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Seielstad, G
Pitla, S.K
Cheng, S
Larsen, D
Lai, C
P.W Clevers, J.G
Channangi, S.M
Magyar, F
Cordero, E
Schroeder, M.A
Mansor, S
Stefanini, M
Vargas, F
Ortiz, B
Mahns, B
Souza, E.G
Maja, J.M
Postelmans, A
TORGBOR, B.A
Sui, R
Coates, A
Marra, M.C
Morris, E
Egea, G
Udompetaikul, V
Carroll, S
Tauqir, N.A
Lu, J
Shechter, M
Carter, P.G
Sanches, G.M
Owen, J
Peña-Barragán, J.M
Munkhbayar, S
Licht, M.A
Mitsuoka, M
Ostermann, M
Scheithauer, H
Ortega, A.F
Tronco, M.L
Steffan, S
Chung, S
Perron, I
Taubinger, L
Orensanz, J
Laacouri, A
Pokhrel, A
Chantuma, D
Cendrero Mateo, M.P
Cavalcante, D.S
Varco, J.J
Sheshadri, T
Lambert, D.M
Macy, T
Mendez, L
Shanahan, J
Cardoso, T.F
Magalhães, P.S
Tabatabai, S
Michelon, G.K
Seyhan, G.T
Moulton, P
Saraiva, A.M
Camberato, J
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Authors
Lambert, D.M
Larson, J.A
English, B.C
Rejesus, R.M
Marra, M.C
Mishra, A.K
Wang, C
Watcharaanantapong, P
Roberts, R.K
Velandia, M
Liaghat, S
Mansor, S
Shafri, H
Meon, S
Ehsani, R
Azam, S
Noh, N
Ehsani, R
Sankaran, S
Maja, J.M
Neto, J.C
Nisa, M.U
Babar, I
Sarwar, M
Tauqir, N.A
Shahzad, M.A
Amaral, L.R
Molin, J.P
Taubinger, L
Thompson, N.M
Larson, J.A
English, B.C
Lambert, D.M
Roberts, R.K
Velandia, M
Wang, C
Saraiva, A.M
Santos, R.T
Molin, J.P
Dhillon, R
Udompetaikul, V
Rojo, F
Upadhyaya, S
Slaughter, D
Lampinen, B
Shackel, K
Ortiz, B
Ortiz, B
Thomson, S.J
Huang, Y
Reddy, K
Balkcom, K
Ortiz, B
Shockley, J
Fulton, J.P
Ortiz, B
Perry, C
Sullivan, D.G
Kemerait, R.C
Davis, R.F
Lu, P
Smith, A
Pan, L
Adamchuk, V.I
Martin, D.L
Schroeder, M.A
Fergugson, R.B
Norwood, S.H
Fulton, J.P
Winstead, A.T
Shaw, J.N
Rodekohr, D
Brodbeck, C.J
Macy, T
Chantuma, D
Zaller, M
Lan, Y
Zhang, H
Yang, C
Martin, D
Lacey, R
Huang, Y
Hoffmann, W.C
Moulton, P
Udompetaikul, V
Upadhyaya, S
Lampinen, B
Slaughter, D
Pierce, F
Perry, E.M
Young, S.L
Collins, H.P
Carter, P.G
Velandia, M
Mooney, D.F
Roberts, R.K
English, B.C
Larson, J.A
Lambert, D.M
Larkin, S.L
Marra, M.C
Rejesus, R
Martin, S.W
Paxton, K.W
Mishra, A
Wang, C
Segarra, E
Reeves, J.M
Harper, D.C
Lambert, D.M
English, B.C
Larson, J.A
Roberts, R.K
Velandia, M
Mooney, D.F
Larkin, S.L
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Luck, J.D
Sharda, A
Pitla, S.K
Fulton, J.P
Shearer, S.A
Morris, E
Clarke, A
Sunley, S
Hill, C
Cranfield, G
She, Y
Ehsani, R
Robbins, J
Owen, J
Leiva, J.N
Lai, C
Belsky, C
Rossant, F
Bloch, I
Orensanz, J
Boisgontier, D
Verma, U
Lagarrigue, M
Rossant, F
Orensanz, J
Boisgontier, D
Bouhlel, N
Lagarrigue, M
Veiga, J.P
Cavalcante, D.S
Molin, J.P
Cao, Q
Miao, Y
Shen, J
Cheng, S
Khosla, R
Liu, F
Sanches, G.M
Graziano Magalhães, P.S
Franco, H.C
Remacre, A.Z
Graziano Magalhães, P.S
Sanches, G.M
Kolln, O.T
Franco, H.C
Braunbeck, O.A
Driemeier, C
Kolln, O.T
Sanches, G.M
Rossi Neto, J
Castro, S.G
Mariano, E
Otto, R
Inamasu, R
Magalhães, P.S
Braunbeck, O.A
Franco, H.C
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Seyhan, G.T
Yegul, U
Ayık, M
Licht, M.A
Lenssen, A
Elmore, R
Mulla, D
Laacouri, A
Kaiser, D
Hirai, Y
Yamakawa, T
Inoue, E
Okayasu, T
Mitsuoka, M
Muller, O
Cendrero Mateo, M.P
Albrecht, H
Pinto, F
Mueller-Linow, M
Pieruschka, R
Schurr, U
Rascher, U
Schickling, A
Keller, B
Cho, W
Kim, D
Kang, C
Kim, H
Son, J
Chung, S
Jiang, J
Yun, H
Lu, J
Miao, Y
Huang, Y
Shi, W
Larson, J.A
Stefanini, M
Lambert, D.M
Yin, X
Boyer, C.N
Varco, J.J
Scharf , P.C
Tubaña, B.S
Dunn, D
Savoy, H.J
Buschermohle, M.J
Tyler, D.D
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Castro, S.G
Sanches, G.M
Cardoso, G.M
Silva, A.E
Franco, H.C
Magalhães, P.S
Garcia-Torres, L
Peña-Barragán, J.M
Gómez-Candón, D
López-Granados, F
Jurado-Expósito, M
Ram, E
Shechter, M
Sela, E
