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Mouazen, A.M
Corrêdo, L
Eivazi, F
Melkonian, J
Maloof, J
Lamb, D
Molendijk, L.P
Quaderer, J
Struthers, R.R
Mathew, J
Mahmoudi, S
Marchant, B.P
Stephens, P
Schwalbert, R
Vories, E
Chang, Y.K
Souza, E
Lilienthal, H
Lutz, C.C
Schindelbeck, R
Maja, J.M
Millen, J.A
Pena-Yewtukhiw, E.M
Cao, Q
Maharjan, B
Mohd Hanif, A
Verschwele, A
Mishra, A.K
Camargo Neto, J
Shiratsuchi, L
Milani, I
Erdenee, B
Liu, C
L, R.N
Luck, J
Souza, W.J
Lang, V
Xie, R
Suokannas, A
Samborski, S.M
Carneiro, F.M
Taylor, D
Lee, W
Erickson, B
Qiu, Z
Sorensen, M.D
Powell, K
Tsoulias, N
MacAuliffe, R
Schwiesow, D
Tang, L
Skouby, D
Souza, E.G
Emadi, M
Longchamps, L
Lopes, W
Sade, Z
Cavayas, F
Phillips, S.B
Lowenberg-DeBoer, J
Clay, D.E
Pittman, J
Cho, Y
Meng, L
Sanaei, A
Schweinzer, V
Pereira, J.C
Chae, Y
Swen, W
Scharf , P.C
Marlier, G
Eyster, R
Cloutier, G
Leszczyńska, R
Peeters, A
Chen, T
Martinez, M.M
Tavares, T.R
Susin, A
Virk, S.S
Lamb, D.W
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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
Stephens, P
Mackin, S
Holmes, G
Naser, M.A
Khosla, R
Haley, S
Reich, R
Longchamps, L
Moragues, M
Buchleiter, G.W
McMaster, G.S
Khosla, R
Westfall, D.G
Longchamps, L
Khosla, R
Longchamps, L
Panneton, B
Simard, M
Leroux, G.D
Longchamps, L
Longchamps, L
Panneton, B
Westfall, D.G
Khosla, R
Suokannas, A
Backman, J
Visala, A
Kunnas, A
Qiu, Z
Dosskey, M.G
Abu Kassim, F
Vadamalai, G
Mohd Hanif, A
Balasundram, S.K
Gowda, H.H
Reddy, K.A
Patil, M.B
L, R.N
Shanwad, U
Chung, S
Kong, J
Huh, Y
Bae, K
Hur, S
Lee, D
Chae, Y
Ehsani, R
Salyani, M
Maja, J.M
Mishra, A.R
Larbi, P.A
Camargo Neto, J
Zaman, Q
Esau, T.J
Farooque, A.A
Schumann, A.W
Percival, D.C
Chang, Y.K
Shiratsuchi, L
Lutz, C.C
Ferguson, R.B
Adamchuk, V.I
Dutra, R
Sousa, R
Porto, A
Inamasu, R
Lopes, W
Tronco, M
Cao, Q
Miao, Y
Feng, G
Gao, X
Liu, B
Khosla, R
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Stanley, J.N
Schneider, D.A
Lamb, D.W
Khot, L.R
Ehsani, R
Albrigo, G
Campoy, J
Wellington, C
Swen, W
Camergo Neto, J
Schwiesow, D
Eivazi, F
Miao, Y
Cao, Q
Cui, Z
Li, F
Dao, T.H
Khosla, R
Chen, X
Chen, L
Zhao, C
Huang, W
Chen, T
Wang , J
Longchamps, L
Panneton, B
Simard, M
Theriault, R
Roger, T
Longchamps, L
Panneton, B
Leroux, G.D
Simard, M
Theriault, R
Trotter, M.G
Lamb, D.W
Hinch, G.N
Guppy, C.N
Lamb, D.W
Trotter, M.G
Schneider, D
Stone, K
Bauer, P.J
Busscher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Griffin, T
Lowenberg-DeBoer, J
Shiratsuchi, L
Ferguson, R.B
Shanahan, J.F
Adamchuk, V.I
Slater, G
Qiu, Z
Dosskey, M.G
Frieberg, D
Sauer, B
Guppy, C.N
Trotter, M.G
Lamb, D.W
Delgado, J.A
Donald, G.E
Trotter, M.G
Lamb, D.W
Levow, G
van Es, H.M
Erdenee, B
Batbayar, B
Tateishi, R
Grove, J
Pena-Yewtukhiw, E.M
Pena-Yewtukhiw, E.M
Grove, J
Pena-Yewtukhiw, E.M
Mata-Padrino, D
Bryan, W
Taylor, D
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Quaderer, J
Coonen, J
Lange, A
Pauly, K
Souza, E
Schenatto, K
Rodrigues, F
Rocha, D
Bazzi, C.L
Schenatto, K
Bazzi, C.L
Bier, V
Souza, E
Fulton, J.P
Balkcom, K.S
Ortiz, B.V
McDonald, T.P
Pate, G.L
Virk, S.S
Poncet, A
Cao, Q
Miao, Y
Shen, J
Cheng, S
Khosla, R
Liu, F
Huh, Y
Chung, S
Chae, Y
Lee, J
Kim, S
Choi, M
Jung, K
Pittman, J
Wang, C
Chen, T
Dong, J
Li, C
Ulusoy, Y
Tümsavas, Z
Mouazen, A.M
Tekin, Y
Brian, S
Toledo, O.M
Tang, L
Holland, K.H
Lamb, D.W
Samborski, S.M
Cosby, A.M
Falzon, G
Trotter, M
Stanley, J
Powell, K
Schneider, D
Lamb, D
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Nguyen, T
Slaughter, D
Townsley, B
Carriedo, L
Maloof, J
Sinha, N
Siegfried, J
Khosla, R
Longchamps, L
Patto Pacheco, E
Liu, J
Longchamps, L
Khosla, R
Walsh, O.S
Samborski, S.M
Stępień, M
Gozdowski, D
Lamb, D.W
Gacek, E.S
Drzazga, T
van Es, H
Sela, S
Marjerison, R
Moebiu-Clune, B
Schindelbeck, R
Moebius-Clune, D
Rudolph, S
Marchant, B.P
Gillingham, V
Kindred, D
Sylvester-Bradley, R
Lilienthal, H
Wilde, P
Schnug, E
Sela, S
van-Es, H
McLellan, E
Melkonian, J
Marjerison , R
Constas, K
Gerighausen, H
Lilienthal, H
Schnug, E
Lilienthal, H
Gerighausen, H
Schnug, E
Huang, S
Miao, Y
Yuan, F
Gnyp, M.L
Yao, Y
Cao, Q
Lenz-Wiedemann, V
Bareth, G
Bazzi, C.L
Araujo, R
Souza, E.G
Schenatto, K
Gavioli, A
Betzek, N.M
Longchamps, L
Khosla, R
Reich, R
Barwick, J.D
Trotter, M
Lamb, D.W
Dobos, R
Welch, M
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
Souza, W.J
Benez, S.H
Nakazawa, P.H
Santana Neto, A.J
Citon, L.C
Akune, V.S
Schwalbert, R
Carneiro Amado, T.J
Horbe, T
Corassa, G.M
Gebert, F.H
Sung, N
Chung, S
Kim, Y
han, K
Choi, J
Kim, J
Cho, Y
Jang, S
Ortega, R.A
Martinez, M.M
Poblete, H.P
Tremblay, N
Khun, K
Vigneault, P
Bouroubi, M.Y
Cavayas, F
Codjia, C
Skouby, D
Schumacher, L
Yost, M
Kitchen, N.R
Erickson, B
Clay, D.E
Clay, S.A
Fausti, S
Lilienthal, H
Schnug, E
Haneklaus, S
Luck, J
Parrish, J
Thompson, L
Krienke, B
Glewen, K
Ferguson, R.B
Sanaei, A
Mullen, R.W
Phillips, S.B
Raun, W.R
Thomason, W.E
Clay, D.E
Clay, S.A
Reicks, G
Horvath, D
Baghernejad, M
Emadi, M
Baghernejad, M
Emadi, M
Bauer, P.J
Stone, K.C
Bussher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Struthers, R.R
Johannsen, C.J
Morris, D.K
Liu, X
Cao, Q
Tian, Y
Zhu, Y
Zhang, Z
Cao, W
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Khakbazan, M
Moulin, A
Huang, J
