, V
Charvat Jr., K
Horakova, S
Splichal, M
Kepka, M
Archer, J.K
Delgadillo, C.A
Shen, F
Erickson, B
Clay, D.E
Clay, S.A
Fausti, S
Xiongkui, H
Longlong, L
Jianli, S
Aijun, Z
Yajia, L
Thomson, S.J
DeFauw, S.L
English, P.J
Hanks, J.E
Fisher, D.K
Foster, P.N
Zimba, P.V
Eigenberg, R.A
Woodbury, B.L
Nienaber, J.A
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Pradalier, C
Richard, A
Perez, V
Van Couwenberghe, R
Benbihi, A
Durand, P
Milics, G
Szabó, S
Bűdi, K
Takács, A
Láng, V
Zsebo, S
Trindall, J
Rainbow, R
Pfeiffer, J
Gandorfer, M
Ettema, J.F
Bazzi, C.L
Schenatto, K
Upadhyaya, S
Rojo, F
Cullop, J
Griffin, T.W
Ibendahl, G
Barnes, E
Shockley, J
Devine, J
Lee, J
Fulton, J
Port, K
Colley III, R
Erickson, B
Lowenberg-DeBoer, J
Bradford, J
Hatfield, G
Reicks, G
Carter, E
Yang, C
Suh, C
Guo, W
Zhao, H
Zhang, J
Eyster, R
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
Duff, H
Maxwell, B
Evers, B
Rekhi, M
Hettiarachchi, G
Welch, S
Fritz, A
Alderman, P.D
Poland, J
Elvir Flores, A
Miao, Y
Sharma, V
Lacerda, L
Canavari, M
Lattanzi, P
Vitali, G
Emmi, L
Tucker, M.W
Virk, S
Harris, G
Lessl, J
Levi, M
De Waele, T
Peralta, D
Shahid, A
De Poorter, E
Bazzi, C.L
Rauber, L.A
Oliveira, W.K
Sobjak, R
Schenatto, K
Gebler, L
Rabello, L.M
McFadden, J
Erickson, B
Lowenberg-DeBoer, J
Milics, G
Byers, C
Virk, S
Meena, R.K
Rains, G
Barbosa, M
Duron, D
Rontani, F
Bortolon, G
Moreira, B
Oliveira, L
Setiyono, T
Shiratsuchi, L
Silva, R.P
Holland, K.H
Dalla Betta, M.M
Puntel, L
Thompson, L
Mieno, T
Luck, J.D
Cafaro La Menza, N
Paccioretti, P
Erazo, E
Mosquera, C
Ochoa, O
Castiblanco Rubio, F.A
Arun, A
Lee, B
Balmos, A
Jha, S
Krogmeier, J
Love, D.J
Buckmaster, D
Nunes, L
Francisco, E
Prasad, R
Ortiz, B.V
Abban-Baidoo , E
Worosz, M
Robinette , M
O'Connor, C
Gamble, A
Roa Acosta, G
Ruiz Diaz, D
Dua, A
Sharda, A
Schapaugh, W
Hessel, R
Rai, S
Dua, S
Sharda, A
Rai, S
Sharda, A
Berretta, B.G
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Wang, Y
Lu, Y
Morris, D
Benjamin, M
Lavagnino, M
McIntyre, J
Xu, J
Lu, Y
Xu, J
Lu, Y
Fernandez, O
Bhandari, M
Landivar-Scoot, J.L
Eldefrawy, M
Zhao, L
Landivar, J
Topics
Precision Crop Protection
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Precision A-Z for Practitioners
Precision Conservation
Precision Horticulture
Precision Livestock Management
eXtension: Precision Agriculture on the Internet
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Crop Protection
Engineering Technologies and Advances
Sensor Application in Managing In-season CropVariability
Precision Conservation Management
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Decision Support Systems in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Horticulture
Sensor Application in Managing In-season Crop Variability
Unmanned Aerial Systems
Standards & Data Stewardship
Precision Agriculture and Climate Change
Agricultural Education
Engineering Technologies and Advances
Remote Sensing Application / Sensor Technology
Precision Agriculture and Global Food Security
Geospatial Data
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Precision Dairy and Livestock Management
Decision Support Systems
Robotics, Guidance and Automation
Education and Outreach in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Land Improvement and Conservation Practices
Geospatial Data
Drainage Optimization and Variable Rate Irrigation
Factors Driving Adoption
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Drone Spraying
Artificial Intelligence (AI) in Agriculture
On Farm Experimentation with Site-Specific Technologies
Wireless Sensor Networks and Farm Connectivity
Extension or Outreach Education of Precision Agriculture
Site-Specific Nutrient, Lime and Seed Management
Precision Crop Protection
Farm Animals Health and Welfare Monitoring
Robotics and Automation with Row and Horticultural Crops
International Symposium on Robotics and Automation
Data Analytics for Production Ag
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results74 paper(s) found.