P.W Clevers, J.G
Wijnholds, K.H
Jukema, J.N
Zhang, X
Helgason, C
Seielstad, G
Shi, L
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Sui, R
Baggard, J
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Reddy, S
Biradar, D.P
Patil, V.C
Desai, B.L
Nargund, V.B
Patil, P
Desai, V
Tulasigeri, V
Channangi, S.M
John, W
Tumenjargal, E
Batbayar, E
Munkhbayar, S
Tsogt-Ochir, S
Oyumaa, M
Chung, K
Ham, W
Laacouri, A
Nigon, T
Mulla, D
Yang, C
Kantipudi, K
Lai, C
Min, C
Chiang, R.C
Schenatto, K
Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Magalhães, P.S
Bazzi, C.L
Jasse, E.P
Souza, E.G
Magalhães, P.S
Michelon, G.K
Schenatto, K
Gavioli, A
Michelon, G.K
Sanches, G.M
Valente, I.Q
Bazzi, C.L
de Menezes, P.L
Amaral, L.R
Magalhaes, P.G
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
Adams, C
Coates, A
Wilson, G.L
Mulla, D.J
Galzki, J
Laacouri, A
Vetsch, J
Larsen, D
Skovsen, S
Steen, K.A
Grooters, K
Green, O
Jørgensen, R.N
Eriksen, J
Lai, C
Min, C
Chiang, R
Hafferman, A
Morgan, S
Agili, H
Chokmani, K
Cambouris, A
Perron, I
Poulin, J
Cambouris, A
Perron, I
Zebarth, B
Vargas, F
Chokmani, K
Biswas, A
Adamchuk, V
Lu, J
Wang, H
Miao, Y
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Luck, B
Drewry, J
Chassen, E
Steffan, S
Marmette, M
Adamchuk, V
Nault, J
Tabatabai, S
Cocciardi, R
Lugli, L.C
Tronco, M.L
Porto, A.J
G, S
Biradar, D.P
Desai, B.L
Patil, V.C
Patil, P
Nargund, V.B
Desai, V
John, W
Channangi, S.M
Tulasigeri, V
Tsibart, A
Postelmans, A
Dillen, J
Elsen, A
Van de Ven, G
Saeys, W
Milics, G
Varga, P.M
Magyar, F
Balla, I
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Oliveira, M.F
Morata, G.T
Ortiz, B
Silva, R.P
Jimenez, A
Ortega, R.A
Ortega, A.F
Orellana, M.C
Pokhrel, A
Virk, S
Snider, J.L
Vellidis, G
Parkash, V
TORGBOR, B.A
Rahman, M.M
Robson, A
Brinkhoff, J
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Topics
Global Proliferation of Precision Agriculture and its Applications
Precision Horticulture
Precision Dairy and Livestock Management
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Food Security and Precision Agriculture
Precision A to Z for Practitioners
Remote Sensing Applications in Precision Agriculture
Guidance, Auto Steer, and GPS Systems
Precision Conservation
Modeling and Geo-statistics
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season Crop Variability
Precision Carbon Management
Profitability, Sustainability, and Adoption
Precision Nutrient Management
Precision Weed Management
Engineering Technologies and Advances
Precision Horticulture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Engineering Technologies and Advances
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season CropVariability
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Precision Nutrient Management
Engineering Technologies and Advances
Profitability, Sustainability and Adoption
Remote Sensing Applications in Precision Agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Precision Agriculture and Climate Change
Unmanned Aerial Systems
Precision Horticulture
Remote Sensing Application / Sensor Technology
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Precision Agriculture and Global Food Security
Drainage Optimization and Variable Rate Irrigation
Geospatial Data
Applications of Unmanned Aerial Systems
Robotics, Guidance and Automation
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Decision Support Systems
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Decision Support Systems
Big Data, Data Mining and Deep Learning
Land Improvement and Conservation Practices
Applications of Unmanned Aerial Systems
Precision Horticulture
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Filter results79 paper(s) found.