Michiels, P
Xie, R
Maharjan, B
Lilienthal, H
Haneklaus, S.H
Schnug, E
Yang, L
Huang, L
Meng, L
Wang, J
Wu, D
Fu, X
Li, S
Lilienthal, H
Gerighausen, H
Schnug, E
Iwersen, M
Reiter, S
Schweinzer, V
Kickinger, F
Öhlschuster, M
Lidauer, L
Auer, W
Drillich, M
Berger, A
Trevisan, R.G
Eitelwein, M.T
Ferraz, M.N
Tavares, T.R
Molin, J.P
Neves, D.C
Schweinzer, V
Lidauer, L
Kickinger, F
Öhlschuster, M
Auer, W
Drillich, M
Iwersen, M
Berger, A
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Bazzi, C.L
Jasse, E.P
Souza, E.G
Magalhães, P.S
Michelon, G.K
Schenatto, K
Gavioli, A
Balasundram, S.K
Chong, Y
Mohd Hanif, A
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
van Evert, F.K
Been, T
Booij, J.A
Kempenaar, C
Kessel, G.J
Molendijk, L.P
Li, S
Cao, Q
Liu, X
Tian, Y
Zhu, Y
Seo, Y
Lee, W
Kim, Y
Chung, S
Jang, S
Bae, I
Souza, E
Schenatto, K
Bazzi, C
de Souza, M.R
Bertani, T.D
Parraga, A
Bredemeier, C
Trentin, C
Doering, D
Susin, A
Negreiros, M
Bouroubi, Y
Bugnet, P
Nguyen-Xuan, T
Bélec, C
Longchamps, L
Vigneault, P
Gosselin, C
Vories, E
Jones, A
Stevens, G
Meeks, C
Khun, K
Vigneault, P
Fallon, E
Tremblay, N
Codjia, C
Cavayas, F
Phillippi, E
Khosla, R
Longchamps, L
Turk, P
Li, Y
Zhang, Y
Liu, X
Liu, C
Erickson, B
Lowenberg-DeBoer, J
Bradford, J
King, W
Dynes, R
Laurenson, S
Zydenbos, S
MacAuliffe, R
Taylor, A
Manning, M
Roberts, A
White, M
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
Longchamps, L
Panneton, B
Tremblay, N
Tsoulias, N
Paraforos, D
Brandes, N
Fountas, S
Zude-Sasse, M
Bazzi, C.L
Silva, F.V
Gebler, L
Souza, E.G
Schenatto, K
Sobjak, R
Dos Santos, R.S
Hachisuca, A.M
Franz, F
Bazzi, C.L
Martins, M.R
Gebler, L
Souza, E.G
Schenatto, K
Sobjak, R
Hachisuca, A.
Franz, F
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Rydahl, P
Boejer, O
Torresen, K
Montull, J.M
Taberner, A
Bückmann, H
Verschwele, A
Virk, S.S
Prostko, E.P
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Tavares, T.R
Molin, J.P
da Silva , T.R
de Carvalho , H.W
Yang, C
Suh, C
Guo, W
Zhao, H
Zhang, J
Eyster, R
Mandal, D
Siqueira, R.D
Longchamps, L
Khosla, R
Katz, L
Ben-Gal, A
Litaor, I
Naor, A
Peeters, A
Goldshtein, E
Alchanatis, V
Cohen, Y
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Lang, V
Tóth, G
Csenki, S
Dafnaki, D
Plum, J
Quoitin, B
Dufrasne, I
Mahmoudi, S
Lebeau, F
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Longchamps, L
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Das, A
Flores, P
Zhang , Z
Friskop, A
Mathew, J
Samborski, S.M
Szatylowicz, J
Gnatowski, T
Leszczyńska, R
Thornton, M
Walsh, O
Ruma, F.Y
Munnaf, M.A
De Neve, S
Mouazen, A.M
Vories, E
Veum, K
Sudduth, K
Capolicchio, J
Mennuti, D
Milani, I
Fortunato, M
Petix, R
Reyes Gonzalez, J
Sunkevic, M
Lamb, D.W
Schaefer, M.T
Beeri, O
Pelta, R
Sade, Z
Shilo, T
Ghimire, D
Maharjan, B
Topics
Global Proliferation of Precision Agriculture and its Applications
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Precision Crop Protection
Guidance, Robotics, Automation, and GPS Systems
Engineering Technologies and Advances
Precision Conservation and Carbon Management
Spatial Variability in Crop, Soil and Natural Resources
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Precision Horticulture
Proximal Sensing in Precision Agriculture
Precision A to Z for Practitioners
Precision Conservation
Precision Nutrient Management
Modeling and Geo-statistics
Precision Weed Management
Precision Livestock Management
Sensor Application in Managing In-season Crop Variability
Profitability, Sustainability, and Adoption
Global Proliferation of Precision Agriculture and its Applications
Precision Carbon Management
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Conservation Management
Engineering Technologies and Advances
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Precision Crop Protection
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Decision Support Systems in Precision Agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Precision Agriculture and Climate Change
Precision Dairy and Livestock Management
Profitability, Sustainability and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Unmanned Aerial Systems
Agricultural Education
No Group Selected
Sensor Application in Managing In-season Crop Variability
Precision Management / Precision Conservation
Remote Sensing for Nitrogen Management
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Modelling and Geo-Statistics
Applications of Unmanned Aerial Systems
Geospatial Data
Profitability and Success Stories in Precision Agriculture
Precision Agriculture and Global Food Security
Site-Specific Nutrient, Lime and Seed Management
Precision Crop Protection
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Precision Horticulture
Education and Outreach in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Robotics, Guidance and Automation
Site-Specific Pasture Management
Decision Support Systems
Education and Outreach in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Geospatial Data
Farm Animals Health and Welfare Monitoring
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Site-Specific Nutrient, Lime and Seed Management
Precision Agriculture and Global Food Security
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
Home » Authors » Results