1. Spectral Discrimination Of Early Dchinochloa Crasgalli And Echinochloa Crusgalli In Corn And Soybean By Using Support Vector Machines

    The key to realize precise chemical application is weed identification. This paper introduces a kind of multi-classification mode based on Support Vector Machines (SVM) and one-against-one-algorithm for weed seedlings (Dchinochloa crasgalli, and Echinochloa crusgalli) in corn and soybean fields. A handheld FieldSpec® 3 Spectroradiometer manufactured by ASD Inc., in USA was used to measure the spectroscopic data of the canopies of the seedlings of corn, soybean,... W. Deng, G. Wu

2. Timely, Objective, And Accurate Crop Area Estimations And Mapping Using Remote Sensing And Statistical Methods For The Province Of Prince Edward Island, Canada

The provincial government of Prince Edward Island, Canada, required timely, objective, and accurate annual crop area statistics and mapping for 2006 to 2008. Consequently, Statistics Canada conducted a survey incorporating medium- resolution satellite imagery (10 to 30 m) and statistical survey methods. The objective was to produce crop area estimates with a coefficient of variation (CV) as a measure of accuracy, and to produce maps showing the distribution and location of different crops and... F. Bedard, G. Reichert, R. Dobbins, M. Pantel, J. Smith

3. Revising Nitrogen Recommendations For Wheat In Response To The Need For Support Of Variable-rate Nitrogen Application

Sampling studies in North Dakota conducted from 1994 to 2003 showed that variable-rate N application could be practically directed with zone soil sampling. Results from variable-rate N studies using zone soil sampling were often less than rewarding due in part to the use of a whole-field predicted yield-based formula for developing the N recommendation in each zone. Nitrogen rate studies on spring wheat and durum were established in 2005 through 2009 to reexamine N recommendations. The results... D. Franzen, G. Endres, R. Ashley, J. Staricka, J. Lukach, K. Mckay

4. Oenoview : Bringing Remote Sensing To Wine Quality

  Oenoview is born in 2006 from the partnership between Infoterra, an EADS Astrium company specialised in earth observation and the Institut Cooperatif de Vin, a French company of services for the wine industry. Oenoview is an operating precision viticulture service, dedicated to vine monitoring, harvest optimisation and input management. In France, this service implemented in 2009 on a commercial scale is now used by clients as different as large... H. Douche, J. Rousseau

5. Variable Rate Application Of Nematicides On Cotton Fields: A Promising Site-specific Management Strategy

  The impact of two nematicides [ 1,3 – Dichloropropene (Telone® II) and Aldicarb (Temik)] applied at two rates on RKN population density and cotton (Gossypium hirsutum L.) lint yield were compared across previously determined RKN management zones (MZ) in commercial fields between 2007 and 2009. The MZ were delineated using fuzzy clustering of various surrogate data for soil texture. All treatments were randomly allocated among... B. Ortiz, C. Perry, D.G. Sullivan, R.C. Kemerait, R.F. Davis, P. Lu, A. Smith

6. Development Of Ground-based Sensor System For Automated Agricultural Vehicle To Detect Diseases In Citrus Plantations

An integrated USDA-funded project involving Carnegie Mellon University, University of Florida, Cornell University and John Deere is ongoing, to develop an autonomous tractors for sustainable specialty crop farming. The research teams have come together to develop an automated system for detecting plant stress, estimating yields, and reducing chemical usage through precision spraying for specialty crops. The goals of the automation process are to reduce the tractor-related labor costs, reduce... S. Sankaran, R. Ehsani, A. Mishra, C. Dima

