Login

Proceedings

Find matching any: Reset
Nascimento-Silva, K
Gidea, M
Dong, J
Berry, P
Westfall, D.G
Griffin, T.W
Boini, A
Hunsche, M
Westfall, D
Yilma, W
Bellenguez, R
White, S.N
Hachisuca, A.
Yan, N
Gebbers, R
Nadav, I
Wang, N
Bhuiya, G
Draye, X
Bonfil, D.J
Woods, S.A
G, S
Rice, K
Helmers, M
B, K
Bugnet, P
Webber, H
Romier, C
Been, T
Hensley, R
Wunder, E
Donatti, C
NAGAMI, Y
Fixen, P
Rahman, .M
Ham, W
Weckler, P
Bell, G.E
Dyrmann, M
Guerrero, H.B
Wienhold, B
Busscher, W.J
Dutta, S
Balkcom, K.S
Redmond, C
Giriyappa, M
Blackmer, T.M
Ru, G
Wang, K
Franzen, D.W
Russo, J.M
Yang, X.M
Green, R.L
Hartschuh, J
YI, S
R, P
Hopkins, B
Dag, A
Dafnaki, D
Add filter to result:
Authors
Sharma, L
Franzen, D.W
Tumenjargal, E
Badarch, L
Ham, W
Kwon, H
Tumenjargal, E
Badarch, L
Ham, W
Kwon, H
Lee, W
Wang, K
Li, H
Ehsani, R
Yang, C
Khosla, R
Westfall, D.G
Longchamps, L
Longchamps, L
Panneton, B
Westfall, D.G
Khosla, R
Soaud, A.A
Rahman, .M
Al Darwish, F.H
Shanwad, U.K
Patil, M.B
H, V
B.G , M
R, P
N.L. , R
S, S
Khosla, R
Patil, V.C
Bonfil, D.J
Shapira, U
Karnieli, A
Herrmann, I
Kinast, S
Wang, J.M
Li, C.M
Yang, X.M
Huang, W.M
Yang, H.M
Xu, X.M
Betz, A
Benny, H
Jens, M
Özyurtlu, M
Pflanz, M
Rachow-Autrum, T
Schischmanow, A
Scheele, M
Schrenk, J
Schrenk, L
Zude, M
Gebbers, R
Blackmer, T.M
Kyveryga, P.M
Romier, C
Hyrien, M
Lamker, D
Kyveryga, P.M
Blackmer, T.M
Kyveryga, P.M
Blackmer, T.M
Reeg, P.R
Blackmer, T.M
Kyveryga, P.M
Shaver, T
Schmer, M
Irmak, S
Van Donk, S
Wienhold, B
Jin, V
Bereuter, A
Francis, D
Rudnick, D
Ward, N
Hendrickson, L
Ferguson, R.B
Adamchuk, V.I
Franzen, D.W
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Moshia, M.E
Khosla, R
Davis, J
Westfall, D
Ru, G
Schneider, M
Kruse, R
Bonfil, D.J
Herrmann, I
Pimstein, A
Karnieli, A
Shapira , U
Herrmann, I
Karnieli, A
Bonfil, D.J
Herrmann, I
Pimstein, A
Karnieli, A
Cohen, Y
Alchanatis , V
Bonfil, D.J
Kyveryga, P.M
Blackmer, T.M
Pearson , R
Blackmer, T.M
Kyveryga, P.M
Rice, K
Carson, T
Krum, J
Flitcroft, I
Cline, V
Carrow, R
Kodaira, M
NAGAMI, Y
Shibusawa, S
KANDA, R
Stone, K
Bauer, P.J
Busscher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
R, C
Rumpf, T
B, K
Hunsche, M
Pl, L
Noga, G
Shaver, T
Khosla, R
Westfall, D
Singh, M
Sharma, A
Singh, G
Fixen, P
Peterson, G
Westfall, D
Sherrod, L.A
Moss, J.Q
Bell, G.E
Moss, J.Q
Bell, G.E
Solie, J.B
Stone, M.L
Martin, D.L
Payton, M.E
McNeill, D
Bishop-Hurley, G.J
Irvine, L
Freeman, M
Bellenguez, R
YI, S
Deng, L
Gitelson, A.A
Bonfil, D.J
Sharma, L
Bu, H
Ashley, R
Endres, G
Teboh, J
Franzen, D.W
Mueller, T
Neelakantan, S
Helmers, M
Dosskey, M
Stevens, L.J
Ferguson, R.B
Franzen, D.W
Kitchen, N.R
Hertzberg, J
Ruckelshausen, A
Wunder, E
Linz, A
Fulton, J.P
Balkcom, K.S
Ortiz, B.V
McDonald, T.P
Pate, G.L
Virk, S.S
Poncet, A
Alchanatis, V
Cohen, Y
Sprinstin, M
Cohen, A
Zipori, I
Dag, A
Naor, A
Griffin, T.W
Mark, T
Zeng, H
Wu, B
Yan, N
Leufen, G
Noga, G
Hunsche, M
Leufen, G
Noga, G
Hunsche, M
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Wang, C
Chen, T
Dong, J
Li, C
Rothrock, C.S
Monfort, W.S
Griffin, T.W
Spurlock, T.N
Banerjee, M
Dutta, S
Bhuiya, G
Malik, G
Maiti, D
Momsen, E
Xu, J
Franzen, D.W
Nowatzki, J.F
Farahmand, K
Denton, A.M
Kempenaar, C
Been, T
Evert, F.V
Webber, H
Maurer, J.L
Griffin, T.W
Sharda, A
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Denton, A.M
Chavan, H
Franzen, D.W
Nowatzki, J.F
Becker, M
Velasquez, A.E
Guerrero, H.B
HIguti, V.A
Milori, D.M
Magalhães, D.V
Kempenaar, C
van Evert, F
Been, T
Kocks, C
Westerdijk, K
Nysten, S
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Bennett, J
Wilson, C
Sharda, A
Griffin, T.W
Ransom, C.J
Bean, M
Kitchen, N
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Sharda, A
Badua, S
Flippo, D
Ciampitti, I
Griffin, T.W
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
Franzen, D.W
Boettinger, J.L