Authors

Filter results138 paper(s) found.

1. Minimizing On-farm Point Source Contamination Of Pesticides Using The “Biobed” Method

  Microorganisms play a vital role in maintaining the environmental quality through their metabolic activities. The highly versatile metabolic capabilities of fungi and bacteria can be used to reclaim polluted ecosystems. A variety of biological, chemical, and physical methods have been used for degradation and detoxification of pesticides. However, conventional clean- up methods are costly and not always effective. Agrochemical storage and handling practices have been targeted... F. Eivazi

2. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain

... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen

3. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracting... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

4. Sensing The Inter-row For Real-time Weed Spot Spraying In Conventionally Tilled Corn Fields

The spatial distribution of weeds is aggregated most of the time in crop fields. Site-specific management of weeds could result in economical and environmental benefits due to herbicide... L. Longchamps, B. Panneton, M. Simard, R. Theriault, T. Roger

5. Partial Weed Scouting For Exhaustive Real-time Spot Spraying Of Herbicides In Corn

Real-time spot spraying of weeds implies the use of plant detectors ahead of a sprayer. The range of weed spatial autocorrelation perpendicularly to crop rows is often greater than the space between the corn rows. To assess the possibility of using less than one plant detector scouting each inter-row, a one hectare field was entirely sampled with ground pictures at the appropriate timing for weed spraying. Different ways of disposing the detectors ahead of the sprayer were virtually tested. Scouting... L. Longchamps, B. Panneton, G.D. Leroux, M. Simard, R. Theriault

6. GNSS Tracking Of Livestock: Towards Variable Fertilizer Strategies For The Grazing Industry

This study reveals the potential for GPS tracking in the grazing industry. By monitoring the locations and movement of livestock, times of peak grazing activity can be identified and these can in turn produce maps of preferred grazing areas, and by examining residency times provide an indication of spatial variability in grazing pressure. A comparison of grazing preference can be made to similarly inferred camping areas to understand the potential redistribution of nutrients within a paddock.... M.G. Trotter, D.W. Lamb, G.N. Hinch, C.N. Guppy

7. Ultra Low Level Aircraft (ULLA) As A Platform For Active Optical Sensing Of Crop Biomass

Crop producers requiring crop biomass maps to support timely application of in-season fertilisers, pesticides or growth regulators rely on either on-ground active sensors or airborne/satellite imagery. Active crop sensing (for example using Yara N-SensorTM, GreenseekerTM or CropcircleTM) can only be used when the crop is accessible by person or vehicle, and extensive, high-resolution coverage is time consuming. On the other hand, airborne or satellite imaging is... D.W. Lamb, M.G. Trotter, D. Schneider

8. Variable-rate Irrigation Management For Peanut Using Irrigator Pro

  Variable-rate irrigation has the potential to save substantial water. These water savings will become more important as urban, industrial, and environmental sectors compete with agriculture for available water. However, methodologies to precision-apply water for maximum agronomic and economic utility are needed.  Information is needed to optimally management variable-rate irrigation systems. In this study, we conducted irrigation experiments on peanut to compare... K. Stone, P.J. Bauer, W.J. Busscher, J.A. Millen, D.E. Evans, E.E. Strickland

9. Worldwide Adoption Of Precision Agriculture Technology: The 2010 Update

Precision agriculture technology has been on the market for nearly two decades; and the question remains regarding how and to what extent farmers are making the best use of the technology. Yield monitors, GPS-enabled guidance technology, farm-level mapping and GIS software, on-the-go variable rate applications, and other spatial technologies are being used by thousands of farmers worldwide. The USDA Agricultural Resource Management Survey (ARMS) and the annual CropLife/Purdue University Precision... T. Griffin, J. Lowenberg-deboer

10. Comparison Of Spectral Indices Derived From Active Crop Canopy Sensors For Assessing Nitrogen And Water Status

... L. Shiratsuchi, R.B. Ferguson, J.F. Shanahan, V.I. Adamchuk, G. Slater

11. A Comparison Of Alternative Methods For Prioritizing Buffer Placement In Agricultural Watersheds For Water Quality Improvement

Conservation buffers are a widely used best management practice for reducing agricultural nonpoint source pollution. Various governmental programs and community initiatives have been implemented to adopt conservation buffers for water quality improvement. Since there is substantial cost for installing conservation buffers in watersheds, cost-effectiveness would be improved by targeting buffers to locations where they would produce greater benefit and to avoid locations... Z. Qiu, M.G. Dosskey, D. Frieberg

12. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol Soil

Crop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado

13. 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

14. Land Information System Of Precision Farming In Mongolia Using Remote Sensing And Geographical Information System

    Remote sensing (RS) and geographic information system (GIS) technologies have been of great use to planners in planning for efficient use of natural resources at national, sub region and rural levels.   RS can be used for precision farming in a number of ways for providing input supplies and variability management through decision support system.   GIS is the principal technology used to integrate spatial data... B. Erdenee, B. Batbayar, R. Tateishi

15. C And N Coupling Through Time: Soil C, N, And Grain Yield In A Long-term Continuous Corn Trial

Gains and losses of both C and N are important in agricultural landscapes. Temporal changes in the pattern of crop yield response to tillage and fertilizer input are commonly observed; often weakly interpreted, in long-term research. A 38-year-long monoculture corn (Zea mays L.) tillage (moldboard plow, no-tillage) by N rate (0, 84, 168, 336 kg N per hectare) trial was sampled to a depth of 100 cm, as was the surrounding... J. Grove, E.M. Pena-yewtukhiw

16. Crop Rotation Impacts ‘Temporal Sampling’ Needed For Landscape-defined Management Zones

Yield and landscape position are used to delineate management zones, but this approach is confounded by yield’s weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options (e.g. crop rotation) also influence yield stability. Our objective was to build a model that would describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotations,... E.M. Pena-yewtukhiw, J. Grove

17. Impact Of Winter Grazing On Forage Biomass Topography Soil Strength Spatial Relationships

Spatial relationships between soil properties, forage productivity, and landscape can be used to manage site-specific grazing. Soil penetration resistance and forage biomass were collected for three years in winter grazing experiment. The three ha experimental area was divided into six paddocks, hay was cut twice per year in the months of May and June, and forage stockpiled after the second cutting. Animals were admitted to paddocks at the end of November, at a stocking rate... E.M. Pena-yewtukhiw, D. Mata-padrino, W. Bryan

18. Gps Tracking Of Sheep To Investigate Shelter And Shade Use In Relation To Climatic Conditions

In Australia inclement weather contributes to losses of new-born lambs and recently-shorn sheep. Provision of forced shelter has been observed to reduce lamb losses by up to 10 percent and when given a choice, ewes preferentially seek shelter on offer for a period of approximately two weeks post shearing (Alexander et al. 1980). Given significant sheep losses can occur during adverse weather conditions a better understanding of sheep use of shelter and/or alternative ways of attracting sheep to... D. Taylor, , , , , ,

19. 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

20. Exploiting the Dmc Satellite Constellation for Applications in Precision Agriculture

This paper presents the unique capabilities of the DMC constellation of optical sensors, and examples of how a number of organisations around the world are exploiting this powerful data source for applications in precision farming. The DMC consists of five satellites built in the UK by Surrey Satellite Technology Ltd, each carrying a wide swath (650km) optical sensor. It is an international programme of satellite ownership and groundstations, with joint campaigns being coordinated centrally... P. Stephens, S. Mackin, G. Holmes

21. Can Active Sensor Based NDVI Consistently Classify Wheat Genotypes?

ABSTRACT ... M.A. Naser, R. khosla, S. Haley, R. Reich, L. Longchamps, M. Moragues, G.W. buchleiter, G.S. Mcmaster

22. Early Detection of Corn N-Deficiency by Active Fluorescence Sensing in Maize

Globally, the agricultural nitrogen use efficiency (NUE) is no more than 40 %. This low efficiency comes with an agronomic, economic and environmental cost. By better management of spatial and temporal variability of crop nitrogen need, NUE can be improved. Currently available crop canopy sensors based on reflectance are capable... R. Khosla, D.G. Westfall, L. Longchamps

23. Comparing Sensing Platforms for Crop Remote Sensing

Remote sensing offers the possibility to obtain a rapid and non-destructive diagnosis of crop health status. This gives the opportunity to apply variable rates of fertilizers to meet the actual crop needs at every locations of the field. However, the commonly used normalized difference vegetation index (NDVI)... R. Khosla, L. Longchamps