7. Precision Livestock Management: An Example Of Pasture Monitoring In Eastern Australian Pastures Using Proximal And Remote Sensing Tools

  Pasture monitoring Australian rangelands by Remote Sensing   G.E.Donald.  CSIRO Livestock Industries, Locked Bag 1, Armidale NSW, 2350 Australia     A series of spatial models and datasets were jointly developed to estimate pasture biomass as feed on offer (FOO®) and pasture growth rate (PGR®) in the south-west... G.E. Donald, M.G. Trotter, D.W. Lamb, G. Levow, H.M. Van es

8. The Scholarship Of eXtension

  eXtension (www.extension.org) is an interactive on-line learning environment delivering "best of the best," researched-based knowledge from the top minds across the land-grant university system.  It is a space where university content providers can collaborate to gather and produce new educational and information resources on wide-ranging topics while continually interacting with their customers to help solve real-life problems in real time.  The works of faculty... M. Lambur

9. Comparison and Evaluation of Spray Characteristics of Three Types of Variable-Rate Spray

For the present developing direction of "low-input sustainable agriculture", variable-rate technology is increasingly concerned in agricultural engineering field. The technology of variable-rate precision chemical application is the typical of variable-rate technology. In China, agro-chemical production technology has reached the international advanced level, but the chemical application... C. Zhao, J. Zhou, W. Deng

10. 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

11. Spatial Variability Index Based On Soil Properties for Notill and Pasture Site-Specific Management in Brazil.

 Quantitative characterization of soil properties spatial variation has first been applied... R.P. De oliveira, A.C. Bernardi, V.D. Benites, L.M. Rabello, R.Y. Inamassu

12. Validation of Modicovi - Monocot and Dicot Coverage Ratio Vision Based Method for Real Time Estimation Canopy Coverage Ratio between Cereal Crops and Dicotyledon Weeds

... H.S. Midtiby, R.N. Jørgensen, N. Krüger, M.S. Laursen

13. Soil Spatial Variability in the Everglades Agricultural Area in South Florida

The Everglades agricultural area is composed by histosols laying on hard limestone bedrock in south Florida. Despite the common assumption of homogeneity of these soils, agricultural practices could result in the increase of soil variability. Therefore, soil spatial variability was studied on three fields (5.5 ha each) at the Everglades Research and Education Center to compare the changes... J.L. Pantoja, S.H. Daroub, O.A. Diaz

14. 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

15. 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

16. 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

17. 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

18. 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

19. Weed Identification From Seedling Cabbages Using Visible And Near-Infrared Spectrum Analysis

Target identification is one of the main research content and also a key point in precision crop protection. The main purpose of the study is to choose the characteristic wavelengths (CW for short) to classify the cabbages and the weeds at their seedling stage using different data analysis methods. Using a handheld full-spectrum FieldSpec-FR, the canopies of the seedling plants, cabbage ‘8398, cabbage ‘zhonggan’, Barnyard grass, green foxtail, goosegrass,... W. Deng, X. Wang, C. Zhao, Y. Huang

20. A Dual Motor Actuator Used To Detach Fruit By Shaking Limbs Of Fruit Trees

Mechanizing the fruit removal operation during fresh-market apple harvesting will result in considerable cost savings for fruit growers. This study introduces a mechanical fruit removal technique that uses a unique limb shaking mechanism called a Dual Motor Actuator (DMA). The DMA was developed as an infinitely variable end-effector that applies rhythmic motions to a fruiting limb to remove fruit. The novelty of the DMA design is the use of two eccentrics mounted to electric motors... M. De kleine, M. Karkee, Q. Zhang, K. Lewis

21. Evaluating Decision Systems For Using Variable Rates In Planting Soybean

Increased interest in managing seeding rates within soybean fields is being driven by the advances in technologies and the need to increase productivity and economic returns. A wealth of previous research was focused on studying how different seeding rates affect soybean yields at small-plot scales. However, little is known how different site-specific factors influence the responsiveness of soybean to higher or lower plant population densities at field levels, especially across geographic... P. Reeg, P.M. Kyveryga, T.A. Mueller