1. Determination Of Crop Injury From Aerial Application Of Glyphosate Using Vegetation Indices And Geostatistics

Injury to crops caused by off-target drift of glyphosate can seriously reduce growth and yield, and is of great concern to farmers and aerial applicators. Determining an indirect method for assessing the levels and extent of crop injury could support management decisions. The objectives of this study were to evaluate multiple vegetation indices (VIs) as surrogate variables for glyphosate injury identification and to evaluate the combined use of Geostatistical methods and the VIs to assess... B. Ortiz, S.J. Thomson, Y. Huang, K. Reddy

2. Profitability Of RTK Autoguidance And Its Influence On Peanut Production

Efficient harvest of peanuts (Arachis hypogea L.) requires that the digging implement be accurately positioned directly over the target rows. Small driving... K. Balkcom, B. Ortiz, J. Shockley, J.P. Fulton

3. 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

4. Analysis Of Water Use Efficiency Using On-the-go Soil Sensing And A Wireless Network

An efficient irrigation system should meet the demands of the growing crops. While limited water supply may result in yield reduction, excess irrigation is a waste of resources. To investigate water use efficiency, on-the-go sensing technology was used to reveal soil spatial variability relevant to water holding capacity (in this example, field elevation and apparent electrical conductivity). These high-density data layers were used to identify strategic sites where monitoring water availability... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson

5. A Case Study For Variable-rate Seeding Of Corn And Cotton In The Tennessee Valley Of Alabama

      Farmers have recently become more interested in implementing variable-rate seeding of corn and cotton in Alabama due to increasing seed costs and the potential to maximize yields site-specifically due to inherent field variability.  Therefore, an on-farm case study was conducted to evaluate the feasibility of variable-rate seeding for a corn and cotton rotation. ... S.H. Norwood, J.P. Fulton, A.T. Winstead, J.N. Shaw, D. Rodekohr, C.J. Brodbeck, T. Macy

6. Carbohydrate Reserves On Tapping Systems And Production Of Hevea Brasiliensis

CARBOHYDRATE RESERVES ON TAPPING SYSTEMS AND PRODUCTION OF Hevea brasiliensis Chantuma P1., Lacointe A2., Kasempsap P3., Thanysawanyangkura S4., Gohet E5., Clément A6., Guilliot A7., Améglio T2., Thaler P8. and Chantuma A1. 1 Agriculture Scientist Senior, Chachoengsao Rubber Research Center, RRIT-DOA, Ministry of Agriculture and Cooperative, Sanam Chai Ket, Thailand. 2 INRA, UMR 547 PIAF, F-60100 Clermont-Ferrand, France. 3 Department... D. Chantuma, M. Zaller

7. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field Mapping

  A wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by synthesizing... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton

8. Development Of A Sensor Suite To Determine Plant Water Potential

The goal of this research was to develop a mobile sensor suite to determine plant water status in almonds and walnuts. The sensor suite consisted of an infrared thermometer to measure leaf temperature and additional sensors to measure relevant ambient conditions such as light intensity, air temperature, air humidity, and wind speed. In the Summer of 2009, the system was used to study the relationship between leaf temperature, plant water status, and relevant microclimatic information in an almond... V. Udompetaikul, S. Upadhyaya, B. Lampinen, D. Slaughter

9. Performance Of The Veris Nir Spectrophotometer For Mapping Soil C In The Palouse Soils Of Eastern Washington

Recent advances in sensing technology have made measuring and mapping the dynamics of important soil properties that regulate carbon and nutrient budgets possible. The Veris Technologies (Salinas, KS) Near Infrared (NIR) Spectrometer is one of the first sensors available for collecting geo-referenced NIR soil spectra on-the-go. Field studies were conducted to evaluate the performance of the Veris NIR in wheat grown under both conventional and no-till management in the Palouse region of eastern... F. Pierce, E.M. Perry, S.L. Young, H.P. Collins, P.G. Carter

10. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

11. Adoption And Perceived Usefulness Of Precision Soil Sampling Information In Cotton Production

  Soil testing assists farmers in identifying nutrient variability to optimize input placement and timing. Anecdotal evidence suggests that soil test information has a useful life of 3–4 years. However, perceived usefulness may depend on a variety of factors, including field variability, farmer experience and education, farm size, Extension, and factors indirectly related to farming. In 2009, a survey of cotton farmers in 12 Southeastern states collected information... D.C. Harper, D.M. Lambert, B.C. English, J.A. Larson, R.K. Roberts, M. Velandia, D.F. Mooney, S.L. Larkin

12. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton Yield

A long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

13. Generating Herbicide Effective Application Rate Maps Based On GPS Position, Nozzle Pressure, And Boom Section Actuation Data Collected From Sprayer Control Systems

The application of pre- and post- emergence burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials.  The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides.  While automatic boom section control has provided benefits, pressure differences across... J.D. Luck, A. Sharda, S.K. Pitla, J.P. Fulton, S.A. Shearer

14. Attaching Multiple Conductivity Meters To An Atv To Speed Up Precision Agriculture Soil Surveys

Ground conductivity meters are used in a number of precision agriculture applications, including the estimation of water content, nutrient levels, salinity and depth of topsoil. Typically the Geonics EM38 conductivity meter, and to a lesser extent the EM31, are used for soil surveys. Most conductivity surveys involve towing a ground conductivity meter behind an all-terrain vehicle (ATV). In some situations, such as rutted or sloping fields, it is preferable to mount the conductivity meter directly... E. Morris, A. Clarke, S. Sunley, C. Hill, G. Cranfield

15. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton Production

Technology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia

16. Early Detection of Oil Palm Fungal Disease Infestation Using A Mid-Infrared Spectroscopy Technique

Basal stem rot (BSR) caused by Ganoderma boninense is known as the most destructive disease of oil palm plantations in Southeast Asia. Ganoderma could potentially reduce the market share of palm oil for Malaysia. Currently Malaysia produces about 50% of the world’s supply of palm oil. Early, accurate, and non-destructive diagnosis of Ganoderma fungal infection is critical for management of this disease. Early disease management of Ganoderma could also prevent great losses in production and... S. Liaghat, S. Mansor, H. Shafri, S. Meon, R. Ehsani, S. Azam, N. Noh

17. Affordable Multi-Rotor Remote Sensing Platform for Applications In Precision Horticulture.

Satellite and aerial imaging technologies have been explored for a long time as an extremely useful source of collecting cost-effective data for agricultural applications. In spite of the availability of such technologies, very few growers are using the technology... R. Ehsani, S. Sankaran, J.M. Maja, J.C. Neto

18. Influence Of Phosphorus Application With Or Without Nitrogen On Oat (Avena Sativa) Grass Nutritive Value And In Situ Digestion Kinetics In Buffalo Bulls

Fodder is the mainstay of ruminant production in majority of developing countries. However, its low yield and poor quality are considered considerable constrains which impede ruminant productivity. Fodder production and its nutritive value can be enhanced by ensuring adequate supply and utilization of nutrients... M.U. Nisa, I. Babar, M. Sarwar, N.A. Tauqir, M.A. Shahzad

19. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on Sugarcane

Among the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply in... L.R. Amaral, J.P. Molin, L. Taubinger

20. The Adoption of Information Technologies and Subsequent Changes in Input Use in Cotton Production

The use of precision farming has become increasingly important in cotton production. It allows farmers to take advantage of knowledge about infield variability by applying expensive inputs at levels appropriate to crop needs. Essential to the success of the precision... N.M. Thompson, J.A. Larson, B.C. English, D.M. Lambert, R.K. Roberts, M. Velandia, C. Wang

21. Comparison of Algorithms for Delineating Management Zones

... A.M. Saraiva, R.T. Santos, J.P. Molin

22. 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

23. Raising Awareness of the Potential of Crop Sensing Technologies to Improve Environmental Stewardship

Extensive research and on-farm work using active crop sensors for input management have been conducted in the Midwest and Great Plain USA with favorable results. Contrasting is the situation in the Southeast where the adoption by farmers is still limited and current on-going research is focused on the main southeastern crops. This presentation will provide an overview of the multiple extension activities related to crop sensing involving farmers, extension agents and crop consultants in Alabama.... B. Ortiz