24. Development of a Quick Diagnosis Method to Target Fields with Better Potential for Site-Specific Weed Management

Site-specific weed management appears as an innovative way of saving herbicides in crop while maintaining yield. This can potentially lead economic and ecological benefits. However, it was reported in the literature that savings range from 1 % to 94 % from one field to the other. This implies that certain fields... B. Panneton, M. Simard, G.D. Leroux, L. Longchamps

25. Testing The Author Sequence - Finalize

This is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla

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

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

27. Indexes for Targeting Buffer Placement to Improve Water Quality

Targeting the placement of vegetative buffers may increase their effectiveness to improve watershed water quality. Several GIS-based indexes have been developed to help planners identify relatively better locations for placing buffers. Conservation planners require consistent and clear recommendations on which index should be used in a given planning... Z. Qiu, M.G. Dosskey

28. A Non-Destructive Method of Estimating Red Tip Disease in Pineapple

Red Tip disease typically reduces pineapple yields by up to 50%. At present, the causal agent of Red Tip disease is still unconfirmed. B... F. Abu kassim, G. Vadamalai, A. Mohd hanif, S.K. Balasundram

29. Natural Resources Management through Frontier Technologies - A Case Study from India

The social and economic development of the state is interlaced with our natural resources, and the manner in which they are managed and exploited.  The unplanned development and overexploitation of resources are exerting various... H.H. Gowda, K.A. Reddy, M.B. Patil, R.N. L, U. Shanwad

30. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the Day

Several electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environment,... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae

31. Young Leaf Detection for Spot Spray Treatment of Citrus Canopies to Control Psyllids

Huanglongbing (HLB) is an important disease of citrus that is spread mainly through a vector, psyllid (Diaphorina citri), that feeds predominantly on young leaves.  Given the selective feeding of the insect, treating only the young flush, instead of spraying the entire... R. Ehsani, M. Salyani, J.M. Maja, A.R. Mishra, P.A. Larbi, J. Camargo neto

32. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry Fields

An automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang

33. Integrated Crop Canopy Sensing System for Spatial Analysis of In-Season Crop Performance

Over the past decade, the relationships between leaf color, chlorophyll content, nitrogen supply, biomass and grain yield of agronomic crops have been studied widely.... L. Shiratsuchi, C.C. Lutz, R.B. Ferguson, V.I. Adamchuk

34. Architecture and Model of Data Integration between Management Systems and Agricultural Machines for Precision Agriculture

 The development of robotic systems has challenges as the high degree of interdisciplinarity, the difficulty of integration between the various robotic control... R. Dutra, R. Sousa, A. Porto, R. Inamasu, W. Lopes, M. Tronco

35. Performance of Two Active Canopy Sensors for Estimating Winter Wheat Nitrogen Status in North China Plain

... Q. Cao, Y. Miao, G. Feng, X. Gao, B. Liu, R. Khosla

36. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

37. Spatial Apparent Electrical Conductivity (ECa), Soil Moisture and Water Use Efficiency in Vertosol Soils

Producing high resolution maps of water use efficiency (crop yield per unit of water consumption; WUE) for precision crop management is limited by our ability to readily produce maps of soil moisture... J.N. Stanley, D.A. Schneider, D.W. Lamb

38. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological Conditions

This study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. campoy, C. Wellington, W. Swen, J. Camergo neto

39. Raven Sponsor Presentation: Slingshot Overview

Slingshot, a suite of products and services centered around high-speed wireless connectivity in the cab ... D. Schwiesow

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

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

41. 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

42. 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

43. The Influence Of The Interpolation Method In The Management Zones Generation

The definition of management zones (MZ) allows the concepts of precision agriculture (PA) to be used even in small producers. Methods for defining these MZ were created and are being used, obtaining satisfactory results with different crops and parameters (FLEMING & WESTFALL, 2000; ORTEGA & SANTIBÁÑEZ, 2007; MILANI et al., 2006). Through methodologies, the attributes that are influencing the productivity are selected and thematic maps are generated with the... K. Schenatto, C. Bazzi, V. Bier, E. Souza

44. Row-Crop Planter Requirements To Support Variable-Rate Seeding Of Maize

Current planting technology possesses the ability to increase crop productivity and improve field efficiency by precisely metering and placing crop seeds. Growing high yielding crops not only requires using the right seed variety and rate but also achieving optimal performance with available planter technology. Planter performance depends on using the correct planter and technology (display and rate controller system) setup which consists of determining optimal settings for different planting... J.P. Fulton, K.S. Balkcom, B.V. Ortiz, T.P. Mcdonald, G.L. Pate, S.S. Virk, A. Poncet

45. 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

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

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

47. Estimation of Vegetative Biomass Using On-the-Go Mobile Sensors

Non-destructive methods for estimation of vegetative biomass have been developed using several remote sensing strategies as well as physical measurement techniques. An effective method for estimating biomass must be at least as accurate as the accepted standard for destructive removal measurement techniques such as a forage harvester or quad harvest strategies. In large part vegetative biomass is considered a function of canopy or plant height. Subsequently, a method or... J. Pittman

48. Study Of Spatio-Temporal Variation Of Soil Nutrients In Paddy Rice Planting Farm

It is significant to analysis the spatial and temporal variation of soil nutrients for precision agriculture especially in large-scale farms. For the data size of soil nutrients grows once after sampling which mostly by the frequency of one year or months, to discover the changing trends of exact nutrient would be instructive for the fertilization in the future. In this study, theories of GIS and geostatistics were used to characterize the spatial and temporal variability of soil... C. Wang, T. Chen, J. Dong, C. Li

49. Prediction Of Cation Exchange Capacity Using Visible And Near Infrared Spectroscopy

Cation exchange capacity (CEC) of the soil is a measure of the soil ability to hold positively charged ions and is an important indicator of soil physicochemical characteristic. It is an important property for site specific management of soil nutrients in precision agriculture. The conventional analytical methods used for the determination of CEC are expensive, difficult and time consuming, because different cations must be extracted and determined. Visible and near infrared (vis-NIR) spectroscopy... Y. Ulusoy, Z. Tümsavas, A.M. Mouazen, Y. Tekin

50. Assessing Impact Of Precision On Agricultural Energy Requirements: Weed Control Case Study

The anticipated world population increase demands growth in sustainable food production. The current trend is to use more efficient agricultural processes in order to increase food production. Precision agriculture (PA) technology provides the means to increase equipment productivity and field and input efficiency. The concept of small modular and scalable intelligent machines tries to address the challenge of more productivity with the goal of reduced cost and power. In addition,... S. Brian, O.M. Toledo, L. Tang

51. Airborne Active Optical Sensors (AOS) For Photosynthetically-Active Biomass Sensing: Current Status And Future Opportunities

The first published deployment of an active optical reflectance sensor (AOS) in a low-flying aircraft in 2009 catalyzed numerous developments in both sensor development and sensor platform integration. Integral to these sensors is a modulated light source composed of high power LED technology that emits high radiance polychromatic light. The sensor easily mounts to agricultural aircraft and can sense agricultural landscapes at altitudes from a few meters to altitudes exceeding 40 meters while... K.H. Holland, D.W. Lamb

52. Does Nitrogen Balance Surplus Done At Field Level Help To Assess Environmental Effects Of Variable Nitrogen Application In Winter Wheat?