22. 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

23. Applying Conventional Vegetation Vigor Indices To UAS-Derived Orthomosaics: Issues And Considerations

In recent years, unmanned airborne systems (UAS) have gained a lot of interest for their potential use in precision agriculture. While the imagery from near-infrared (NIR) enabled off-the-shelf cameras included in UAS can be directly used to facilitate crop scouting, the application in quantitative analyses remains cumbersome. The ultimate goal is to calculate (nitrogen) prescription maps from vegetation indices obtained from UAS imagery, but two main issues hamper this workflow: (1) the... J. Quaderer, J. Coonen, A. Lange, K. Pauly

24. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means Methods

The generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi

25. Heavy Metal PB2+ Pollution Detection In Soil Using Terahertz Time-domain Spectroscopy For Precision Agriculture

Soil is an important natural resource for human beings. With the rapid development of modern industry, heavy metals pollution in soil has made prominent influences on farmland environment. It was reported that, one fifth of China's cultivated lands and more than 217,000 farms in the US have been polluted at different levels by heavy metals. The crop grows in the polluted soil and the heavy metal ions transfer from soil to the plant and agro-products. As a result, the crop yield... C. Zhao, B. Li

26. 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

27. Are Thermal Images Adequate For Irrigation Management?

Thermal crop sensing technologies have potential as tools for monitoring and mapping crop water status, improving water use efficiency and precisely managing irrigation. As thermal sensors and imagers became more affordable, various platforms were examined to allow for canopy- and field-scale acquisitions of canopy temperature and to extract maps of water status variability. Various canopy temperature statistics and crop water stress index (CWSI) were used to estimate water status... O. Rosenberg, V. Alchanatis, Y. Saranga, A. Bosak, Y. Cohen

28. 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

29. Proximal Sensing of Leaf Temperature and Microclimatic Variables to Implement Precision Irrigation in Almond and Grape Crops

Irrigation decisions based on traditional soil moisture sensing often leads to uncertainty regarding the true amount of water available to the plant. Plant based sensing of water stress decreases this uncertainty. In specialty crops grown in California’s Central Valley, precision deficit irrigation based on plant water stress could be used to decrease water use and increase water use efficiency by supplying the necessary quantity of water only when it is needed by the plant. However, there... E. Kizer, S.K. Upadhyaya, F. Rojo, S. Ozmen, C. Ko-madden, Q. Zhang

30. Robustness of Pigment Analysis in Tree Fruit

The non-destructive application of spectrophotometry for analyzing fruit pigments has become a promising tool in precise fruit production. Particularly, the pigment contents are interesting to the growers as they provide information on the harvest maturity and fruit quality for marketing. The absorption of chlorophyll at its Q band provides quantitative information on the chlorophyll pool of fruit. As a challenge appears the in-situ measurement at varying developmental stage of the fruit due to... M. Zude-sasse, C. Regen, J. Käthner

31. Development of a Multiband Sensor for Citrus Black Spot Disease Detection

Citrus black spot (CBS), or Guignardia citricarpa, is known as the most destroying citrus fungal disease worldwide. CBS causes yield loss as a result of early fruit drop, and it leaves severely blemished and unmarketable fruit. While leaves usually remain symptomless, CBS generates various forms of lesions on citrus fruits including hard spot, cracked spot, and virulent spot. CBS lesions often appear on maturing fruit, starting two months before maturity. Warm temperature and sunlight exposure... A. Pourreza, W. Lee, J. Lu, P. Roberts

32. 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

33. FOODIE Data Model for Precision Agriculture

The agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and temporal... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka

34. Quo Vadis Precision Farming

The agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

35. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture Industry

Precision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena.  Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen

36. Knowledge, Skills and Abilities Needed in the Precision Ag Workforce: an Industry Survey

Precision agriculture encompasses a set of related technologies aimed at better utilization of crop inputs, increasing yield and quality, reducing risks, and enabling information flow throughout the crop supply and end-use chains.  The most widely adopted precision practices have been automated systems related to equipment steering and precise input application, such as autoguidance and section controllers.  Once installed, these systems are relatively easy for farmers and their supporting... B. Erickson, D.E. Clay, S.A. Clay, S. Fausti