24. Applications Of Small UAV Systems For Tree And Nursery Inventory Management

Unmanned aerial vehicles (UAV) systems could provide low-cost and high spatial resolution aerial images. These features and ease of operation make it a practical tool for applications in precision agriculture and horticulture. This paper highlights the application of UAV systems in tree counting, which is vital for tree inventory management and yield estimation. In this paper, two types of trees were discussed. One type is with non-uniform canopy area (e.g. container plants and citrus... Y. She, R. Ehsani, J. Robbins, J. Owen, J.N. Leiva

25. Building Proactive Predictive Models With Big Data Technology For Precision Agriculture

In a world with ever increasing shortages of food production due to increasing populations and depletion of resources, the need for new technologies and techniques for sustainable and efficient agriculture with long term financial, environmental and cultural benefits are critical.  An area of scientific study concerning crop-production management called Precision Agriculture (PA) is a concept based on integrating modern information technologies such as Big Data Analytics, GPS... C. Lai, C. Belsky

26. Tomato Development Monitoring In An Open Field, Using A Two-Camera Acquisition System

  Introduction   Optimal harvesting date and predicted yield are valuable information when farming open field tomatoes, making harvest planning and work at the processing plant much easier. Monitoring growth during tomato?s early stages is also interesting to assess plant stress or abnormal development. Yet, it is very challenging due to the colours and the high degree of occlusion... F. Rossant, I. Bloch, J. Orensanz, D. Boisgontier, U. Verma, M. Lagarrigue

27. Sound Based Detection Of Moths In Open Fields

Introduction   Open field farming of tomatoes suffers from the presence of harmful moths whose larvas are devastating. Detecting automatically the presence of moths allows regulating the use of pesticides, according to the actual population present in the field. Up to now, sex pheromone traps have been used, the number of captured insects giving some indication about the population. However, proper inspection of the traps is... F. Rossant, J. Orensanz, D. Boisgontier, N. Bouhlel, M. Lagarrigue

28. Measuring And Mapping Sugarcane Gaps

Sugarcane is an important crop in tropical regions of the world and especially for Brazil, the largest sugar supplier in the market, also running a domestic fleet of flex-fuel driven vehicles based on ethanol. Site specific production management can impact sugarcane production by increasing yield and reducing cost. Sugarcane fields are planted each five years, in average, and an important parameter that is measured after the planting operation is the gaps caused by problems during planting... J.P. Veiga, D.S. Cavalcante, J.P. Molin

29. Crop Circle Sensor-Based Precision Nitrogen Management Strategy For Rice In Northeast China

GreenSeeker (GS) sensor-based precision N management strategy for rice has been developed, significantly improved N fertilizer use efficiency. Crop Circle ACS-470 (CC) active sensor is a new user configurable sensor, with a choice of 6 possible bands. The objectives of this study were to identify important vegetation indices obtained from CC sensor for estimating rice yield potential and rice responsiveness to topdressing N application and evaluate their potential improvements over GS normalized... Q. Cao, Y. Miao, J. Shen, S. Cheng, R. Khosla, F. Liu

30. Multivariate Geostatistics As A Tool To Estimate Physical And Chemical Soil Properties With Reduced Sampling In Area Planted With Sugarcane

Precision Agriculture (PA) can be described as a set of tools and techniques applied to agriculture in order to enable localized production management, considering the spatial and temporal variability of crop fields. Among the numerous existing tools, one of the most important ones is the use of geostatistics, whose main objective is the description of spatial patterns and estimation data in non-sampled places. Nowadays, one of the most limiting factors to the... G.M. Sanches, P.S. Graziano magalhaes, H.C. Franco, A.Z. Remacre

31. Precision Agriculture In Sugarcane Production. A Key Tool To Understand Its Variability.

Precision agriculture (PA) for sugarcane represents an important tool to manage local application of fertilizers, mainly because sugarcane is third in fertilizer consumption among Brazilian crops, after soybean and corn. Among the limiting factors detected for PA adoption in the sugarcane industry, one could mention the cropping system complexity, data handling costs, and lack of appropriate decision support systems. The objective of our research group has... P.S. Graziano magalhães, G.M. Sanches, O.T. Kolln, H.C. Franco, O.A. Braunbeck, C. Driemeier