Increased nitrogen use efficiency (NUE) is important as a specific consideration to decrease negative impacts of nitrogen (N) on the environment and provide better crop quality. Therefore, in many European countries N is used with restrictions due to UE regulations, set to increase NUE. This is particularly important in wheat production because this crop in EU accounts for 48% of cereal production and uses about 25% of total N-fertilizer applied. One of the methods applied to increase NUE... S.M. Samborski

53. Using A Decision Tree To Predict The Population Density Of Redheaded Cockchafer (Adoryphorus Couloni) In Dairy Fields

A native soil dwelling insect pest, the redheaded cockchafer (Adoryphorus couloni) (Burmeister) (RHC) is an important pest in the higher rainfall regions of south-eastern Australia. Due to the majority of its lifecycle spent underground feeding on the roots and soil organic matter the redheaded cockchafer is difficult to detect and control. The ability to predict the level of infestation and location of redheaded cockchafers in a field may give producers the option to use an endophyte containing... A. Cosby, G. Falzon, M. Trotter, J. Stanley, K. Powell, D. Schneider, D. Lamb

54. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine Vision

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen  concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

55. In-field Plant Phenotyping Using Multi-view Reconstruction: an Investigation in Eggplant

Rapid methods for plant phenotyping are a growing need in agricultural research to help accelerate improvements in crop performance in order to facilitate more efficient utilization of plant genome sequences and the corresponding advancements in associated methods of genetic improvement. Manual plant phenotyping is time-consuming, laborious, frequently subjective, and often destructive. There is a need for building field-deployable systems with advanced sensors that have both high-speed and high-performance... T. Nguyen, D. Slaughter, B. Townsley, L. Carriedo, J. Maloof, N. Sinha

56. Spectral Vegetation Indices to Quantify In-field Soil Moisture Variability

Agriculture is the largest consumer of water globally. As pressure on available water resources increases, the need to exploit technology in order to produce more food with less water becomes crucial. The technological hardware requisite for precise water delivery methods such as variable rate irrigation is commercially available. Despite that, techniques to formulate a timely, accurate prescription for those systems are inadequate. Spectral vegetation indices, especially Normalized Difference... J. Siegfried, R. Khosla, L. Longchamps

57. Detecting Nitrogen Variability at Early Growth Stages of Wheat by Active Fluorescence and NDVI

Low efficiency in the use of nitrogen fertilizer, has been reported around the world which often times result in high production costs and environmental damage. Today, unmanned aerial vehicles (UAV) cameras are being used to obtain conditions of crops, and can cover large areas in a short time. The objectives of this study were (i) to investigate N-variability in wheat at early growth stages using induced fluorescence indices, NDVI measured by active sensor and NDVI obtained by digital imagery;... E. Patto pacheco, J. Liu, L. Longchamps, R. Khosla

58. Winter Wheat Genotype Effect on Canopy Reflectance: Implications for Using NDVI for In-season Nitrogen Topdressing Recommendations

Active optical sensors (AOSs) measure crop reflectance at specific wavelengths and calculate vegetation indices (VIs) that are used to prescribe variable N fertilization. Visual observations of winter wheat (Triticum aestivum L.) plant greenness and density suggest that VI values may be genotype specific. Some sensor systems use correction coefficients to eliminate the effect of genotype on VI values. This study was conducted to assess the effects of winter wheat cultivars and growing conditions... O.S. Walsh, S.M. Samborski, M. Stępień, D. Gozdowski, D.W. Lamb, E.S. gacek, T. Drzazga

59. Comparing Adapt-N to Static N Recommendation Approaches for US Maize Production

Large temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses.  Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools,... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune

60. 'Spatial Discontinuity Analysis' a Novel Geostatistical Algorithm for On-farm Experimentation

Traditional agronomic experimentation is restricted to small plots. Under appropriate experimental designs the effects of uncontrolled environmental variables are minimized and the measured responses (e.g. in yields) are compared to controllable inputs (seed, tillage, fertilizer, pesticides) using well-trusted design-based statistical methods. However, the implementation of such experiments can be complex and the application, management, and harvesting of treated areas might have to... S. Rudolph, B.P. Marchant, V. Gillingham, D. Kindred, R. Sylvester-bradley

61. Proximal Hyperspectral Sensing in Plant Breeding

The use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug

62. Using the Adapt-N Model to Inform Policies Promoting the Sustainability of US Maize Production

Maize (Zea mays L.) production accounts for the largest share of crop land area in the U.S. It is the largest consumer of nitrogen (N) fertilizers but has low N Recovery Efficiency (NRE, the proportion of applied N taken up by the crop). This has resulted in well-documented environmental problems and social costs associated with high reactive N losses associated with maize production. There is a potential to reduce these costs through precision management, i.e., better application timing, use... S. Sela, H. Van-es, E. Mclellan, J. Melkonian, R. Marjerison , K. Constas

63. Non-destructive Plant Phenotyping Using a Mobile Hyperspectral System to Assist Breeding Research: First Results

Hybrid plants feature a stronger vigor, an increased yield and a better environmental adaptability than their parents, also known as heterosis effect. Heterosis of winter oilseed rape is not yet fully understood and conclusions on hybrid performance can only be drawn from laborious test crossings. Large scale field phenotyping may alleviate this process in plant breeding. The aim of this study was to test a low-cost mobile ground-based hyperspectral system for breeding research to easily... H. Gerighausen, H. Lilienthal, E. Schnug

64. First Experiences with the European Remote Sensing Satellites Sentinel-1A/ -2A for Agricultural Research

The Copernicus program headed by the European Commission (EC) in partnership with the European Space Agency (ESA) will launch up to twelve satellites, the so called “Sentinels” for earth and environmental observations until 2020. Within this satellite fleet, the Sentinel-1 (microwave) and Sentinal-2 (optical) satellites deliver valuable information on agricultural crops. Due to their high temporal (5 to 6 days repeating time) and spatial (10 to 20 m) resolutions a continuous monitoring... H. Lilienthal, H. Gerighausen, E. Schnug

65. Potential Improvement in Rice Nitrogen Status Monitoring Using Rapideye and Worldview-2 Satellite Remote Sensing

For in-season site-specific nitrogen (N) management of rice to be successful, it is crucially important to diagnose rice N status efficiently across large area in a timely fashion. Satellite remote sensing provides a promising technology for crop growth monitoring and precision management over large areas. The FORMOSAT-2 satellite remote sensing imageries with 4 wavebands have been used to estimate rice N status. The objective of this study was to evaluate the potential of using high spatial resolution... S. Huang, Y. Miao, F. Yuan, M.L. Gnyp, Y. Yao, Q. Cao, V. Lenz-wiedemann, G. Bareth

66. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with better... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

67. Climate Smart Precision Nitrogen Management

Climate Smart Agriculture (CSA) aims at improving farm productivity and profitability in a sustainable way while building resilience to climate change and mitigating the impacts of agriculture on greenhouse gas emissions. The idea behind this concept is that informed management decision can help achieve these goals. In that matter, Precision Agriculture goes hand-in-hand with CSA. The Colorado State University Laboratory of Precision Agriculture (CSU-PA) is conducting research on CSA practices... L. Longchamps, R. Khosla, R. Reich

68. Ear Deployed Accelerometer Behaviour Detection in Sheep

An animal’s behaviour can be a clear indicator of their physiological and physical state. Therefore as resting, eating, walking and ruminating are the predominant daily activities of ruminant animals, monitoring these behaviours could provide valuable information for management decisions and individual animal health status. Traditional animal monitoring methods have relied on human labor to visually observe animals. Accelerometer technology offers the possibility of remotely monitoring animal... J.D. Barwick, M. Trotter, D.W. Lamb, R. Dobos, M. Welch

69. 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

70. Spatial Variability and Correlations Between Soil Attributes and Productivity of Green Corn Crop

In Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphic... W.J. Souza, S.H. Benez, P.H. Nakazawa, A.J. Santana neto, L.C. Citon, V.S. Akune