37. Design of VAV System of Air Assisted Sprayer in Orchard and Experimental Study in China

One type of new automatic target detecting based on size of canopy with variable chemical dosage and air-flow of fan orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards. Canopy parameter data scanned by infrared sensors and LIDAR (Light Detection and Ranging) were used to detect the target and to design spraying algorithm and PWM (Pulse Width Modulation) control system. Four integrated five-finger atomizers were equipped on each side of sprayer, independent... H. Xiongkui, L. Longlong, S. Jianli, Z. Aijun, L. Yajia

38. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)

Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba

39. Precision Management of Cattle Feedlot Waste

Open-lot cattle feeding operations face challenges in control of nutrient runoff, leaching, and gaseous emissions. This report investigates the use of precision management of saline soils as found on 1) feedlot surfaces and on a 2) vegetative treatment area (VTA) utilized to control feedlot runoff. An electromagnetic induction soil conductivity meter was used to collect apparent soil electrical conductivity (ECa) from a feedlot pen and a research VTA at the U.S. Meat Animal Research Center, Clay...

40. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision Agriculture

The agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi

41. Automated Segmentation and Classification of Land Use from Overhead Imagery

Reliable land cover or habitat maps are an important component of any long-term landscape planning initiatives relying on current and past land use. Particularly in regions where sustainable management of natural resources is a goal, high spatial resolution habitat maps over large areas will give guidance in land-use management. We propose a computational approach to identify habitats based on the automated analysis of overhead imagery. Ultimately, this approach could be used to assist experts,... C. Pradalier, A. Richard, V. Perez, R. Van couwenberghe, A. Benbihi, P. Durand

42. Increasing Corn (Zea Mays L.) Profitability by Site-Specific Seed and Nutrient Management in Igmand-Kisber Basin, Hungary

Variable Rate Technology (VRT) in seeding and nutrient management has been developed in order to apply crop inputs variably. Farm equipment is widely available to manage in-field variability in Hungary, however, defining management zones, seed rates and amounts of nutrients is still a challenge. An increasing number of growers in Hungary have started adopting precision agriculture technology; however, data on profitability concerning site-specific seeding and nitrogen management is not widely... G. Milics, S. Szabó, K. Bűdi, A. Takács, V. Láng, S. Zsebo

43. Accelerating Precision Agriculture to Decision Agriculture: Enabling Digital Agriculture in Australia

For more than two decades, the success of Australia’s agricultural and rural sectors has been supported by the work of the Rural Research and Development Corporations (RDCs). The RDCs are funded by industry and government. For the first time, all fifteen of Australia’s RDC’s have joined forces with the Australian government to design a solution for the use of big data in Australian agriculture. This is the first known example of a nationwide approach for the digital transformation... J. Trindall, R. Rainbow

44. Economic Evaluation of Automatic Heat Detection Systems in Dairy Farming

Although heat detection makes a relevant contribution to good reproduction performance of dairy cattle, available studies on the economic evaluations of automatic heat detection systems are limited. Therefore, the objective of this article is to provide an economic evaluation of using automatic heat detection. The effect of different heat detection rates on gross margin is modelled with SimHerd (SimHerd A/S, Denmark). The analysis considers all additional investment costs in automatic heat detection.... J. Pfeiffer, M. Gandorfer, J.F. Ettema

45. Optimal Placement of Proximal Sensors for Precision Irrigation in Tree Crops

In agriculture, use of sensors and controllers to apply only the quantity of water required, where and when it is needed (i.e., precision irrigation), is growing in importance. The goal of this study was to generate relatively homogeneous management zones and determine optimal placement of just a few sensors within each management zone so that reliable estimation of plant water status could be obtained to implement precision irrigation in a 2.0 ha almond orchard located in California, USA. First... C.L. Bazzi, K. Schenatto, S. Upadhyaya, F. Rojo