32. Optical Sensors To Predict Nitrogen Demand By Sugarcane

The low effectiveness of nitrogen (N) from fertilizer is a substantial concern in worldwide which has been threatening the sustainability of sugarcane production. The increment of nitrogen use efficiency (NUE) by sugarcane genotypes associated to the best practices of fertilizer management and nutritional diagnosis methods have higher potential to reduce environment impacts of nitrogen fertilization. Due to the difficult to determine N status in soil test as well as there is not... O.T. Kolln, G.M. Sanches, J. Rossi neto, S.G. Castro, E. Mariano, R. Otto, R. Inamasu, P.S. Magalhães, O.A. Braunbeck, H.C. Franco

33. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular India

               Groundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi

34. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

35. Design of a Greenhouse Monitoring System Based on GSM Technologies

Nowadays, internet and mobile technologies are developing and being used in everyday life. Systems based on mobile technologies and IoT (Internet of Things) are being popular in every area of life and science. Innovative IoT applications are helping to increase the quality, quantity, sustainability and cost effectiveness of agricultural production. In this study; a system which monitors temperature, relative humidity and PAR (Photosynthetically Active Radiation) and warns the farmer... G.T. Seyhan, U. Yegul, M. Ayık

36. Maize Seeding Rate Optimization in Iowa Using Soil and Topographic Characteristics.

The ability to collect soil, topography, and productivity information at spatial scales has become more feasible and more reliable with many advancement in precision technologies. This ability, combined with precision services and the accessibility farmers have to equipment capable implementing precision practices, has led to continued interest in making site-specific crop management decisions. The objective of this research was to utilize soil and topographic parameters to optimize seeding rates... M.A. Licht, A. Lenssen, R. Elmore

37. Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four... D. Mulla, A. Laacouri, D. Kaiser

38. Analysis of High Yield Condition Using a Rice Yield Predictive Model

Rice production in Japan is facing problems of yield and quality instability owing to recent climate changes and a decline in rice prices, and possible competition with foreign inexpensive rice. Thus, it is becoming more important to stably achieve high yield and quality, while reducing production costs. Various data, including crop growth, farmer’s management styles, yield and quality, has recently become accessible in actual fields using advanced information and communication technologies.... Y. Hirai, T. Yamakawa, E. Inoue, T. Okayasu, M. Mitsuoka

39. 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

40. Precision Nutrient Management System Based on Ion and Crop Growth Sensing

Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun

41. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote Sensing

Active crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing system... J. Lu, Y. Miao, Y. Huang, W. Shi

42. Net Returns and Production Use Efficiency for Optical Sensing and Variable Rate Nitrogen Technologies in Cotton Production

This research evaluated the profitability and N use efficiency of real time on-the-go optical sensing measurements (OPM) and variable-rate technologies (VRT) to manage spatial variability in cotton production in the Mississippi River Basin states of Louisiana, Mississippi, Missouri, and Tennessee. Two forms of OPM and VRT and the existing farmer practice (FP) were used to determine N fertilizer rates applied to cotton on farm fields in the four states. Changes in yields and N rates due to OPM... J.A. Larson, M. Stefanini, D.M. Lambert, X. Yin, C.N. Boyer, J.J. Varco, P.C. Scharf , B.S. Tubaña, D. Dunn, H.J. Savoy, M.J. Buschermohle, D.D. Tyler

43. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

44. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in Brazil

Given the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitrogen... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães

45. A Software for Managing Remotely Sensed Imagery of Orchards Plantations for Precision Agriculture

Agronomic and environmental characteristics of fruit orchards/ forests can be automatically assessed from remote-sensing images by a computer programme named Clustering Assessment (CLUAS®). The aim of this paper is to describe the operational procedure of CLUAS and illustrate examples of the information provided for citrus orchards and Mediterranean forest. CLUAS® works as an additional menu (“add-on”) of ENVI®, a world-wide known image-processing programme, and operates... L. Garcia-torres, J.M. Peña-barragán, D. Gómez-candón, F. López-granados, M. Jurado-expósito

46. High Capacity System for Precision Agriculture Reconnaissance and Intelligence

Icaros-Demeter has developed a lightweight, compact remote sensing system with a potential for producing 100,000 acre (400km-2) thematic maps per day with high resolution digital RGB/CIR CMOS sensors. The Icaros- Demeter system enables fast, precise location of multiple area and spots types. The system’s ability for producing high precision Digital Surface Models (DSM) over vast areas, offers a direct method for computing agricultural biomass via volume calculations, instead of common indirect... E. Ram, M. Shechter, E. Sela