71. Adjustment of Corn Population and Nitrogen Fertilization Based on Management Zones

The main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1),... R. Schwalbert, T.J. Carneiro amado, T. Horbe, G.M. Corassa, F.H. Gebert

72. Evaluation of a Sensor and Control Interface Module for Monitoring of Greenhouse Environment

Protected horticulture in greenhouses and plant factories has been increased in many countries due to the advantages of year-round production in controlled environment for improved productivity and quality. For protected horticulture, environmental conditions are monitored and controlled through wired and wireless devices. Various devices are used for monitoring and control of spatial and temporal variability in crop growth environmental conditions. Recently, various sensors and control devices,... N. Sung, S. Chung, Y. Kim, K. Han, J. Choi, J. Kim, Y. Cho, S. Jang

73. Use of the Active Sensor Optrx to Measure Canopy Changes to Evaluate Foliar Treatments and to Identify Soil Quality in Table Grape

Table Grape (Vitis vinifera L.) is the main exporting horticultural crop in Chile, with the country being one of the top exporters at the world level. Commonly, grape producers perform trials of different commercial products which are not evaluated in an objective way. On the other hand they do not have the tools to easily identify areas within the field that may have some limiting factor. The use of active ground sensors that pass under the canopy several times during the season may... R.A. Ortega, M.M. Martinez, H.P. Poblete

74. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in Corn

Remotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia

75. A Content Review of Precision Agriculture Courses Across the US

Knowledge of what precision agriculture (PA) content is currently taught across the United States will help build a better understanding for what PA instructors should incorporate into their classes in the future. The University of Missouri partnered with several universities throughout the nation on a USDA challenge grant. Precision Agriculture faculty from 24 colleges/universities from across the U.S. shared their PA content by sharing their syllabi from 43 different courses. The syllabi were... D. Skouby, L. Schumacher, M. Yost, N.R. Kitchen

76. 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

77. 25 Years Precision Agriculture in Germany - a Retrospective

It all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus

78. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case Study

While on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson

79. Using Pricise Gps/gis Based Barley Yield Maps to Predict Site-specific Phosphorus Requirements

Three fundamental stages and technologies as main parts of a precision farming project should be considered precisely. These are access to actual multi- dimensional variability detail or variable description on farms, creating a suitable variable-rate technology, and finally providing a decision support system. Some results of a long term practical research conducted by the author in Upon-Tyne Newcastle University of UK for reliable yield monitoring and mapping were utilised to prepare this paper. The... A. Sanaei

80. Developing Nitrogen Algorithms for Corn Production Using Optical Sensors

Remote sensing for nitrogen management in cereal crops has been an intensive research area due to environmental concerns and economic realities of today’s agronomic system. In the search for improved nitrogen rate decisions, what approach is most often taken and are those approaches justified through scientific investigation? The objective of this presentation is to educate decision makers on how these algorithms are developed and evaluate how well they work in the field on a small-plot... R.W. Mullen, S.B. Phillips, W.R. Raun, W.E. Thomason

81. Plant and N Impacts on Corn (Zea Mays) Growth: Whats Controlling Yield?

Studies were conducted in South Dakota to assess mechanisms of intraspecific competition between corn (Zea mays) plants. Treatments were two plant populations (74,500 and 149,000 plants ha-1), three levels of shade (0, 40, and 60%) on the low plant population, two water treatments (natural precipitation and natural + irrigation), and two N rates (0 and 228 kg N ha-1). In-season leaf chlorophyll content was measured. At harvest, grain and stover yields were quantified with grain 13C-discrimination... D.E. Clay, S.A. Clay, G. Reicks, D. Horvath

82. Mapping Surface Soil Properties Using Terrain and Remotely Sensed Data in Arsanjan Plain, Southern Iran

Sustainable land management and land use planning require reliable information about the spatial distribution of the physical and chemical soil properties affecting both landscape processes and services. Spatial prediction with the presence of spatially dense ancillary variables has attracted research in pedometrics. The main objective of this research is to enhance prediction of soil properties such electrical conductivity (ECe), exchangeable sodium percentage (ESP), available phosphorus (P),... M. Baghernejad, M. Emadi

83. A New Approach for Quantitative Land Suitability Evaluation Using Geostatistics, Remote Sensing (Rs) and Geographic Information System (Gis)

The objective of this study was to incorporate geostatistics, remote sensing and geographic information system methods due to improving the quantitative land suitability assessment in Arsanjan plain, southern Iran. The primary data was collected from 85 soil samples from tree depths (0­30, 30­60 and 60­90 cm) and the secondary information from remotely sensed data “LISS­III receiver from IRS­P6 satellite”. In order to identify the spatial dependence of soil important... M. Baghernejad, M. Emadi

84. Site-specific Irrigation of Peanuts on a Coastal Plain Field

Irrigator-Pro is an expert system that prescribes irrigation for corn (Zea mays L.), cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea). We conducted an experiment in 2007 to evaluate Irrigator-Pro as a tool for variable rate irrigation of peanut using a site-specific center pivot irrigation system. Treatments were irrigation of whole plots based on the expert system, irrigation of individual soils within plots based on the expert system, irrigation of individual...

85. Soil Moisture, Organic Matter and Potassium Influences on Eca Measurement

Spatial variability of soil physical and chemical properties is a fundamental element of site-specific soil and crop management. Since its early implementation in agriculture as a method of measuring soil salinity, the acceptance of Apparent Electrical Conductivity (ECa) in agriculture has been popular as a method of determining the spatial variability of soil physical and chemical properties that influence the ECa estimates. It was the objective of this study to examine the spatial-temporal stability... R.R. Struthers, C.J. Johannsen, D.K. Morris

86. Using Unmanned Aerial Vehicle and Active-Optical Sensor to Monitor Growth Indices and Nitrogen Nutrition of Winter Wheat

Using unmanned aerial vehicle (UAV) remote sensing monitoring system can rapidly and cost-effectively provide crop canopy information for growth diagnosis and precision fertilizer regulation. RapidScan CS-45 (Holland, Lincoln, NE, USA) is a portable active-optical sensor designed for timely, non-destructive obtaining plant canopy information without being affected by weather condition. UAV equipped with RapidScan, is of great significant for rapidly monitoring crop growth and nitrogen (N) status.... X. Liu, Q. Cao, Y. Tian, Y. Zhu, Z. Zhang, W. Cao

87. 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

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

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

89. Introducing Precision Ag Tools to Over-100 Year Old Historical Experiment

The historic Knorr-Holden experimental site near Scottsbluff, Nebraska, US, established in 1912 is the oldest irrigated maize plot in North America. Over years, the treatment has been revised a few times to reflect and address contemporary practices. The N fertilization is found to be capable of restoring most of production capacity of the soil. After a full century of the experiment, in 2014, N treatments were revised again. Now, the experiment is a split-plot randomized complete block design... B. Maharjan

90. Frameworks for Variable Rate Application of Manure

Worldwide, nitrogen (N) and phosphorus (P) losses from agriculture are main contributors to eutrophication of water bodies so that forceful agro-technical measures are required to reduce their diffuse discharge to the environment. With view to worldwide finite mineral rock phosphates efficient standards are required to close the agricultural P cycle. In intensive agricultural livestock production manure is often treated as a waste problem rather than an organic fertilizer and source of nutrients.... H. Lilienthal, S.H. Haneklaus, E. Schnug