46. Economics of Swarm Bot Profitability for Cotton Harvest

Improved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine

47. 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

48. Tracking Two Decades of Precision Agriculture Through the Croplife Purdue Survey

The CropLife/Purdue University precision dealer survey is the longest-running continuous survey of precision farming adoption.  The 2017 survey is the 18th, conducted every year from 1997 to 2009, and then every other year following.  For individuals working in agriculture there is great value in knowing who is doing what and why, to get a better understanding of the utilities and applications, and to guide investments.  A major revision in survey questions was made... B. Erickson, J. Lowenberg-deboer, J. Bradford

49. Can Unreplicated Strip Trials Be Used in Precision On-Farm Experiments?

On-farm experiments are used to evaluate a wide variety of products ranging from pesticide and fertilizer rates to the installation of tile drainage. The experimental design for these experiments is usually replicated strip trials.  Replication of strip trials is used to estimate experimental error, which is the basis for judging statistical significance of treatment effects. Another consideration for using strip trials is greater within-field variability than smaller fields used... G. Hatfield, G. Reicks, E. Carter

50. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS Imagery

Aerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimation... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster

51. Sun Effect on the Estimation of Wheat Ear Density by Deep Learning

Ear density is one of the yield components of wheat and therefore a variable of high agronomic interest. Its traditional measurement necessitates laborious human observations in the field or destructive sampling. In the recent years, deep learning based on RGB images has been identified as a low-cost, robust and high-throughput alternative to measure this variable. However, most of the studies were limited to the computer challenge of counting the ears in the images, without aiming to convert... S. Dandrifosse, E. Ennadifi, A. Carlier, B. Gosselin, B. Dumont, B. Mercatoris

52. Ecological Refugia As a Precision Conservation Practice in Agricultural Systems

Current global agriculture fails to meet the basic food needs of 687.7 million people. At the same time, our food system is responsible for catastrophic losses of biodiversity. Precision conservation solutions offer the potential to benefit both production systems and natural systems. Transforming low-producing areas on farm fields into ecological refugia may provide small-scale habitat and ecosystem services in fragmented agricultural landscapes. We collaborated with three precision agriculture... H. Duff, B. Maxwell

53. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding Program

In plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland

54. Evaluating the Potential of Integrated Precision Irrigation and Nitrogen Management for Corn in Minnesota

The environmental impact of irrigated agriculture on ground and surface water resources in Minnesota is of major concern. Previous studies have focused on either precision irrigation or precision nitrogen (N) management, with very limited studies on the integrated precision management of irrigation and N fertilizers, especially in Minnesota. The Dualex Scientific sensor is a leaf fluorescence sensor that has been used to diagnose crop N... A. Elvir flores, Y. Miao, V. Sharma, L. Lacerda

55. Robot Safety Issues in Field Crops - EU Regulatory Issues and Technical Aspects

The use of robots in Precision Agriculture is becoming of great interest, but they introduce a new kind of risk in the field due to their self-acting and self-driving capability. Safety issues appear with respect to people working in the same field in human-robot collaboration (HRC) framework or to the accidental presence of humans or animals. A robot out of control may also invade other areas causing unpredictable harm and damage. Currently, the safety of highly automated agricultural... M. Canavari, P. Lattanzi, G. Vitali, L. Emmi

56. Effectiveness of Different Precision Soil Sampling Strategies for Site-Specific Nutrient Management in Row-Crops

Soil sampling is an important component of site-specific nutrient management in precision agriculture. While precision soil sampling strategies such as grid or zone have been around for a while, the adoption and utilization of these strategies varies considerably among the growers, especially in the southeastern United States. The selection of an appropriate grid size or management zone further differ among the users depending on several factors. In order to better understand how some of the commonly... M.W. Tucker, S. Virk, G. Harris, J. Lessl, M. Levi

57. Supervised Feature Selection and Clustering for Equine Activity Recognition

In this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter

58. Portable Soil EC - Development of an Electronic Device for Determining Soil Electrical Conductivity

Decision-making in agriculture demands continuous monitoring, a factor that propels the advancement of tools within Agriculture 4.0. In this context, understanding soil characteristics is essential. Electrical conductivity (EC) sensors play a pivotal role in this comprehension. Given this backdrop, the core motivation of this research was developing an accessible and effective electronic device to measure the apparent EC of the soil. It provides features like geolocation, recording of the date... C.L. Bazzi, L.A. Rauber, W.K. Oliveira, R. Sobjak, K. Schenatto, L. Gebler, L.M. Rabello