47. Remote Sensing-based Biomass Maps for an Efficient Use of Fertilizers

For decades the main objective of farmers was to get the highest yields from their farmland. Nowadays, quality of agricultural products is becoming more and more important for the largest returns. In addition, the effects on our environment are also becoming important. These put increasing limitations on modern agriculture. So-called site-specific management can optimize the input of, for instance, nutrients and pesticides to the need of the plants. In this study, the objective was to study whether... J.G. P.w clevers, K.H. Wijnholds, J.N. Jukema

48. Zone Mapping Application for Precision-farming: a Decision Support Tool for Variable Rate Application

We have developed a web-based decision support tool, Zone Mapping Application for Precision Farming (ZoneMAP, http://zonemap.umac.org), which can automatically determine the optimal number of management zones and delineate them using satellite imagery and field survey data provided by users. Application rates, say for fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming applicators. ZoneMAP is linked to Digital Northern... X. Zhang, C. Helgason, G. Seielstad, L. Shi

49. 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

50. Wireless Sensor System for Variable Rate Irrigation

Variable rate irrigation (VRI) systems use intelligent electronic devices to control individual sprinklers or groups of sprinklers to deliver the desired amount irrigation water at each specific location within a field according to VRI prescriptions. Currently VRI systems, including software tools for generate prescription maps, are commercially available for VRI practices. However, algorithms and models are required to determine the desired amount of water that needs to be applied based on the... R. Sui, J. Baggard

51. 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

52. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John

53. Design and Analysis of ISO 11783 Task Controller's Functionality in Server - Client ECU for Agricultural Vehicles

A modern agricultural vehicle's electronic control units (ECU) communicated based on the ISO 11783 standards. The connection of different machines, implements, different manufacturers into a single bus for the exchange of control commands and sensor data are a challenge for the precision agriculture. One of main functionality is the Task controller in the intelligent monitoring system. The task controller is to log data and assign set-point values for automated work (task) sequences... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham

54. A Case Study Comparing Machine Learning and Vegetation Indices for Assessing Corn Nitrogen Status in an Agricultural Field in Minnesota

Compact hyperspectral sensors compatible with UAV platforms are becoming more readily available. These sensors provide reflectance in narrow spectral bands while covering a wide range of the electromagnetic spectrum. However, because of the narrow spectral bands and wide spectral range, hyperspectral data analysis can benefit greatly from data mining and machine learning techniques to leverage its power. In this study, rainfed corn was grown during the 2017 growing season using four nitrogen treatments... A. Laacouri, T. Nigon, D. Mulla, C. Yang

55. Weed Detection Among Crops by Convolutional Neural Networks with Sliding Windows

One of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang

56. Use of Farmer’s Experience for Management Zones Delineation

In the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this study... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães

57. AgDataBox – API (Application Programming Interface)

E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and plant... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli

58. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape Attributes

One of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity in... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes

59. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

60. Using UAV Imagery for Crop Analytics

UAV imagery was collected in April and July of 2017 over a grape vineyard in California’s San Joaquin Valley. Using spectral signatures, a landcover classification was performed to isolate table grapes from the background vegetation and soil. A novel vegetation index was developed based off the unique spectral characteristics of the yellowing effects of chlorosis within the table grape vines. Spatial statistics were run only on the pixels containing grape plants, and a relative vegetation... C. Adams, A. Coates

61. Predicted Nitrate-N Loads for Fall, Spring, and VRN Fertilizer Application in Southern Minnesota

Nitrate-N from agricultural fields is a source of pollution to fresh and marine waters via subsurface tile drainage.  Sensor-based technologies that allow for in-season monitoring of crop nitrogen requirements may represent a way to reduce nitrate-N loadings to surface waters by allowing for fertilizer application on a more precise spatial and temporal resolution.  However, little research has been done to determine its effectiveness in reducing nitrate-N losses.  In this study,... G.L. Wilson, D.J. Mulla, J. Galzki, A. Laacouri, J. Vetsch

62. Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural Networks

This paper presents a method which can provide support in determining the grass-clover ratio, in grass-clover fields, based on images from an unmanned aerial vehicle. Automated estimation of the grass-clover ratio can serve as a tool for optimizing fertilization of grass-clover fields. A higher clover content gives a higher performance of the cows, when the harvested material is used for fodder, and thereby this has a direct impact on the dairy industry. An android application... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen

63. Precision Agriculture Research Infrastructure for Sustainable Farming

Precision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan

64. Site-Specific Management Zones Delineation Using Drone-Based Hyperspectral Imagery

Conventional techniques (e.g., intensive soil sampling) for site-specific management zones (MZ) delineation are often laborious and time-consuming. Using drones equipped with hyperspectral system can overcome some of the disadvantages of these techniques. The present work aimed to develop a drone-based hyperspectral imagery method to characterize the spatial variability of soil physical properties in order to delineate site-specific MZ. Canonical correlation analysis (CCA) was used to extract... H. Agili, K. Chokmani, A. Cambouris, I. Perron, J. Poulin

65. Delineation of Soil Management Zones: Comparison of Three Proximal Soil Sensor Systems Under Commercial Potato Field in Eastern Canada.