Franzen, D.W
Casey, F
Staricka, J
Long, D
Lamb, J
Sims, A
Halvorson, M
Hofman, V
Franzen, D.W
Taylor, R.K
Bennur, P
Solie, J.B
Wang, N
Weckler, P
Raun, W.R
Musetescu, L
Gidea, M
Nadav, I
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Sylvester-Bradley, R
Kindred, D
Berry, P
Tumenjargal, E
Batbayar, E
Munkhbayar, S
Tsogt-Ochir, S
Oyumaa, M
Chung, K
Ham, W
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
van Evert, F.K
Been, T
Booij, J.A
Kempenaar, C
Kessel, G.J
Molendijk, L.P
Skovsen, S
Dyrmann, M
Eriksen, J
Gislum, R
Karstoft, H
Jørgensen, R.N
Dyrmann, M
Skovsen, S
Jørgensen, R.N
Laursen, M.S
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
KC, K
Hannah, L
Roehrdanz, P
Donatti, C
Fraser, E
Berg, A
Saenz, L
Wright, T.M
Hijmans, R.J
Mulligan, M
Bouroubi, Y
Bugnet, P
Nguyen-Xuan, T
Bélec, C
Longchamps, L
Vigneault, P
Gosselin, C
Sharda, A
Badua, S
Ciampitti, I
Strasser, R
Griffin, T.W
Bhandari, S
Raheja, A
Chaichi, M.R
Green, R.L
Do, D
Ansari, M
Wolf, J.G
Espinas, A
Pham, F.H
Sherman, T.M
Dhoubhadel, S
Griffin, T.W
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Griffin, T
Redmond, C
Knapp, M
G, S
Biradar, D.P
Desai, B.L
Patil, V.C
Patil, P
Nargund, V.B
Desai, V
John, W
Channangi, S.M
Tulasigeri, V
Yari, A
Madramootoo, C
Woods, S.A
Adamchuk, V.I
Gilbert, L
Bazzi, C.L
Martins, M.R
Gebler, L
Souza, E.G
Schenatto, K
Sobjak, R
Hachisuca, A.
Franz, F
Goldwasser, Y
Alchanati, V
Goldshtein, E
Cohen, Y
Gips, A
Nadav, I
Lang, V
Tóth, G
Csenki, S
Dafnaki, D
Peña, J
Melgar, J
de Castro, A
Maja, J
Nascimento-Silva, K
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Siegfried, J
Khosla, R
Mandal, D
Yilma, W
Turner, I
Kerry, R
Jensen, R
Woolley, E
Hansen, N
Hopkins, B
Fulton, J.P
Hawkins, E
Shearer, S
Klopfenstein, A
Hartschuh, J
Custer, S
Xiong, X
Myers, D
DeBruin, J
Gunzenhauser, B
Sampath, N
Ye, D
Underwood, H
Hensley, R
Topics
Sensor Application in Managing In-season Crop Variability
Engineering Technologies and Advances
Guidance, Robotics, Automation, and GPS Systems
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Precision Nutrient Management
Food Security and Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Precision Crop Protection
Education and Training in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision A to Z for Practitioners
Precision A-Z for Practitioners
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability, and Adoption
Modeling and Geo-statistics
Sensor Application in Managing In-season Crop Variability
Precision Carbon Management
Precision Horticulture
Precision Livestock Management
Sensor Application in Managing In-season CropVariability
Precision Conservation Management
Precision Horticulture
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Fluorescence Sensing for Precision Crop Management
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Precision Crop Protection
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Decision Support Systems in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Standards & Data Stewardship
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Remote Sensing for Nitrogen Management
Drainage Optimization and Variable Rate Irrigation
Big Data, Data Mining and Deep Learning
Precision Agriculture and Global Food Security
Robotics, Guidance and Automation
Precision Crop Protection
Profitability and Success Stories in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Geospatial Data
On Farm Experimentation with Site-Specific Technologies
Applications of Unmanned Aerial Systems
Smart Weather for Precision Agriculture
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Applications of Unmanned Aerial Systems
Big Data, Data Mining and Deep Learning
Drainage Optimization and Variable Rate Irrigation
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
Home » Authors » Results