91. Rapid Identification of Mulberry Leaf Pests Based on Near Infrared Hyperspectral Imaging

As one of the most common mulberry pests, Diaphania pyloalis Walker (Lepidoptera: Pyralididae) has occurred and damaged in the main sericulture areas of China. Naked eye observation, the most dominating method identifying the damage of Diaphania pyloalis, is time-wasting and labor consuming. In order to improve the identification and diagnosis efficiency and avoid the massive outbreak of Diaphania pyloalis, near infrared (NIR) hyperspectral imaging technology combined with partial least discriminant... L. Yang, L. Huang, L. Meng, J. Wang, D. Wu, X. Fu, S. Li

92. Agricultural Remote Sensing Information for Farmers in Germany

The European Copernicus program delivers optical and radar satellite imagery at a high temporal frequency and at a ground resolution of 10m worldwide with an open data policy. Since July 2017 the satellite constellation of the Sentinel-1 and -2 satellites is fully operational, allowing e.g. coverage of Germany every 1-2 days by radar and every 2-3 days with optical sensors. This huge data source contains a variety of valuable input information for farmers to monitor the in-field variability and... H. Lilienthal, H. Gerighausen, E. Schnug

93. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy Cows

The objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger

94. Optimum Spatial Resolution for Precision Weed Management

The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves

95. Evaluation of the Ear-Tag Sensor System SMARTBOW for Detecting Estrus Events in Indoor Housed Dairy Cows

Livestock farming technologies have a tremendous potential to improve and support farmers in herd management decisions, in particular in reproductive management. Nowadays, estrus detection in cows is challenging and many detection tools are available. The company Smartbow (Weibern, Austria) developed a novel ear-tag sensor, which consists of a 3D-accelerometer that records head and ear movements of cows as basis for algorithm development and further analyses. Estrus detection by the SMARTBOW system... V. Schweinzer, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger

96. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

97. 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

98. Monitoring Potassium Levels in Peat-Grown Pineapple Using Selected Spectral Ratios

In this study, we assessed the biophysical changes within pineapple (var. MD2) in response to different potassium (K) rates using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430 nm and 680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e.... S.K. Balasundram, Y. Chong, A. Mohd hanif

99. Spatial Variability of Optimized Herbicide Mixtures and Dosages

Driven by 25 years of Danish, political 'pesticide action plans', aiming at reducing the use of pesticides, a Danish Decision Support System (DSS) for Integrated Weed Management (IWM) has been constructed. This online tool, called ‘IPMwise’ is now in its 4th generation. It integrates the 8 general IPM-principles as defined by the EU. In Denmark, this DSS includes 30 crops, 105 weeds and full assortments of herbicides. Due to generic qualities in both the integrated... P. Rydahl, R.N. Jorgensen, M. Dyrmann, N. Jensen, M.D. Sorensen, O.M. Bojer, P. Andersen

100. Akkerweb: A Platform for Precision Farming Data, Science, and Practice

The concept of precision farming (PF) was formulated about 40 years ago and the scientific knowledge for some applications of PF in The Netherlands has been available for almost 20 years. Also, in many cases equipment is available to implement PF in practice. In spite of all this PF uptake is still limited. An important reason for the limited uptake of PF is in the challenges that must be overcome to let data flow from sensors to data storage, to combine data sources and process them into recommendations,... F.K. Van evert, T. Been, J.A. Booij, C. Kempenaar, G.J. Kessel, L.P. Molendijk

101. Using a UAV-Based Active Canopy Sensor to Estimate Rice Nitrogen Status

Active canopy sensors have been widely used in the studies of crop nitrogen (N) estimation as its suitability for different environmental conditions. Unmanned aerial vehicle (UAV) is a low-cost remote sensing platform for its great flexibility compared to traditional ways of remote sensing. UAV-based active canopy sensor is expected to take the advantages of both sides. The objective of this study is to determine whether UAV-based active canopy sensor has potential for monitoring rice N status,... S. Li, Q. Cao, X. Liu, Y. Tian, Y. Zhu

102. Variability Analysis of Temperature and Humidity for Control Optimization of a Hybrid Dehumidifier with a Heating Module for Greenhouses

Protected horticulture using greenhouses and also recently plant factories is becoming more popular, especially for high-value crops such as paprika, tomato, strawberry, due to year-round production of high yield and better quality crops under controlled environment. Temperature and humidity are most important ambient environmental factors for not only optimum crop growth but also disease control. This study was conducted to analyze vertical and spatial variability of temperature and humidity... Y. Seo, W. Lee, Y. Kim, S. Chung, S. Jang, I. Bae

103. Creating Thematic Maps and Management Zones for Agriculture Fields

Thematic maps (TMs) are maps that represent not only the land but also a topic associated with it, and they aim to inform through graphic symbols where a specific geographical phenomenon occurs. Development of TMs is linked to data collection, analysis, interpretation, and representation of the information on a map, facilitating the identification of similarities, and enabling the visualization of spatial correlations. Important issues associated with the creation of TMs are: selection of the... E. Souza, K. Schenatto, C. Bazzi

104. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural Network

In this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros

105. Pest Detection on UAV Imagery Using a Deep Convolutional Neural Network

Presently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin

106. Variety Effects on Cotton Yield Monitor Calibration

While modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replications... E. Vories, A. Jones, G. Stevens, C. Meeks

107. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial Vehicle

Above-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas

108. Precision Nitrogen and Water Management for Enhancing Efficiency and Productivity in Irrigated Maize

Nitrogen and water continue to be the most limiting factors for profitable maize production in the western Great Plains. The objective of this research was to determine the most productive and efficient nitrogen and water management strategies for irrigated maize.  This study was conducted in 2016 at Colorado State University’s Agricultural Research Development and Educational Center, in Fort Collins, Colorado. The experiment included a completely randomized block design with five... E. Phillippi, R. Khosla, L. Longchamps, P. Turk

109. High Accuracy Path Tracking for Rice Drill Seeder in Uneven Paddy Fields

High accuracy track tracing is a challenging task in paddy fields due to uneven grounds as well as wet soil conditions, thus restricting the development of autonomous rice drill seeder in China. For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven mud paddy fields is introduced in this paper. Combining lateral deviation and heading angle... Y. Li, Y. Zhang, X. Liu, C. Liu

110. 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

111. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm Profitability

Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White

112. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

113. Observational Studies in Agriculture: Paradigm Shift Required

There is a knowledge gap in agriculture. For instance, there is no way to tell with precision what is the outcome of cutting N fertilizer by a quarter on important outcomes such as yield, net return, greenhouse gas emissions or groundwater pollution. Traditionally, the way to generate knowledge in agriculture has been to conduct research with the experimental method where experiments are conducted in a controlled environment with trials replicated in space and... L. Longchamps, B. Panneton, N. Tremblay

114. Calculating the Water Deficit of Apple Orchard by Means of Spatially Resolved Approach

In semi-humid climate, spatially resolved analysis of water deficit was carried out in apple orchard (Malus x domestica 'Pinova'). The meteorological data were recorded daily by a weather station. The apparent soil electrical conductivity (ECa) was measured at field capacity, and twenty soil samples in 30 cm were gathered for texture, bulk density, and gravimetric soil water content analyses. Furthermore, ten trees were defoliated in different ECa regions in order to estimate the leaf... N. Tsoulias, D. Paraforos, N. Brandes, S. Fountas, M. Zude-sasse

115. Fruit Fly Electronic Monitoring System

Insects are a constant threat to agriculture, especially the cultivation of various types of fruits such as apples, pears, guava, etc. In this sense, it is worth mentioning the Anastrepha genus flies (known as fruit fly), responsible for billionaire losses in the fruit growing sector around the world, due to the severity of their attack on orchards. In Brazil, this type of pests has been controlled in most product areas by spraying insecticides, which due to the need for prior knowledge regarding... C.L. Bazzi, F.V. Silva, L. Gebler, E.G. Souza, K. Schenatto, R. Sobjak, R.S. Dos santos, A.M. Hachisuca, F. Franz

116. Yield Mapping in Fruit Farming

Due to the importance of increasing the quantity and quality of world agricultural production, the use of technologies to assist in production processes is essential. Despite this, a timid adoption by precision agriculture (PA) technologies is verified by the Brazilian fruit producers, even though it is one of the segments that had been stood out in recent years in the country's economy. In the PA context, yield maps are rich sources of information, especially by species harvested through... C.L. Bazzi, M.R. Martins, L. Gebler, E.G. Souza, K. Schenatto, R. Sobjak, A. . Hachisuca, F. Franz

117. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

118. Economic Potential of IPMwise – a Generic Decision Support System for Integrated Weed Management in 4 Countries

Reducing use and dependency on pesticides in Denmark has been driven by political action plans since the 1980ies, and a series of nationally funded accompanying R&D programs were completed in the period 1989-2006. One result of these programs was a decision support system (DSS) for integrated weed management. The 4th generation (2016) of the agro-biological models and IT-tools in this DSS, named IPMwise. The concept of IPMwise is to systematically exploit that: occurrence... P. Rydahl, O. Boejer, K. Torresen, J.M. Montull, A. Taberner, H. Bückmann, A. Verschwele

119. Survey of Pesticide Application Practices and Technologies in Georgia Agricultural Crops

Georgia is a leading producer of numerous crops including cotton, peanut, blueberries, pecans, bell peppers, cabbage, watermelons, and peaches in the United States. Pesticide applications are critical for the successful production of these crops. Pesticide regulations and application technologies are changing rapidly due to growing concerns around off-target movement and increased focus on improving the efficiency and efficacy of pesticide applications. In order to provide suitable recommendations and... S.S. Virk, E.P. Prostko

120. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

121. Predicting Secondary Soil Fertility Attributes Using XRF Sensor with Reduced Scanning Time in Samples with Different Moisture Content

To support future in situ/on-the-go applications using X-ray fluorescence (XRF) sensors for soil mapping, this study aimed at evaluating the XRF performance for predicting organic matter (OM), base saturation (V), and exchangeable (ex-) Mg, using a reduced analysis time (e.g., 4 s) in soil samples with different moisture contents. These attributes are considered secondary for XRF prediction because they do not present emission lines in the XRF spectrum. Ninety-nine soil samples... T.R. Tavares, J.P. Molin, T.R. Da silva , H.W. De carvalho

122. 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

123. Machine Learning Techniques for Early Identification of Nitrogen Variability in Maize

Characterizing and managing nutrient variability has been the focus of precision agriculture research for decades. Previous research has indicated that in-situ fluorescence sensor measurements can be used as a proxy for nitrogen (N) status in plants in greenhouse conditions employing static sensor measurements. Indeed, practitioners of precision N management require determination of in-season plant N status in real-time at field scale to enable the most efficient N fertilizer... D. Mandal, R.D. Siqueira, L. Longchamps, R. Khosla

124. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach Orchard

Canopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen

125. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

126. Comparison and Validation of Different Soil Survey Techniques to Support a Precision Agricultural System

The data need of precision agriculture has resulted in an intensive increase in the number of modern soil survey equipment and methods available for farmers and consultants. In many cases these survey methods cannot provide accurate information under the used environmental conditions. On a 36 hectare experimental field, several methods have been compared to identify the ones which can support the PA system the best. The methods included contact and non contact soil scanning, yield mapping, high... V. Lang, G. Tóth, S. Csenki, D. Dafnaki

127. Use of Watering Hole Data As a Decision Support Tool for the Management of a Grazing Herd of Cattle

Establish grazing practices would improve the welfare of the animals, allowing them to express more natural behaviours. However, free-range reduces the ability to monitor the animals, thus increase the time needed to intervene in the event of a health problem. To ease the adoption of grazing, farmer would benefit from autonomously collected indicators at pasture that identify abnormal behaviours possibly related to a health problem in a bovine. These indicators must be individualised and collected... J. Plum, B. Quoitin, I. Dufrasne, S. Mahmoudi, F. Lebeau

128. 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

129. Enhancing NY State On-farm Experimentation with Digital Agronomy

Agriculture is putting pressure on the ecosystems and practices need to evolve towards a more sustainable way of producing food. Industrial agriculture has imposed a unique production model on the ecosystems while it is now understood that it is more sustainable to adapt the production model to the ecosystem. This involves adapting existing solutions to the local agricultural context and developing new solutions that are best suited to the local ecosystem. Farmers are doing this by conducting... L. Longchamps

130. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

131. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV Imagery

Goss Wilt has become a common disease in corn fields in North Dakota.  It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew

132. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield Estimators

Prediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that most... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh

133. Management Zone-specific N Mineralization Rate Estimation in Unamended Soil

Since nitrogen (N) mineralization from soil organic matter is governed by basic soil properties (soil organic matter content, pH, soil texture, …) that are known to exhibit strong in-field spatial variability, N mineralization is also expected to exhibit significant spatial variability at field scale. An ideal and efficient N recommendation for precision fertilization should therefore account for potential soil mineralizable N considering this spatial variability. Therefore, this study... F.Y. Ruma, M.A. Munnaf, S. De neve, A.M. Mouazen

134. Impact of Cover Crop and Soil Apparent Electrical Conductivity on Cotton Development and Yield

Cotton is one of the major crops in the New Madrid Seismic Zone (NMSZ) of the U.S. Lower Mississippi River Valley region. Because cotton production doesn’t leave a lot of crop residue in the field, low soil organic matter levels are common. While the benefits of crop rotation are well known, cotton is often grown year after year in the same fields for economic reasons. Soils in the region are generally quite variable, with areas of very high sand content. Winter cover crops and reduced tillage... E. Vories, K. Veum, K. Sudduth

135. Agriculture Machine Guidance Systems: Performance Analysis of Professional GNSS Receivers

GNSS (Global Navigation Satellite Systems) plays nowadays a major role in different civilian activities and is a key technology enabling innovation in different market sectors. For instance, GNSS-enabled solutions are widespread within the Precision Agriculture and, among them, applications in the field of machinery guidance are commonly employed to optimize typical agriculture practices. The scope of this paper is to present the outcomes of the agriculture testing campaign performed,... J. Capolicchio, D. Mennuti, I. Milani, M. Fortunato, R. Petix, J. Reyes gonzalez, M. Sunkevic

136. Enhancing PA Adoption Through Value Connections

Despite an increase in breadth of precision agriculture over time, and the attendant elements of digital agriculture that either support PA or integrates the outputs of PA, the pace of adoption of digital agriculture in our farming systems remains slow. In assessing impediments to adoption of digital agriculture, much work to date has focused on the value proposition as considered by individual producers or value chain actors.  At this level, adoption remains constrained by perceptions of... D.W. Lamb, M.T. Schaefer

137. Multi-sensor Imagery Fusion for Pixel-by-pixel Water Stress Mapping

Evaluating water stress in agricultural fields is fundamental in irrigation decision-making, especially mapping the in-field water stress variability as it allows real-time detection of system failures or avoiding yield loss in cases of unplanned water stress. Water stress mapping by remote sensing imagery is commonly associated with the thermal or the short-wave-infra-red (SWIR) bands. However, integration of multi-sensors imagery such as radar imagery or sensors with only visible and near-infra-red... O. Beeri, R. Pelta, Z. Sade, T. Shilo

138. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter Wheat

Optimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequently... D. Ghimire