Precision agriculture (PA) involves optimization of seeding, fertilizer application, irrigation, and pesticide use to optimize crop production for the purpose of increasing grower revenue and protecting the environment. Potato crops (Solanum tuberosum L.) are recognized as good candidates for the adoption of PA because of the high cost of inputs. In addition, the sensitivity of potato yield and quality to crop management and environmental conditions makes precision management economically... A. Cambouris, I. Perron, B. Zebarth, F. Vargas, K. Chokmani, A. Biswas, V. Adamchuk

66. Active Canopy Sensor-Based Precision Rice Management Strategy for Improving Grain Yield, Nitrogen and Water Use

The objective of this research was to develop an active crop sensor-based precision rice (Oryza sativa L.) management (PRM) strategy to improve rice yield, N and water use efficiencies and evaluate it against farmer’s rice management in Northeast China. Two field experiments were conducted from 2011 to 2013 in Jiansanjiang, Heilongjiang Province, China, involving four treatments and two varieties (Kongyu 131 and Longjing 21). The results indicated that PRM system significantly increased... J. Lu, H. Wang, Y. Miao

67. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

68. Unmanned Aerial Systems and Remote Sensing for Cranberry Production

Wisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Initial... B. Luck, J. Drewry, E. Chassen, S. Steffan

69. Comparison of the Performance of Two Vis-NIR Spectrometers in the Prediction of Various Soil Properties

Spectroscopy has shown capabilities of predicting certain soil properties. Hence, it is a promising avenue to complement traditional wet chemistry analysis that is costly and time-consuming. This study focuses on the comparison of two Vis-NIR instruments of different resolution to assess the effect of the resolution on the ability of an instrument to predict various soil properties. In this study, 798 air dried and compressed soil samples representing different agro-climatic conditions across... M. Marmette, V. Adamchuk, J. Nault, S. Tabatabai, R. Cocciardi

70. Computer Vision Techniques Applied to Natural Scenes Recognition and Autonomous Locomotion of Agricultural Mobile Robots

The use of computer systems in Precision Agriculture (PA) promotes the processes’ automation and its applied tasks, specifically the inspection and analysis of agricultural crops, and guided/autonomous locomotion of mobile robots. In this context, this research aims the application of computer vision techniques for agricultural mobile robot locomotion, settled through an architecture for the acquisition, image processing and analysis, in order to segment, classify and recognize patterns... L.C. Lugli, M.L. Tronco, A.J. Porto

71. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri

72. Should We Increase or Decrease the Fertilization in the Zones with the Highest Crop Productivity Potential?

Introduction. In traditional farming, fertilizers are applied homogeneously on the agricultural fields taking into account the average crop recommendation. As most fields are not homogeneous, this results in overfertilization of certain zones and underfertilization of other zones. The excess of nitrate leaches to the surface and groundwaters which causes problems with the water quality. Precision fertilizer management has been proposed to reduce these negative effects.... A. Tsibart, A. Postelmans, J. Dillen, A. Elsen, G. Van de ven, W. Saeys

73. Data Sources and Risk Management in Precision Agriculture

The digitalisation of the agricultural economy provides more data about the biological processes and technological solutions used for producing agricultural products than ever before. Paralell to the data collection – aiming to provide information for agricultural decision-making and operations – the data informs the farmers, public administration officers and other players in agriculture about the state of the environment. The strategic planning on operation of farms and data handling... G. Milics, P.M. Varga, F. Magyar, I. Balla

74. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target Regression

Peanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco

75. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez

76. Analysis of the Mapping Results Using SoilOptix TM Technology in Chile After Two Seasons

Soil mapping is a key element to successfully implement Integrated Nutrient Management (INM) in high value crops.  SoilOptixTM is a mapping service based on the use of gamma radiation technology that arrived in Chile in 2019. Since then, around 2000 ha have been mapped, mainly in fruit orchards and vineyards. The technology has demonstrated its value in determining the most limiting factors in new and old orchards, and the possibility of correcting them in a site-specific... R.A. Ortega, A.F. Ortega, M.C. Orellana

77. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of Cotton

The use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationships... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash

78. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern Ghana

The rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retrieved... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff

79. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia