Proceedings

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Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Education and Training in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Weed Management
Remote Sensing Applications in Precision Agriculture
Demonstration
Spatial Variability in Crop, Soil and Natural Resources
Farm Animals Health and Welfare Monitoring
Drainage Optimization and Variable Rate Irrigation
Meeting
Precision Nutrient Management
Precision Conservation and Carbon Management
Sensor Application in Managing In-season Crop Variability
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Authors
Aasen, H
Abbas, F
Abdollahi, J.M
Adamchuk, V.I
Adamchuk, V.I
Adamchuk, V.I
Aduramigba-Modupe, V
Ahmad, H.N
Al-Gaadi, K.A
Alchanatis, V
Alomran, A.M
Alsheri, S.A
Alwabel, M.I
Amaral, L.R
Amaral, L.R
Amaral, L.R
Amaral, L.R
Andersson, K
Arzani, H.P
Ascough II, J.C
Astillo, P
Azimi, M.S
Bajwa, S
Bajwa, S
Balakrishnan, P
Balakrishnan, P
Balasundram, S.K
Balboa, G
Balboa, G
Balboa, G
Balkcom, K
Baresel, P
Baret, F
Bareth, G
Bareth, G
Bareth, G
Bastos, A.H
Bazzi, C.L
Bean, G
Behrendt, K
Beitz, T
Belford, R
Belmont, K
Ben Abdallah, F
Beneduzzi, H.M
Benites, V.D
Benjamin, M
Bennett, S
Bereuter, A
Bernardi, A.C
Berti, M
Berzins, R
Betzek, N.M
Bierman, D
Blackmer, T.M
Bodson, B
Bolten, A
Bolton, C
Borhani, M.M
Borůvka, L
Bosse, D
Bourouah, M
Boyer, W
Boyko, Y.I
Brand, H
Brasco, T
Bruce, A.E
Brungardt, J.J
Buffet, D
Büchele, D
Camberato, J
Cambouris, A
Canal Filho, R
Canata, T.F
Cao, Q
Cardoso, G.M
Carneiro Amado, T.J
Carter, P
Castrignanò, A
Castro, S.G
Chang, Y.K
Charvat, K
Chau, M
Chavan, H
Cheema, S.J
Chen, L
Chen, Y
Chen, Y
Cho, W
Cho, Y
Chok, S.E
Chudy, T
Chung, S
Ciampitti, I
Ciampitti, I
Cisneros, M
Claire, G
Colaço, A.F
Colaço, A.F
Connor, J
Constas, K
Corá, J
Corassa, G.M
Cox, M
Craker, B.E
Cui, B
Cushnahan, T
D.C, H
D.C, H
Da Silva, E.R
Daroub, S.H
De Oliveira Moreira, F
Defourny, P
Delgado, J.A
Demattê, J.M
Denton, A.M
Denton, A.M
Destain, M
Diaz, O.A
Dornbusch, T
Dosskey, M.G
Dr., N
Dr., N
Dr., S
Drzazga, T
Duarte de Val, M
Duft, D.G
Dworak, V
Dzinaj, T
EMİNOĞLU, B.M
Eitelwein, M.T
Elvir Flores, A
Erdle, K
Esau, T
Esau, T.J
Farahpour, M.D
Farooque, A.A
Farooque, A.A
Farooque, A.A
Farooque, A.A
Fassinou Hotegni, N
Ferguson, A
Ferguson, A
Ferguson, R.B
Ferguson, R.B
Ferguson, R.B
Fernandez, F.G
Ferraz, M.N
Fiorio, P.R
Fontenelli, J.V
Francis, D
Franco, H.C
Franco, H.C
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, J
Friell, J
Frimpong, K.A
Frimpong, K.A
Frizzel, L
Frotscher, K.J
Fulton, J.P
Fulton, J.P
Gacek, E.S
Gamble, A
Gan, H
Gan, H
Garcia, A.H
Gavioli, A
Ge, Y
Gebbers, R
Gebert, F.H
George, D
Gerighausen, H
Gerighausen, H
Gholizadeh, A
Gholizadeh, A
Gianello, E
Gil, E
Gnyp, M.L
Gnyp, M.L
Gnyp, M.L
Goffart, J
Goffart, J
Goffart, J
Gonzalez, J
Goorahoo, D
Gornushkin, I
Gowda, H.H
Gozdowski, D
Gozdowski, D
Grafton, M.C
Grafton, M.C
Green, S
Greene, J
Grewal, K
Griffin, T
Griffin, T
Griffin, T
Gritten, F
Groulx, D
Guangwei, W
Gunther, D
Gupta, M
Gupta, S
Gutiérrez, V
Gérard, B
Hackl, H
Hammond, K
Han, Y.J
Hansen, N
Hansen, N
Harper, J
Heggemann, T
Heil, K
Hejl, R
Hendrickson, L
Hopkins, B
Hopkins, B
Horbe, T
Howatt, K
Huang, S
Huang, S
Huang, W
Huang, Y
Hunt, E
Inamassu, R.Y
Ingram, B
Irmak, S
Irwin, M.E
Isakeit, T
Islam, M
Jackson, C
Jansen, M
Jasper, J
Jasper, J
Jensen, R
Jensen, R
Jiang, J
Jiang, R
Jianjun, D
Jin, V
Johnson, R.M
KODAIRA, M
Kaboli, S.D
Kaiser, D
Kanannavar, P
Kanannavar, P
Kang, C
Kepka, M
Kereszturi, G
Kerry, R
Kerry, R
Kersebaum, C
Khalilian, A
Khan, F
Khan, F.S
Khan, F.S
Khosla, R
Khosla, R
Khosla, R
Kim, D
Kim, H
Kinder, T
Kipp, S
Kirkpatrick, T
Kitchen, N
Kitchen, N.R
Kizer, E
Klose, R
Ko-Madden, C
Kombali, G
Kumar R, M
Kumar R, M
Kumke, M
Kyveryga, P.M
Kyveryga, P.M
L, R.N
LI, Y
Laacouri, A
Laboski, C
Lacerda, L
Lamb, D.W
Lamb, D.W
Langovskis, D
Larbi, P.A
Laurent, P
Lavagnino, M
Le Roux, M
Lee, W
Leemans, V
Leenen, M
Lena, B.P
Lenz-Wiedemann, V
Leonard, A
Leroux, G.D
Leszczyńska, E
Lianqing, Z
Lilienthal, H
Lilienthal, H
Lilienthal, H
Liping, C
Liu, J
Liu, Z
Longchamps, L
Longchamps, L
Longchamps, L
Longchamps, L
Longchamps, L
Lopez Lozano, R
Lu, Y
Luck, J.D
Lund, E
Lund, T
Ma, K
Madani, A
Madani, A
Magalhaes, P.S
Magalhaes, P.S
Magalhães, P.G
Magalhães, P.S
Maharlooei, M
Maharlooei, M
Mahjoub, O.A
Mahns, B
Mailwald, M
Maiwald, M
Maja, J
Maja, J.M
Makkar, M.S
Mandel, R
Manfield, A
Mangus, D.L
Manon, M
Marine, L
Marjerison, R
Marlier, G
Marshall, J
Martello, M
Martinsson, J
Masnello, J.C
Matocha, C
Maxton, C
McClintick-Chess, J
McEntee, P
McGary, S.D
McIntyre, J
McLellan, E
McVeagh, P.J
McVeagh, P.J
Melkonian, J
Mercatoris, B
Mhlongo, N
Miao, Y
Miao, Y
Miao, Y
Michels, M
Mijatovic, B
Mijatovic, B
Miles, R.J
Mirdavodi, H.M
Mireei, S.A
Mistele, B
Mistele, B
Mistele, B
Mistele, B
Mizgirev, A
Modaihsh, A.S
Mohd Soom, M
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Monfort, S
Morata, G
Morlin, F
Morris, D
Mosmen, E.W
Mostafa, F
Mouazen, A.M
Mouazen, D
Moulton, H
Mueller, T
Mueller, T
Mueller, T
Mueller, T
Mueller, T
Mulla, D
Musil, M
Nadagouda, D
Nafziger, E
Naima, B
Nawar, S.M
Nichols, R.L
Noorasma, S
Nowatzki, J
Nowatzki, J
Nowatzki, J.F
OOMORI, T
Odvody, G.N
Oliveira, V
Olivier, G
Ortega, R
Ortega, R.A
Ortiz, B.V
Ortiz, B.V
Ortiz, B.V
Ortiz-Monasterio, I
Ostermann, M
Ozmen, S
PATIL, B
Panitzki, M
Panneton, B
Panneton, B
Pantoja, J.L
Patil, M
Patil, M
Patil, M.B
Patil, V.C
Patto Pacheco, E
Paulus, S
Payero, J.O
Pearson, R
Pennington, D
Percival, D
Percival, D.C
Piikki, K
Pimstein, A
Pitla, S.K
Pitrat, T
Portz, G
Portz, G
Prabhudeva, D
Prasad, R
Prasad, V
Prasad, V
Preiner, M
Pritsolas, J
Privette, C.V
Pujari, B
Pujari, B
Pullanagari, R.R
Puntel, L.A
Pätzold, S
Qiao, X
Qiu, Z
Rabello, L.M
Ransom, C
Reddy, K
Reddy, K.A
Reeg, P.R
Reusch, S
Riebe, D
Rienzi, E
Rienzi, E
Rienzi, E
Roberts, D
Rodrigues Júnior, F.H
Rodrigues Jr., F.A
Rodrigues, M
Rodrigues, M
Roger, T
Rojo, F
Rondon, S.I
Ruckelshausen, A
Rudnick, D
Rühlmann, J
Rühlmann, M
Sébastien, D
Söderström, M
SEYHAN, G.T
SITI NOOR ALIAH, B
Saberioon, M
Saberioon, M
Saleem, S.R
Samborski, S.M
Samborski, S.M
Sampson, T
Sanches, G
Sanches, G.M
Sanches, G.M
Sawyer, J
Schacht, R
Scharf, P
Scharf, P
Scheithauer, H
Schenatto, K
Schill, S
Schmer, M
Schmid, T
Schmidhalter, U
Schmidhalter, U
Schmidhalter, U
Schmidhalter, U
Schneider, D
Schneider, D.A
Schnug, E
Schnug, E
Schnug, E
Schulthess, U
Schumann, A
Schumann, A.W
Schumann, A.W
Schwalbert, R
Seepersad, G
Seepersad, S
Sela, S
Shanahan, J
Shannon, D.K
Shanwad, U
Sharda, A
Sharda, A
Sharma, A
Sharma, L
Sharma, V
Sharry, R
Shaver, T
Shearer, S.A
Shi, Y
Shibusawa, S
Shibusawa, S
Shirzadi, A
Shirzadi, A
Shumate, S
Siegfried, J
Sikora, F
Silva, A.E
Silva, M.J
Simard, M
Simard, M
Sivarajan, S
Sivarajan, S
Slaeem, S
Smith, L
Son, J
Song, X
Songchao, C
Souza, E.G
Stadig, H
Stanley, J.N
Stansell, J
Stenberg, M
Straw, C
Stępień, M
Stępień, M
Sudduth, K
Sudduth, K.A
Sudduth, K.A
Sumpf, B
Swoboda, K
Söderström, M
T, S
T, S
TALEBPOUR, B
Tahir, M
Theriault, R
Theriault, R
Thimmegowda, M
Thomasson, J.A
Thompson, C
Thomson, S.J
Tilly, N
Tisseyre, B
Toledo, F.H
Torino, M.S
Tremblay, N
Trevisan, R.G
Trevisan, R.G
Trotter, M
Trotter, M
Turner, I
Turner, R.W
TÜRKER, U
Upadhyaya, S
Upadhyaya, S
Upadhyaya, S.K
Valcke, R
Van Den Wyngaert, L
Van Donk, S
Van Langevelde, F
Varela, S
Varela, S
Vargas, M.R
Veum, K
Viator, R.P
Wagner, P
Waine, D
Waits, M
Wallor, E
Walsh, O.S
Walsh, O.S
Walsh, O.S
Wang, N
Wang, Y
Ward, N
Watkins, E
Weiqiang, F
Welch, M
Welp, G
Weltzien, C
Whattoff, D
White, M
White, M
Wienhold, B
Wijewardane, N
Wilde, P
Williams, E
Williams, J.D
Willis, L.A
Woolley, E
Xu, J.X
Yafei, Y
Yang, C
Yang, Q
Yang, Q
Yao, Y
Yao, Y
Yegul, U
Yoder, J
Young, J
Yuan, F
Yule, I.J
Yule, I.J
Yule, I.J
Yun, H
Yuncai, H
Zadrazil, F
Zaman, Q.U
Zaman, Q.U
Zaman, Q.U
Zamzow, M
Zamzow, M
Zarco-Tejada, P.J
Zhang, Q
Zhang, Y
Zhang, Y
Zhao, C
Zhao, T
Zhao, T
Zhijun, M
Zhou, S
Zillmann, E
Zoran, C
Zur, Y
de Boer, W.F
de Oliveira, R.P
de Solan, B
de knegt, H
giriyappa, M
giriyappa, M
hassanijalilian, O
van-Es, H
ÇOLAK, A
Topics
Precision Weed Management
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Precision Conservation and Carbon Management
Drainage Optimization and Variable Rate Irrigation
Remote Sensing Applications in Precision Agriculture
Education and Training in Precision Agriculture
Meeting
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Demonstration
Farm Animals Health and Welfare Monitoring
Type
Poster
Oral
Year
2010
2012
2016
2022
2024
Home » Topics » Results

Topics

Filter results158 paper(s) found.

1. Use of Corn Height to Improve the Relationship Between Active Optical Sensor Readings and Yield Estimates

Pre-season and early in-season loss of N continues to be a problem in corn. One method to improve nitrogen use efficiency is to fertilize based on in-season crop foliage sensors. The objective of this study was to evaluate two different ground-based, active-optical sensors and explore the use of corn height with sensor readings for improved relationship with corn yield. Two different ground-based active-optical sensors (GreenseekerTM ... L. Sharma, D.W. Franzen

2. Development of Ground Based Multi-source Crop Information Collection System.

Precision agriculture requires reliable technology to acquire accurate information on crop conditions. A ground-based integrated sensor and instrumentation system was developed to measure real-time crop conditions. The integration system included multispectral camera and N-sensor for real time Nitrogen application. The system was interfaced with a DGPS receiver to provide spatial coordinates for sensor readings. Before mounting of the sensors on modified paddy transplanter, different mounting... A. Sharma, M.S. Makkar, S. Gupta

3. Active Sensor Performance – Dependence to Measuring Height, Light Intensity and Device Temperature

For land use management, agriculture, and crop management spectral remote sensing is widely used. Ground-based sensing is particularly advantageous allowing to directly link on-site spectral information with agronomic algorithms. Sensors are nowadays most frequently used in site-specific oriented applications of fertilizers, but similarly site-specific applications of growth regulators, herbicides and pesticides become more often adopted. Generally little is known about the effects ... B. Mistele, U. Schmidhalter, S. Kipp

4. Estimation of Nitrogen of Rice in Different Growth Stages Using Tetracam Agriculture Digital Camera

Many methods are available to monitor nitrogen content of rice during various growth stages. However, this monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera (ADC) was used to acquire high spatial and temporal resolution in order to determine the status of nitrogen (N) and predict the grain yield of rice (Oriza sativa L.). In this study, 12 pots of rice with four different N treatments (0, ... A. Gholizadeh , M. Mohd soom , M. Saberioon

5. Comparison of Active and Passive Spectral Sensors in Discriminating Biomass Parameters and Nitrogen Status in Wheat Cultivars

Several sensor systems are available for ground-based remote sensing in crops. Vegetation indices of multiple active and passive sensors have seldom been compared in determining plant health. This study was aimed to compare active and passive sensing systems in terms of their ability to recognize agronomic parameters. One bi-directional passive radiometer (BDR) and three active sensors (Crop Circle, GreenSeeker, and an active flash sensor (AFS)) were tested for their ability to assess six des... B. Mistele, U. Schmidhalter, K. Erdle

6. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

7. Assembly of an Ultrasound Sensors System for Mapping of Sugar Cane Height

In Precision Agriculture, the use of sensors provides faster data collection on plant, soil, and climate, allowing collecting larger sample sets with better information quality. The objective of this study was the development of a system for plant height measurement in order to mapping of sugar cane crop, so that regions with plant growth variation and grow failures could be id... A.H. Garcia, F.H. Rodrigues júnior, A.H. Bastos, P.S. Magalhaes, M.J. Silva

8. In-Field Corn Stalk Location Using Rapid Line-Scan Technique

... Y. Shi, N. Wang

9. Model for Remote Estimation of Nitrogen Contents of Corn Leaf Using Hyper-Spectral Reflectance under Semi-Arid Condition.

Accuracy and precision of nitrogen estimation can be improved by hyperspectral remote sensing that lead... M. Tahir

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

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

11. Potential Indicators Based On Leaf Flavonoids Content for the Evaluation of Potato Crop Nitrogen Status

Nitrogen (N) fertilization strategies aim to limit environmental pollution by improving potato crop N use efficiency. Such strategies may use indicators for the assessment of in season crop N status (CNS). Leaf polyphenolics (flavonoids) content appears as a valuable indicator of CNS. Because of their absorption features ... J. Goffart, F. Ben abdallah

12. Measuring Sugarcane Height in Complement to Biomass Sensor for Nitrogen Management

Although extensive studied, nitrogen management remains a challenger for sugarcane growers, especially the nutrient spatial variability management, which demands the use of variable rate application. Canopy reflectance sensors are being studied, but it seems to saturate the sensor s... J.P. Molin, G. Portz, L.R. amaral

13. Optimum Sugarcane Growth Stage for Canopy Reflectance Sensor to Predict Biomass and Nitrogen Uptake

The recent technology of plant canopy reflectance sensors can provide the status of biomass and nitrogen nutrition of sugarcane spatially and in real time, but it is necessary to know the right moment to use this technology aiming the best predictions of the crop p... L.R. Amaral, J.P. Molin, J. Jasper, G. Portz

14. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation Indices

Application of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US r... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom

15. In-season Diagnosis of Rice Nitrogen Status Using an Active Canopy Sensor

... Y. Yao, Y. Miao, S. Huang, M. Gnyp, R. Khosla, R. Jiang, G. Bareth

16. A New Sensing System for Immediate and Direct Measurements of Soil Nitrate

In-season management of nitrogen is a critical component in the drive to increase the nitrogen use efficiency of commercial crop production. Increasing nitrogen use efficiency itself has become a prominent issue due to both economic and environmental/regulatory drivers over the last decade.   Solum, Inc (Mountain View, CA) has developed a new sensing technology to enable the immediate and direct measurement of soil nitrate. This allows rapid and economical so... M. Preiner

17. Local And Regional Soil Clay Mapping Using Gamma Ray Spectrometry

... M. Söderström

18. Impact Of Precision Leveling On Spatial Variability Of Moisture Conservation In Arid Zones Of Karnataka

... S. Upadhyaya, P. Balakrishnan, B. Pujari, M. Patil, P. Kanannavar

19. Laser Leveling Holds a Lot Of Promise in Water Conservation and Saving in Dry Zones (Drought Prone Areas) of Karnataka

... S. Upadhyaya, P. Balakrishnan, B. Pujari, M. Patil, P. Kanannavar

20. Long Term Effects of Irrigation with Sewage Effluent on Some Soil Properties

In the arid and semiarid regions, the use of treated sewage water increases as an alternative for non-renewable resources in irrigation. The objective of this research is to identify the effect of irrigation with sewage effluent and well water for lo... M.I. Alwabel, S.A. Alsheri, A.M. Alomran

21. Application of RS, GPS & GIS in a National Monitoring System for Accurate Range Assessment

Sustainable use of rangelands requires information on vegetation cover and its changes through time, condition trend and the effect of climate as well as management practices. The main objective of this research was showing variation of vegetation para... H.P. Arzani, M.S. Azimi, S.D. kaboli, H.M. mirdavodi, M.M. Borhani, J.M. Abdollahi, M.D. farahpour

22. 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

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

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

24. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China ... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

25. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

  ... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui

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

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

27. Spatial Econometric Approaches to Develop Site-Specific Nematode Management Strategies in Cotton Production

Root-knot nematode infestations tend to be spatially clustered within agricultural... Z. Liu, T. Griffin, T. Kirkpatrick, S. Monfort

28. Precision Tools to Evaluate Benefits of Tile Drainage in a Corn and Soybean Rotation in Iowa

... P.R. Reeg, T.M. Blackmer, P.M. Kyveryga

29. Analysis of Spatial Variability of Key Soil Attributes In North-Central Ukraine

As Ukrainian agricultural production undergoes major changes, a better understanding of the diversity of land resources is needed to optimize management.  Dealing with large fields (over 100 ha in size) with non-uniform growing conditions presents an opportunity for site-specific management of agricultural inputs. This publication describes our 2010 pilot study on the implementation of integrated mapping of apparent soil electrical conductivity and field topography to guide soil sampling... Y.I. Boyko, V.I. Adamchuk

30. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields

  One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild bl... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan

31. Spatial Variability of Sugarcane Yields in Relation to Soil Salinity in Louisiana

High soil salinity levels have been documented to negatively impact sugarcane yields.  Tests were conducted in commercial sugarcane fields in South Louisiana in 2009-2010 to determine if elevated soil salinity ... R.P. Viator, R.M. Johnson

32. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn

... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk

33. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields

Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve cr... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan

34. 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 sens... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

35. 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 moi... J.N. Stanley, D.A. Schneider, D.W. Lamb

36. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate Factors

Effective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability.  The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measure... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi

37. On-The-Go pH Sensor: An Evaluation in a Kentucky Field

A commercially available on-the-go soil pH sensor measures and maps subsurface soil pH at high spatial intensities across managed landscapes.  The overall purpose of this project was to evaluate the potential for this sensor to be used in agricultural fields. The specific goals were to determine and evaluate 1) the accuracy with which this instrument can be calibrated, 2) the geospatial structure of soil pH measure... T. Mueller, E. Gianello, B. Mijatovic, E. Rienzi, M. Rodrigues

38. Measurement of Systematic Errors in Crop Prediction

Precision agriculture typically attempts to answer grower questions using an increasingly more fine-grained analysis.  However, some entities, such as cooperatives, can have an interest in answers that are spatially course-grained, such as obtaining an estimate of the overall crop production within a season.  Errors in factors that most influence fine-grained predictions, such as soil quality, may have a smaller impact on overall yield forecasts since their effect is likely to ... A.M. Denton, E.W. Mosmen, J.X. Xu

39. A Scheme of Precision Carbon Farming for Paddy

Paddy soil used to have a low level of organic matters, generally below 3 %, because of its concerns of producing harmful materials to the crop gro... Y. li, M. kodaira, T. oomori, B. siti noor aliah, S. Shibusawa

40. Cloud Computing and Web 2.0 Mapping Technologies for Disseminating Land Use Planning Information

Open source software and cloud computing techniques could substantially improve the performance and reduce the cost of disseminating land-use planning information for the USDA-NRCS and other organizations. This is a major upgrade of our previously work (Hamilton,2009; Neelakantan et al., 2011). The purpose of this study is to develop a prototype cloud-based Web 2.0 mapping system for MLRA-121 which is primarily in Kentuck... T. Mueller

41. 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 pla... Z. Qiu, M.G. Dosskey

42. A New Version of the Nitrogen Trading Tool (NTT) To Assess Nitrogen Management across the USA

A recent study from the USDA Economic Research Service (September 2011) reported that about one-third of U.S. cropland was found to meet the requirements for ... J.A. Delgado, J.C. Ascough ii

43. Soil Organic Carbon Multivariate Predictions Based on Diffuse Spectral Reflectance: Impact of Soil Moisture

Spatial predictions of soil organic carbon (OC) developed with proximal and remotely sensed diffuse reflectance spectra are complicated by field soil moisture variation. Our objective was to determine how moisture impacted spectral reflectance and Walkley-Black OC predictions. Soil reflectance from the North American Proficiency Testing... T. Mueller, C. Matocha, F. Sikora, B. Mijatovic, E. Rienzi

44. Soil Salinity, Sand Encroachment and Erosion as Indicators of Land Degradation in Harad Center, Saudi Arabia

This study presents the main results of a thorough evaluation of land degradation in Saudi Arabia (Harad Centre). The study was carried out in 2006-2007 as part of a project aimed to study features and causes of land degradation in Saudi Arabia. The study area o... O.A. Mahjoub, A.S. Modaihsh

45. Cloud Computing, Web-Based GIS, Terrain Analysis, Data Fusion, and Multivariate Statistics for Precision Conservation in the 21st Century

... T. Mueller

46. Developing And Teaching A Site-specific Crop/soil Management Course

           Site-specific crop/soil management technologies have been available for over fifteen years. Consequently, there is a demand for classroom and laboratory education across a variety of agricultural disciplines in the University community. To meet this demand, a course was developed in 1998 to teach the basic concepts of site-specific crop/soil management. This class is designed as a upper level undergraduate and graduate class and generally has between 1... M. Cox, D. Roberts

47. Precision Agriculture Education Program In Nebraska

With the cost of agricultural inputs and the instability of commodity prices increasing, demand is growing for training in the essential skills needed to successfully implement site-specific crop management. This set of skills is uniquely interdisciplinary in nature. Thus, it is essential for potential users of precision agriculture to understand the basics of geodetic and electronic control equipment, principles of geographic information systems, fundamenta... V.I. Adamchuk, R.B. Ferguson

48. Interpretation Of Thinking Process In Farmer’s Decision

An idea of knowledge management is composed of (1) defining the four steps of recognition: data, information, knowledge and wisdom, (2) decision-make actions of evidence mining and context making, (3) system makeup of input and output on management. In simulating expert farmers’ practiced, five factors of farming system and eleven units of thinking were derived. The five factors are crop, field, techno... S. Shibusawa

49. Experiencs Of Extension Education Via Online Delivery Of Programming Related To Precision Agriculture Technologies

This paper will describe the content and experiences teaching an extension education course on precision agriculture technologies via online delivery. The course was developed to be delivered in 16 weeks meeting one time a week online. There was also a one-day face-to-face hands-on session focused around 4 lab type activities related to GPS guidance, diagnosis, and setup and maximizing the usefulness of precision agriculture technologies. This course focuses on agricultura... D.K. Shannon

50. Revisited: A Case Study Approach For Teaching And Applying Precision Agriculture

Current agricultural students understand and are excited about new technologies, but often do not understand how precision agriculture can be applied to farming operations. A case-study approach that requires students to develop precision agriculture management practices which includes selecting equipment and assessing the financial feasibility could help students understand and apply precision agriculture. This paper revisits a case-study approach to teaching precision agriculture and descri... J.D. Williams, S.D. Mcgary, M. Waits

51. Isobus Demonstrator And Working Environment For Agricultural Engineering Education

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

52. Farmer Perspectives Of Precision Agriculture In Western Australia

Many farmers in the Western Australian wheatbelt have successfully adopted guidance and yield mapping technologies. However they have so far avoided adopting variable rate technology (VRT).  While agronomists and farmers can determine the limiting factors to production, whether it is soil fertility, pH, plant available water capacity (PAWC) or others, they have less confidence in managing spatial variability. Although WA farmers understand the need to adopt these techniques they h... R. Mandel

53. Interest Of 3D Modeling For Lai Retrieval From Canopy Transmittance Measurements: The Cases Of Wheat And Vineyard

Remote sensing techniques are now widely used in agriculture, for cultivar screening as well as for decision making tools. Empirical methods relate directly the remote sensing measured values to crop characteristics. These methods are limited by the important amount of ground data necessary for their calibration. Their validity domain is generally not very well defined as well as the associated uncertainties. Conversely, radiative transfer models allow simulating a wide range of conditions, a... B. De solan, R. Lopez lozano, K. Ma, F. Baret, B. Tisseyre

54. Comparative Performance Of Different Remote Sensing (RS) And Geographic Information System (GIS) Techniques Of Wheat Area And Production Estimates

  The major wheat producing countries in the world are India, China, USA, France, Russia, Canada and Australia. Global demand for wheat is growing @ 1% per year. Crop growth and productivity are determined by a large number of factors such as genetic potential of crop cultivar, soil, weather and management variables, which vary significantly across time and space. Early prediction of crop yield is important for planning and taking various policy decisions. Many countries use th... V.C. Patil, K.A. Al-gaadi

55. SPOT5 Multispectral Data Potentialities To Monitor Potato Crop Nitrogen Status At Specific Field Scale

The many challenges facing European agriculture and farm of tomorrow are such that they increasingly require the setting up of Decision Support Systems (DSS) that favour integrated crop management at farm or regional level. A valuable DSS for management of split fertilizer N applications was developed in Belgium for potato crop. It combines total N recommendation based on field predictive balance-sheet method along with Crop Nitrogen Status (CNS) monitoring through hand-held chlorophyll meter... J. Goffart, A. Leonard, D. Buffet, P. Defourny, L. Van den wyngaert

56. A Comparison Of Spectral Reflectance And Laser-induced Cholorphyll Fluorescence Measurements To Detect Differences In Aerial Dry Weight And Nitrogen Update Of Wheat

       Chlorophyll fluorescence and spectral reflectance analysis are both powerful tools to study the spatial and temporal heterogeneity of plants` biomass and nitrogen status. Whereas reflectance techniques have intensively been tested for their use in precision fertilizer application, laser-induced chlorophyll fluorescence has been tested to a lesser degree, and there are hardly any... B. Mistele, U. Schmidhalter

57. Chlorophyll Fluorescence Approaches To Estimate The Vitality Of Plants

  Chlorophyll fluorescence is a now well-established technique for the analysis of photosynthesis in plants and algae. Fluorescence transients (Kautsky curves), exhibited by photosynthetic organisms under different conditions provide detail information about the structure, conformation and function of the photosynthetic apparatus, especially of photosystem II. The analysis of the so-called OJIP-curve and of the pulsed-aplitude-modulated fluorometry in conjunction with the satur... R. Valcke, D. Bierman

58. Evaluation Of The Multiplex® Fluorescence Sensor For The Assessment Of Corn Nitrogen Status

The Multiplex® is a new hand-held optical fluorescence sensor for non-destructive measurement of about 20 parameters descriptive of plant physiological status. The Multiplex is of potential value for in-season assessment of crop nitrogen status, but no evaluation has been released for that matter as of yet. An experiment was therefore conducted which consisted of four nitrogen fertilization treatments with 0, 20, 5... Y. Zhang, N. Tremblay

59. 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 he... L. Longchamps, B. Panneton, M. Simard, R. Theriault, T. Roger

60. 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. S... L. Longchamps, B. Panneton, G.D. Leroux, M. Simard, R. Theriault

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

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

62. Effect Of Precision Guided Cultivation On Weed Control In Wide Row Cropping Systems

Wide row cropping has been traditionally followed in summer crops but it is also becoming popular in winter crops such as chickpeas and lupins.  High precision guidance systems with 2 cm accuracy offer unique opportunities to cultivate closer to the row and increase weed control efficiency in wide row cropping systems. Two field experiments were conducted in chickpeas with a Real Time Kinematic Differential Global Positioning System (RTK-DGPS) controlled mechanical cultivation. Cultivati... M. Gupta, ,

63. Studies on Soil Spatial Variability and Its Impact on Cane Yield Under Precision Nutrient Management System

In present investigation an attempt was made to quantify the soil variability of 30 grids of 10 m x 10 m dimension at research farm of Nandi Sahakari Sakkare Karkhane (NSSK), Krishna Nagar, District. Bijapur. Each grid (10 m x 10 m) showed variation with available nitrogen as low as 140 kg ha-1 to as high as 245 kg/ha with a range of 105 kg/ha, phosphorus as low as 53 kg P2O5 ha-1 and as high as 89.3 kg P2O5 ha-1 wit... M. Kumar r, M. Kumar r, D. Nadagouda

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

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

65. 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 conditi... O.S. Walsh, S.M. Samborski, M. Stępień, D. Gozdowski, D.W. Lamb, E.S. gacek, T. Drzazga

66. On-Farm Evaluation of an Active Optical Sensor Performance for Variable Nitrogen Application in Winter Wheat

Winter wheat (Triticum aestivum L.) represents almost 50% of total cereal production in the European Union, accounting for approximately 25% of total mineral nitrogen (N) fertilizer applied to all crops. Currently, several active optical sensor (AOS) based systems for optimizing variable N fertilization are commercially available for a variety of crops, including wheat. To ensure successful adoption of these systems, definitive measurable benefits must be demonstrated. Nitrogen management str... O.S. Walsh, S.M. Samborski, D. Gozdowski, M. Stępień, E. Leszczyńska

67. UAV-based Crop Scouting for Precision Nutrient Management

Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of w... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda

68. Accuracy of Differential Rate Application Technology for Aerial Spreading of Granular Fertiliser Within New Zealand

Aerial topdressing of granular fertilizer is common practice on New Zealand hill country farms because of the challenging topography. Ravensdown Limited is a New Zealand fertilizer manufacturer, supplier and applicator, who are funding research and development of differential rate application from aircraft. The motivation for utilising this technology is to improve the accuracy of fertilizer application and fulfil the variable nutrient requirements of hill country farms.  The capability ... I.J. Yule, S.E. Chok, M.C. Grafton, M. White

69. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis

The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi

70. 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

71. Spatial Variability of Soil Nutrients and Precision Nutrient Management for Targeted Yield Levels of Groundnut (Arachis Hypogaea L.)

A field study was conducted during rabi / summer 2014-15 to know the spatial variability and precision nutrient management practices on targeted yield levels of groundnut. The experimental field has been delineated into 36 grids of 9 m x 9 m using geospatial technology. Soil samples from 0-15 cm were collected and analysed. Spatial variability exists for available nitrogen, phosphorous and potassium and they varied from 99 to 197 kg N, 12.1 to 64.0 kg P2O5 and 1... H. D.c, S. Dr., N. Dr., M. Giriyappa, S. T

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

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

73. Precision Nutrient Management Through Drip Irrigation in Aerobic Rice

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

74. Integrated Approach to Site-specific Soil Fertility Management

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

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

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

76. 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

77. Towards Precision Microbiology

In the recent years, the use of organic matter (OM) and microorganisms is increasing beyond organic agriculture, into conventional horticultural systems, in order to achieve high yields and quality through a more sustainable soil management. Thus, Integrated Nutrient Management (INM), that includes the use of diagnostic tools, high quality OM, microbial inoculants, highly-efficient fertilizer, and site-specific management in gaining space in intensive production systems. Precision m... V. Gutiérrez, R. Ortega

78. Selection and Utility of Uncooled Thermal Cameras for Spatial Crop Temperature Measurement Within Precision Agriculture

Since previous research used local, single-point measurements to indicate crop water stress, thermography is presented as a technique capable of measuring spatial temperatures supporting its use for monitoring crop water stress. This study investigated measurement accuracy of uncooled thermal cameras under strict environmental conditions, developed hardware and software to implement uncooled thermal cameras and quantified intrinsic properties that impact measurement accuracy and repeatability... D.L. Mangus, A. Sharda

79. 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 Differenc... J. Siegfried, R. Khosla, L. Longchamps

80. High Resolution Hyperspectral Imagery to Assess Wheat Grain Protein in a Farmer's Field

The agricultural research sector is working to develop new technologies and management knowledge to sustainably increase food productivity, to ensure global food security and decrease poverty. Wheat is one of the most important crops into this scenario, being among the three most important cereal commodities produced worldwide. Precision Agriculture (PA) and specially Remote Sensing (RS) technologies have become in the recent years more affordable which has improved the availability and flexi... F.A. Rodrigues jr., I. Ortiz-monasterio, P.J. Zarco-tejada, F.H. Toledo, U. Schulthess, B. Gérard

81. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)

Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson

82. High Resolution 3D Hyperspectral Digital Surface Models from Lightweight UAV Snapshot Cameras – Potentials for Precision Agriculture Applications

Precision agriculture applications need timely information about the plant status to apply the right management at the right place and the right time. Additionally, high-resolution field phenotyping can support crop breeding by providing reliable information for crop rating. Flexible remote sensing systems like unmanned aerial vehicles (UAVs) can gather high-resolution information when and where needed. When combined with specialized sensors they become powerful sensing systems. Hyp... H. Aasen

83. 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 i... E. Patto pacheco, J. Liu, L. Longchamps, R. Khosla

84. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted t... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

85. Measuring Pasture Mass and Quality Indices Over Time Using Proximal and Remote Sensors

Traditionally pasture has been measured or evaluated in terms of a dry matter yield estimate, which has no reference to other important quality factors. The work in this paper measures pasture growth rates on different slopes and aspects and pasture quality through nitrogen N% and metabolizable energy and ME concentration. It is known that permanent pasture species vary greatly in terms of quality and nutritional value through different stages of maturity. Pasture quality decreases as grass t... I.J. Yule, M.C. Grafton, L.A. Willis, P.J. Mcveagh

86. 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 monit... H. Lilienthal, H. Gerighausen, E. Schnug

87. Planet Labs' Monitoring Solution in Support of Precision Agriculture Practices

Satellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann

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

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

89. A Photogrammetry-based Image Registration Method for Multi-camera Systems

In precision agriculture, yield maps are important for farmers to make plans. Farmers will have a better management of the farm if early yield map can be created. In Florida, citrus is a very important agricultural product. To predict citrus production, fruit detection method has to be developed. Ideally, the earlier the prediction can be done the better management plan can be made. Thus, fruit detection before their mature stage is expected. This study aims to develop a thermal-visible camer... H. Gan, W. Lee, V. Alchanatis

90. 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 ... S. Huang, Y. Miao, F. Yuan, M.L. Gnyp, Y. Yao, Q. Cao, V. Lenz-wiedemann, G. Bareth

91. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in Scandinavia

CropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable ima... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki

92. Measuring Height of Sugarcane Plants Through LiDAR Technology

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

93. Window-based Regression Analysis of Field Data

High-resolution satellite and areal imagery enables multi-scale analysis that has previously been impossible.  We consider the task of localized linear regression and show that window-based techniques can return results at different length scales with very high efficiency.  The ability of inspecting multiple length scales is important for distinguishing factors that vary over different length scales.  For example, variations in fertilization are expected to occur on shorter len... A.M. Denton, H. Chavan, D.W. Franzen, J.F. Nowatzki

94. Hyperspectral Imaging to Measure Pasture Nutrient Concentration and Other Quality Parameters

Managing pasture nutrient requirements on large hill country sheep and beef properties based on information from soil sampling is expensive because of the time and labor involved. High levels of error are also expected as these properties are often greatly variable and it is therefore extremely difficult to sample intensively enough to capture this variation. Extensive sampling was also not considered viable as there was no effective means of spreading fertilizer with a variable rate capabili... I.J. Yule, R.R. Pullanagari, G. Kereszturi, M.E. Irwin, P.J. Mcveagh, T. Cushnahan, M. White

95. Creating Prescription Maps from Historical Imagery for Site-specific Management of Cotton Root Rot

Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is a severe plant disease that has affected cotton production for over a century. Recent research found that a commercial fungicide, Topguard (flutriafol), was able to control this disease. As a result, Topguard Terra Fungicide, a new and more concentrated formulation developed specifically for this market was registered in 2015, so cotton producers can use this product to control the disease. Cotton root rot only inf... C. Yang, G.N. Odvody, J.A. Thomasson, T. Isakeit, R.L. Nichols

96. Retrieving Crops' Quantitative Biophysical Parameters Through a Newly Developed Multispectral Sensor for UAV Platforms

Today’s intensive agricultural production needs to increase its efficiency in order to keep its profitability in the current market of decreasing prices on one hand, and to reduce the environmental impact on the other. Crop growers are starting to adopt side dressing nitrogen fertilization as part of their fertilization programs, for which they need accurate information about biomass development and nitrogen condition in the crop. This information is usually acquired through ground samp... A. Pimstein, Y. Zur, M. Le roux

97. Development of Sensor Reflection Indices To Predict Yield And Protein Content Based On In-Season N Status

Environmental and economic demands make it necessary for farmers to adopt   management systems that improve Nitrogen Use Efficiency. The premium paid to producers has made farmers striving for maximum grain protein levels because protein is a very important quality component of grains and an important attribute in the market place. The protein content of wheat grains approximately ranges from 8 to 20%. The optimization of nitrogen (N) fertilization is the object of intense research ... U. Yegul, B. Talebpour, U. TÜrker, B.M. EmİnoĞlu, G.T. Seyhan, A. Çolak

98. Intuitive Image Analysing on Plant Data - High Throughput Plant Analysis with Lemnatec Image Processing

For digital plant phenotyping huge amounts of 2D images are acquired. This is known as one part of the phenotyping bottleneck. This bottleneck can be addressed by well-educated plant analysts, huge experience and an adapted analysis software. Automated tools that only cover specific parts of this analysis pipeline are provided. During the last years this could be changed by the image processing toolbox of LemnaTec GmbH. An automated and intuitive tool for the automated analysis of huge amount... S. Paulus, T. Dornbusch, M. Jansen

99. In Season Estimation of Barley Biomass with Plant Height Derived by Terrestrial Laser Scanning

The monitoring of plant development during the growing season is a fundamental base for site-specific crop management. In this regard, the amount of plant biomass at a specific phenological stage is an important parameter to evaluate the actual crop status. Since biomass is directly only determinable with destructive sampling, methods of recording other plant parameters, such as crop height or density, which are suitable for reliable estimations are increasingly researched. Over the past two ... N. Tilly

100. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)

Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson

101. Assessing Soybean Injury from Dicamba Using RGB and CIR Images Acquired on Small UAVs

Dicamba is an herbicide used for postemegence control of several broadleaf weeds in corn, grain sorghum, small grains, and non-cropland. Currently, dicamba-tolerant (DT) soybean and cotton are under development, which provide new options to combat weeds resistant to glyphosate, the most widely used herbicide.  With the use of DT-trait cotton and soybean, off-target dicamba drift onto susceptible crops will become a concern. To relate soybean injury to different rates of dicamba applicati... Y. Huang, H. Brand, D. Pennington, K. Reddy, S.J. Thomson

102. Utilizing Space-based Technology for Cotton Irrigation Scheduling

Accurate soil moisture content measurements are vital to precision irrigation management. Electromagnetic sensors such as capacitance and time domain reflectometry have been widely used for measuring soil moisture content for decades. However, to estimate average soil moisture content over a large area, a number of ground-based in-situ sensors would need to be installed, which would be expensive and labor intensive. Remote sensing using the microwave spectrum (such as GPS signals) has been us... A. Khalilian, X. Qiao, J.O. Payero, J.M. Maja, C.V. Privette, Y.J. Han

103. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy Temperature

Development of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment ... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki

104. Challenges and Successes when Generating In-season Multi-temporal Calibrated Aerial Imagery

Digital aerial imagery (DAI) of the crop canopy collected by aircraft and unmanned aerial vehicles is the yardstick of precision agriculture.  However, the quantitative use of this imagery is often limited by its variable characteristics, low quality, and lack of radiometric calibration.  To increase the quality and utility of using DAI in crop management, it is important to evaluate and address these limitations of DAI.  Even though there have been improvements in spatial reso... P.M. Kyveryga, J. Pritsolas, J. Connor, R. Pearson

105. Detection of Potato Beetle Damage Using Remote Sensing from Small Unmanned Aircraft Systems

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution.  We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center (HAREC) to assess advantages and disadvantages of sUAS for precision farming. In 2014, we conducted an experiment in irrigated potatoes with 4 levels of artificial infestation by Colorado Potato Bee... E. Hunt, S.I. Rondon, A.E. Bruce, R.W. Turner, J.J. Brungardt

106. Time Series Analysis of Vegetation Dynamics and Burn Scar Mapping at Smoky Hill Air National Guard Range, Kansas Using Moderate Resolution Satellite Imagery

Military installments are import assets for the proper training of armed forces. To ensure the continued viability of the training grounds, management practices need to be implemented to sustain the necessary environmental conditions for safe and effective training. This analysis uses satellite imagery over time to gain insight into vegetation conditions over a large military installment. MODIS imagery was collected multiple times a year for 11 years at Smoky Hill Air National Guard Range (Sm... E. Williams

107. Melon Classification and Segementation Using Low Cost Remote Sensing Data Drones

Object recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the f... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang

108. Aerial Photographs to Predict Yield Loss Due to N Deficiency in Corn

Nitrogen fertilizer is a crucial input for corn production, and in the U.S. more nitrogen is applied to corn than to all other crops combined.  In wet weather, nitrogen can be lost from soil by leaching and by denitrification.  Which process predominates depends largely on soil drainage.  Nitrogen deficiency in nearly any plant is expressed by a lighter green color of leaves than in nitrogen-sufficient plants.  Nitrogen deficiency in corn can be easily seen from the air.&n... P. Scharf

109. Almond Canopy Detection and Segmentation Using Remote Sensing Data Drones

The development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different m... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang

110. AGOC: Agriculture Operations Center

After another long day, the farmer sits down in front of a computer (wishing this time was instead spent on the front porch catching a last glimpse of the sunset), and reflects once again ...     What if   ...  I actually knew the health of 100% of my crops rather than what I know today. a mere 20%. What if   ...  there was an effective, simple way to synchronize crop scouting and crop imagery efforts. ... M. Zamzow, H. Moulton

111. The Agriculture Operations Center: the Answer to “What If...”

Can’t farming be simpler?  Yes…with an Agriculture Operations Center -- we call it the AGOC, and it’s the next big step for precision agriculture.  Leveraging decades of lessons from the US Air Force, the AGOC provides the ability to schedule, execute, collect, consolidate, and distribute all the support a farmer needs from satellites, piloted aircraft, unmanned aircraft, sensing, modeling, and analysis…all packaged into “one stop shopping.”&nbs... M. Zamzow

112. Precision Agriculture Techniques for Crop Management in Trinidad and Tobago: Methodology & Field Layout

Agriculture in Trinidad and Tobago has not advanced at the same rate at which new agricultural technology has been released. This has led to large-scale abandonment of crop lands as challenges posed by labor availability and their agronomic capability could not meet the technological demands for agricultural production, competitiveness and sustainability. There is an urgent need to develop technology-based agriculture models to meet the demands of a modern agricultural sector and to maintain ... G. Seepersad, T. Sampson, S. Seepersad, D. Goorahoo

113. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance Spectra

Successful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and ... A. Gholizadeh, M. Saberioon, L. Borůvka

114. 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 d... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

115. NIR Spectroscopy to Map Quality Parameters of Sugarcane

Precision Agriculture aims to explore the potential of each crop considering the differences within the field. One information that is considered the most important is the yield or the obtained income in the field. However, in the case of sugarcane, quality will also directly influence farmer’s income. Several studies suggest harvester automation aiming to monitor yield, but few consider the quality analysis in the process. Among the existing methods for measuring sugar content the one ... M.N. Ferraz, J.P. Molin

116. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement.  However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (... D. Whattoff, D. Mouazen, D. Waine

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

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

118. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.

Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index ... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper

119. 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 detecti... H. Lilienthal, P. Wilde, E. Schnug

120. 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 e... H. Gerighausen, H. Lilienthal, E. Schnug

121. Estimation of Soil Profile Properties Using a VIS-NIR-EC-force Probe

Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related those sensor measuremen... Y. Cho, K.A. Sudduth

122. Laboratory Evaluation of Two VNIR Optical Sensor Designs for Vertical Soil Sensing

Visible and near infrared reflectance spectroscopy (VNIR) is becoming an extensively researched technology to predict soil properties such as soil organic carbon, inorganic carbon, total nitrogen, moisture  for precision agriculture. Due to its rapid, non-destructive nature and ability to infer multiple soil properties simultaneously, engineers have been trying to develop proximal sensors based on the VNIR technology to enable horizontal soil sensing and mapping. Since the vertical varia... N. Wijewardane, Y. Ge

123. Development of Micro-tractor-based Measurement Device of Soil Organic Matter Using On-the-go Visual-near Infrared Spectroscopy in Paddy Fields of South China

Soil organic matter (SOM) is an essential soil property for assessing the fertility of paddy soils in South China. In this study, a set of micro-tractor-based on-the-go device was developed and integrated to measure in-situ soil visible and near infrared (VIS–NIR) spectroscopy and estimate SOM content. This micro-tractor-based on-the-go device is composed of a micro-tractor with toothed-caterpillar band, a USB2000+ VIS–NIR spectroscopy detector, a self-customized steel plow and a ... Z. Lianqing, S. Zhou, C. Songchao, Y. Yafei

124. Development of a Sensing Device for Detecting Defoliation in Soybean

Estimating defoliation by insects in an agricultural field, specifically soybean, is performed by manually removing multiple leaf samples, visually inspecting the leaves for feeding, and assigning a value representing a “best guess” at the level of leaf material missing. These estimates can require considerable time and are subjective. The goal of this study was to design a low-cost system containing light sensors and a microcontroller that could remotely record and report long-te... P. Astillo, J. Maja, J. Greene

125. Evaluating low-cost Lidar and Active Optical Sensors for pasture and forage biomass assessment

Accurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration ac... M. Trotter, K. Andersson, M. Welch, M. Chau, L. Frizzel, D. Schneider

126. Sensor Based Soil Health Assessment

Quantification and assessment of soil health involves determining how well a soil is performing its biological, chemical, and physical functions relative to its inherent potential. Due to high cost, labor requirements, and soil disturbance, traditional laboratory analyses cannot provide high resolution soil health data. Therefore, sensor-based approaches are important to facilitate cost-effective, site-specific management for soil health. In the Central Claypan Region, visible, near-infrared ... K. Veum, K. Sudduth, N. Kitchen

127. Soil Attributes Estimation Based on Diffuse Reflectance Spectroscopy and Topographic Variability

The local management of crop areas, which is the basic concept of precision agriculture, is essential for increasing crop yield. In this context, diffuse reflectance spectroscopy (DRS) and digital elevation modelling (DEM) appears as an important technique for determining soil properties, on an adequate scale to agricultural management, enabling faster and less costly evaluations in soil studies. The objective of this work was to evaluate the use of DRS together with topographic parameters fo... J.V. fontenelli, L.R. Amaral, J.M. Demattê, P.G. Magalhães, G. Sanches

128. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane Fields

One important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-m... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco

129. On-the-go Measurements of pH in Tropical Soil

The objective of this study was to assess the performance of a mobile sensor platform with ion-selective antimony electrodes (ISE) to determine pH on-the-go in a Brazilian tropical soil. The field experiments were carried out in a Cambisol in Piracicaba-SP, Brazil. To create pH variability, increasing doses (0, 1, 3, 5, 7 and 9 Mg ha-1) of lime were added on the experimental plots (25 x 10 m) one year before the data acquisitions. To estimate soil pH levels we used a Mobile Sensor ... M.T. Eitelwein, R.G. Trevisan, A.F. Colaço, M.R. Vargas, J.P. Molin

130. Comparing Predictive Performance of Near Infrared Spectroscopy at a Field, Regional, National and Continental Scales by Using Spiking and Data Mining Techniques

The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties is a crucial step for variable rate application in precision agriculture. The objective of the present study was to compare the prediction performance of vis-NIR spectroscopy at local, regional, national and continental scales using data mining techniques including spiking. Fresh soil samples collected from farms in the UK, Czech Republic, Germany, Denmark and the Nethe... S.M. Nawar, A.M. Mouazen, D. George, A. Manfield

131. Time Series Study of Soybean Response Based on Adjusted Green Red Index

Four time-lapse cameras, Bushnell Nature View HD Camera (Bushnell, Overland Park, KS) were installed in a soybean field to track the response of soybean plants to solar radiation, air temperature, relative humidity, soil surface temperature, and soil temperature at 5-cm depth. The purpose was to confirm if visible spectroscopy can provide useful data for tracking the condition of crops and, if so, whether game and trail time-lapse cameras can serve as reliable crop sensing and monitoring devi... P.A. Larbi, S. Green

132. A Data Fusion Method for Yield and Soil Sensor Maps

Utilizing yield maps to their full potential has been one of the challenges in precision agriculture.  A key objective for understanding patterns of yield variation is to derive management zones, with the expectation that several years of quality yield data will delineate consistent productivity zones.  The anticipated outcome is a map that shows where soil productive potentials differ.  In spite of the widespread usage of yield monitors, commercial agriculture has found it dif... E. Lund, C. Maxton, T. Lund

133. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility Study

The fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffus... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki

134. SmartAgriHubs FIE20 - Groundwater and Meteo Sensors and Earth Observation for Precision Agriculture

The solution developed under the SmartAgriHubs project in the scope of the Flagship Innovation Experiment FIE20 Groundwater and meteo sensors is an expert system to support farmers in decision-making process and planning process of field interventions. This FIE20 solution integrates various data sources and different analytical processes in a complete system and provides users an easy-to-use web map application as a common user interface. The FIE20 system integrates components developed durin... K. Charvat, M. Kepka, R. Berzins, F. Zadrazil, D. Langovskis, M. Musil

135. Soil Moisture Variability on Golf Course Fairways Across the United States: an Opportunity for Water Conservation with Precision Irrigation

Fairways account for an average of 11.3 irrigated hectares on each of the 15,000+ golf courses in the US. Annual median water use per hectare on fairways is between ~2,800,000 and 14,000,000 liters, depending on the region. Conventional fairway irrigation relies on visual observation of the turfgrass, followed by secondary considerations of short-term weather forecasts, which oftentimes lead to “blanket” applications to the entire area. The concept of precision irrigation is a str... C. Straw, C. Bolton, J. Young, R. Hejl, J. Friell, E. Watkins

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

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

137. Investigation of Automated Analysis of Snowmelt from Time-series Sentinel 2 Imagery to Inform Spatial Patterns of Spring Soil Moisture in the American Mountain West

Variable rate irrigation of crops is a promising approach for saving water whilst maintaining crop yields in the semi-arid American Mountain West – much of which is currently experiencing a mega drought. The first step in determining irrigation zones involves characterizing the patterns of spatial variation in soil moisture and determining if these are relatively stable temporally in relation to topographic features and soil texture. Characterizing variable rate irrigation zones is usua... I. Turner, R. Kerry, R. Jensen, E. Woolley, N. Hansen, B. Hopkins

138. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, Canada

Soil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island.  A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision ir... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal

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

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

140. Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

The Western United States is currently experiencing a “Mega Drought”. This makes efficient water use more important than ever. Turfgrass is a major vegetation type in urban areas and performs many ecosystem services such as cooling through evapotranspiration, fixing carbon from the atmosphere and reducing wild-fire risk. There are now more acres of irrigated turfgrass (>40 million) in the USA than irrigated corn, wheat and fruit trees combined (Milesi et al., 2005). It has been... R. Kerry, S. Shumate, B. Ingram, K. Hammond, D. Gunther, R. Jensen, S. Schill, N. Hansen, B. Hopkins

141. Drone Use Extension and Demonstrations Support Management of Riparian Areas, Grazing Land, and Water Quality

Agricultural and natural resource managers have explored a variety of ways in which drones might be used to aid in decision-making. One of the most useful ways may be the production of orthorectified aerial photography which can have very high spatial and temporal resolution. Such photography offers new opportunities for visualizing and measuring features on the landscape. Not just measuring the two-dimensional characteristics of landscape features, but also measuring three-dimensional charac... W. Boyer

142. Sugarcane Yield Mapping Using an On-board Volumetric Sensor

Few alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being intro... G. Balboa, J.C. Masnello, F. De oliveira moreira, R. Canal filho, E.R. Da silva, J.P. Molin

143. Automatic Body Condition Score Classification System for Individual Beef Cattle Using Computer Vision

Body condition scoring (BCS) is a widely used parameter for assessing the utilization of energy reserves in the fat and muscle of cattle. It fulfills the needs of animal welfare and precision livestock farming by enabling effective monitoring of individual animals. It serves as a crucial parameter for optimizing nutrition, reproductive performance, overall health, and economic outcomes in beef cattle. The precise and consistent assessment of BCS relies on personal experience using visuals tha... M. Islam, J. Yoder, H. Gan

144. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows

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

145. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable Sensors

Lameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model pe... N. Mhlongo, H. De knegt, W.F. De boer, F. Van langevelde

146. Africa Regional Meeting

... K.A. Frimpong

147. Asia and Oceania Regional Meeting

... S.K. Balasundram

148. Europe Regional Meeting

... E. Gil

149. Latin America and the Caribbean Regional Meeting

... R.A. Ortega

150. North America Regional Meeting

Agenda: to discuss PA topics of common interest; to examine potential contributions of country representatives to the ISPA; to formulate suggestions to be examined by the Board for the development of the ISPA.   For your information: What do country representatives do? The intent of Country Representatives is to have champions of ISPA spread all over the world. Country Representativ... A. Cambouris, K.A. Sudduth

151. On-Farm Experimentation Community Meeting

Meeting Agenda: Updates for the OFE-C Newsletters  Increased membership Conference  Global OFE Network (GOFEN) Scientists AND Farmers Global Directory Discussion points OFE-C Outreach Country reps for the OFE-C / Entry point... L. Longchamps

152. Precision Nitrogen Management Community Meeting

Agenda Welcome to the meeting participants by Dr. Brenda Ortiz (Professor at Auburn University) 2022-2024 community leader and incoming leader Dr. Laila Puntel (Syngenta). Brief update of activities and opportunities for the upcoming years (Brenda Ortiz) Strategies to assess precision nutrient management educational needs and networking opportunities among community members and ISPA in general. Discuss possibilities for colla... B.V. Ortiz, L.A. Puntel

153. Precision Agriculture Economics, Profitability, Adoption, and Risk Community Meeting

Agenda Update on Community Activities Update on membership Announcement and introduction of incoming Deputy Leader Discussion points GIATE Symposium session Other activities AOB ... K. Behrendt, M. Michels

154. African Association for Precision Agriculture Community Meeting

... K.A. Frimpong, V. Aduramigba-modupe, N. Fassinou hotegni

155. Sentinel Fertigation - Sponsor Presentation

Sentinel’s N-Time software leverages imagery and agronomic data to provide nitrogen application scheduling and rate recommendations to agronomists and farmers. Recommendations from the system have demonstrated profitability improvements of $24/ac and Nitrogen use efficiency (NUE) improvements of 30% in on-farm research studies since 2021. This presentation will discuss the function of N-Time, highlight the advantages of the management system it enables, and briefly discuss on-farm resea... J. Stansell

156. National Agricultural Producers Data Cooperative - Sponsor Presentation

... B.E. Craker

157. TEG Automation Solutions - Sponsor Presentation

... V. Oliveira

158. Oklahoma State University Department of Plant and Soil Sciences - Sponsor Presentation

... R. Sharry