59. Global Adoption of Precision Agriculture: an Update on Trends and Emerging Technologies

The adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial intelligence... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics

60. Spray Deposition Characterization of Uniform and Variable-rate Applications with Spray Drones

The use of unmanned aerial application systems (also known as spray drones) has seen rapidly increasing interest in recent years due to their potential to allow for timely application of pesticides and being able to apply in areas inaccessible to ground application sprayers. Newer spray drone models’ have improved application systems such as rotary atomizers for creating spray droplets and capabilities such as variable-rate (VR) application for site-specific pesticide applications. An investigation... C. Byers, S. Virk, R.K. Meena, G. Rains

61. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland

62. Determining Site-Specific Soybean Optimal Seeding Rate Using On-Farm Precision Experimentation

Ten on-farm precision experiments were conducted in Nebraska during 2018 – 2022 to address the following: i) determine the Economic Optimal Seeding Rates (EOSR), ii) identify the most important site-specific variables influencing the optimal seeding rates for soybeans. Seeding rates ranged from 200,000 to 440,000 seeds ha-1, and treatments were randomized and replicated in blocks across the entire field. The study was implemented using a variable rate prescription. Yield... M.M. Dalla betta, L. Puntel, L. Thompson, T. Mieno, J.D. Luck, N. Cafaro la menza, P. Paccioretti

63. RMAPs: an Integrated Tool to Delimitate Homogeneous Management Zones

Management zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa

64. 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

65. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation Strategies

Farmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble

66. Enhancing Phosphorus Nutrient Management in Corn Through Tissue Analysis and Diagnostic Tools

Phosphorus (P) plays a pivotal role in crop growth, and optimizing its application is crucial for sustainable agriculture. This research focuses on advancing nutrient management by precisely evaluating tissue phosphorus concentrations in corn. The study delves into identifying critical P levels during various growth stages, assessing alternative diagnostic tools, and exploring correlations to refine phosphorus nutrition strategies. Across 26 locations in Kansas, field experiments employed a randomized... G. Roa acosta, D. Ruiz diaz

67. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding Plots

Advances in precision agriculture in data collection, crop monitoring, screening, and management over the 10-15 years are revolutionizing on-farm agricultural research trials. In crop breeding plots, this approach is called "High Throughput Phenotyping", which uses innovative technology to extract phenotypic data for large populations. Remote sensing has become one of the commonly used platforms for rapid acquisition of imagery data at spatial and temporal scale. Particularly, the unmanned... A. Dua, A. Sharda, W. Schapaugh, R. Hessel, S. Rai

68. Machine Learning Model to Predict Total Nozzle Volume Delivery for Pulse Width Modulated Flow Controllers

Product flow rate in the Pulse Width Modulation (PWM) variable rate technologies depends on the duty cycle. However, the actual product flow rate at any duty cycle depends on pressure rise, stable pressure during the cycle, fall time and pressure drop across the nozzle body. The current controller does not consider the pressure drops and the estimation of actual flow during each cycle at any duty cycle cannot be estimated with capturing high-frequency pressure data. Knowledge of volume delivery... S. Dua, A. Sharda

69. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision Agriculture

In precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision technology.  We... F. Sidharth, A. Sharda, B.G. Berretta

70. 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

71. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows

The lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D computer... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre

72. Automated Detection and Length Estimation of Green Asparagus Towards Selective Harvesting

Green asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yield... J. Xu, Y. Lu

73. Development of a Multispectral Vision-based Automated Sweetpotato Grading System

Quality evaluation and grading of sweetpotatoes is a manual operation that requires significant labor input. Machine vision technology offers a promising solution for automated sweetpotato grading and sorting. Although color imaging is widely used for quality evaluation of various horticultural commodities, a multispectral vision technique that acquires color and near-infrared (NIR) images simultaneously is a potentially more effective modality for fruit grading, especially for defects, while... J. Xu, Y. Lu

74. 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