Authors

Filter results97 paper(s) found.

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

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

2. Precision Manure Management: It Matters Where You Put Your Manure

“Precision fertilizer management” has been around for more than a decade and is practiced widely in Colorado and elsewhere. By precision, we mean application of fertilizer at the right time, in the right place, and in the right amount. However, “Precision Manure Management” is a relatively new concept that converge the best manure management practices with precision nutrient management practices, such as variable rate nutrient application across site-specific management... M.E. Moshia, R. Khosla, J. Davis, D. Westfall

3. A Clustering Approach For Management Zone Delineation In Precision Agriculture

In recent years, an increasing amount of research has been devoted to the delineation of management zones. There have been quite a number of approaches towards using small-scale data for subdividing the field into a small number of zones, usually three or four. However, these zones are usually static, often require multi-year data sets and are based on low-resolution sampling methods for data acquisition. Furthermore, existing research into the... G. Ru, M. Schneider, R. Kruse

4. Multi, Super Or Hyper Spectral Data, The Right Way From Research Toward Application In Agriculture

Remote sensing provides opportunities for diverse applications in agriculture. One consideration of maximizing the utility of these applications, is the need to choose the most efficient spectral resolution. Picking the optimal spectral resolutions (multi, super or hyper) for a specific application is also influenced by other factors (e.g., spatial and temporal resolutions) of the utilized device. This work focuses mainly on... D.J. Bonfil, I. Herrmann, A. Pimstein, A. Karnieli

5. Weeds Detection By Ground-level Hyperspectral Imaging

Weeds are a severe pest in agriculture, causing extensive yield loss. Weed control of grass and broadleaf weeds is commonly performed by applying selective herbicides homogeneously all over the field. As presented in several studies, applying the herbicide only where needed has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically... U. Shapira , I. Herrmann, A. Karnieli, D.J. Bonfil

6. Assessment Of Field Crops Leaf Area Index By The Red-edge Inflection Point Derived From Venus Bands

The red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional status.... I. Herrmann, A. Pimstein, A. Karnieli, Y. Cohen, V. Alchanatis , D.J. Bonfil

7. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within Fields

Using uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) deficiencies of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Digital aerial imagery taken later during the growing season is more accurate in identifying areas deficient in N. Even so, the quantitative use of late-season DAI across many fields is still limited because the imagery is not truly calibrated. This study... P.M. Kyveryga, T.M. Blackmer, R. Pearson

8. A Systematic Approach For Using Precision Agriculture Tools For On-farm Evaluations In Iowa

 The competitive nature of modern agriculture requires constant refinements of many crop production management decisions. Precision agriculture tools (PAT) can allow growers to rapidly evaluate different management practices across large areas at a relatively low cost. But a systematic approach and a decision-making process describing how to utilize different PAT for on-farm evaluations have not been yet developed and adopted. This presentation will focus on how  approximately... T.M. Blackmer, P.M. Kyveryga

9. Spatial Mapping Of Penetrometer Resistance On Turfgrass Soils For Site-specific Cultivation

Site-specific management requires site-specific information.  Soil compaction at field capacity is a major stress on recreational turfgrass sites that requires frequent cultivation. Spatial mapping of penetrometer... K. Rice, T. Carson, J. Krum, I. Flitcroft, V. Cline, R. Carrow

10. The Soil P2O5 Mapping Using The Real Time Soil Sensor

    Many researches related to P­2O5 measurement using Vis-NIR spectroscopy have been performed in laboratory. There are not so many researches to perform on-the-go measurement of P­2O5. One of the researches which performed... M. Kodaira, Y. Nagami, S. Shibusawa, R. Kanda

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

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

12. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral Signatures

Early recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370-800... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga

13. Development Of A Nitrogen Requirement Algorithm Using Ground-based Active Remote Sensors In Irrigated Maize

Studies have shown that normalized difference vegetation index (NDVI) from ground-based active remote sensors is highly related with leaf N content in maize (Zea mays). Remotely sensed NDVI imagery can provide valuable information about in-field N variability in maize and significant linear relationships between sensor NDVI and maize grain yield have been found suggesting that an N recommendation algorithm based on NDVI could optimize N application. Therefore, a study was conducted using the two... T. Shaver, R. Khosla, D. Westfall

14. Development Of Batch Type Yield Monitor For Small Fields

 Abstract The yield monitor is intended to give the user an accurate assessment of yield variations y within a field. A yield monitor can assist grain producers in many aspects of crop management. A yield monitor by itself can provide useful information and enhance on-farm research. Yield data can... M. Singh, A. Sharma, G. Singh, P. Fixen

15. Landscape Position And Climatic Gradient Impacts On Carbon Turnover in Dryland Cropping Systems in Colorado

  Soil organic carbon has decreased in cultivated wheat-fallow systems due to increased carbon oxidation, low carbon input and soil erosion.  Implementation of more intensive cropping with no-till management has reversed the trend in soil carbon loss.  Our objective in this presentation is to review the effects of landscape position on soil carbon status as related to intensification of cropping system.  Our analysis will... G. Peterson, D. Westfall, L.A. Sherrod

16. Indirect Measurement Of Creeping Bentgrass N, Chlorophyll, And Color For Precision Golf Green Management

Indirect measurement of turfgrass tissue through optical sensing may provide golf course managers with non-destructive and relatively simple real-time measurements of golf green N requirements. The objective of this study was to determine the effect of N rate on ‘Crenshaw’ creeping bentgrass (Agrostis stolonifera L.) tissue N, chlorophyll concentration, and color using the GreenSeeker (NTech Industries, Ukiah, CA) handheld sensor. Plots... J.Q. Moss, G.E. Bell

17. Development Of A Precision Sensing Sprayer For The Application Of Nitrogen Fertilizer To Turfgrass

  Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m)... J.Q. Moss, G.E. Bell, J.B. Solie, M.L. Stone, D.L. Martin, M.E. Payton

18. A Preliminary Evaluation Of Proximity Loggers To Detect Oestrus Behaviour In Grazing Dairy Cows

... D. Mcneill, G.J. Bishop-hurley, L. Irvine, M. Freeman, R. Bellenguez

19. Research On Nutrition Detection Technology Of Soil And Leaf Of Citrus Based On Spectroscopic Techniques

The diagnosis technique of real-time lossless crop nutrition is the foundation and conditions for the precise and effective fertilization. Currently, the diagnosis of crop nutrition mainly relies on the routine chemical analysis of laboratory. Due to the complicated procedure, time-consuming, high cost and high professional technique requirement, it can hardly meet the need of precise variable fertilization technology. Spectrum technology is the technology of real-time and non-destructive testing,... S. Yi, L. Deng

20. 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 and... L. Sharma, D.W. Franzen

21. Implementation of ECU For Agricultural Machines Based On IsoAgLib Open Source

In this paper work, we consider implementation of electronic control unit (ECU) for agricultural machineries. Software implementation is based on IsoAgLib library developed by OSB&IT Engineering Company. We modify IsoAgLib and upgrade it for our target system. The IsoAgLib is an object oriented C++ library that has the communication services and management systems according to the ISO 11783 standard. This library allows building ISOBUS compatible equipment without the protocols implementation... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon

22. Design and Implementation of Virtual Terminal Based On ISO11783 Standard for Agricultural Tractors

The modern agricultural machinery most common use of the embedded electronic and remote sensing technology demands adoption of the Precision Agriculture (PA). One of the common devices is the Virtual Terminal (VT) for tractor. The VT’s functions and terminology are described in the ISO11783 standard. This work presents the control system design and implementation of the VT and some Electronic Control Units (ECU) for agricultural vehicles based on the ISO 11783 standard. The VT development... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon

23. Spectral Angle Mapper (SAM) Based Citrus Greening Disease Detection Using Airborne Hyperspectral Imaging

Over the past two decades, hyperspectral (HS) imaging has provided remarkable performance in ground objects classification and disease identification, due to its high spectral resolution. In this paper, a novel method named ‘extended spectral angle mapping (ESAM)’ is proposed to detect citrus greening disease (Huanglongbing or HLB), which is a destructive disease of citrus. Firstly, Savitzky-Golay smoothing filter was applied to the raw image to remove spectral noise within the data,... W. Lee, K. Wang, H. Li, R. Ehsani, C. Yang

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

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

25. Testing The Author Sequence - Finalize

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

26. Stable Isotope N-15 as Precision Technique to Investigate Elemental Sulfur Effects on Fertilizer Nitrogen Use Efficiency of Corn Grown in Calcareous Sandy Soils

... A.A. Soaud, .M. Rahman, F.H. Al darwish

27. Precision Agriculture Initiative for Karnataka – A New Direction for Strengthening Farming Community

Strengthening agriculture is crucial to meet the myriad challenges of rural poverty, food security, unemployment, and sustainability of natural resources and it also needs strengthening at technical, financial and management levels. In this context... U.K. Shanwad, M.B. Patil, V. H, M. B.g , P. R, R. N.l. , S. S, R. Khosla, V.C. Patil

28. Ground Level Hyperspectral Imagery For Weeds Detection In Wheat Fields

Weeds are a severe pest in agriculture resulting in extensive yield loss. Applying precise weed control has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically locate and identify weeds in order to allow precise control. The objective of the current work is to detect annual... D.J. Bonfil, U. Shapira, A. Karnieli, I. Herrmann, S. Kinast

29. Estimation of Leaf Nitrogen Concentration in Barley with In Situ Hyperspectral Measurements

Leaf nitrogen concentration (LNC), a good indicator of nitrogen status in crop, is of special significance to diagnose nutrient stress and guide nitrogen fertilization in fields. Due to its non-destructive and quick advantages, hyperspectral remote sensing plays a unique role... J.M. Wang, C.M. Li, X.M. Yang, W.M. Huang, H.M. Yang, X.M. Xu

30. OptiThin - Precision Fruiticulture by Tree-Specific Mechanical Thinning

Apple cultivars show biennial fluctuations in yields (alternate bearing). The phenomenon is induced by reduced yields in one year due to freeze damage, low pollination rate or other reasons. Consequently, trees develop many flower buds that blossom in the following year. The many flowers lead to a high number of small fruits that won’t be accepted on the market. Endogenous factors (phytohormones and carbohydrate allocation) subsequently establish the biennial cycle. The alternate bearing... A. Betz, H. Benny, M. Jens, M. Özyurtlu, M. Pflanz, T. Rachow-autrum, A. Schischmanow, M. Scheele, J. Schrenk, L. Schrenk, M. Zude, R. Gebbers

31. Precision Tools to Evaluate Alternative Weed Management Systems in Soybean

... T.M. Blackmer, P.M. Kyveryga

32. A New Approach to Yield Map Creation

    One of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field.  Numerous data errors in the way the data is collected, poor calibration habits on the part of operators... C. Romier, M. Hyrien, D. Lamker

33. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure

... P.M. Kyveryga, T.M. Blackmer

34. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey

... P.M. Kyveryga, T.M. Blackmer

35. 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

36. 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

37. Use of Zone or Grid Soil Nutrient Management as Part of an Integrated Site-specific Nutrient Strategy

Zone and grid sampling are used as a basis for fertilizing with nutrients site-specifically. Use of sensors to assist in-season management of nitrogen is also gaining momentum. The presentation will suggest when grid or zone sampling for preplant nutrients might be utilized and how these recommendations would be used in an integrated approach of preplant plus in-season nutrient management. ... D. Franzen

38. Rapidscan And CropCircle Radiometers: Opportunities And Limitation In Assessing Wheat Biomass And Nitrogen

Remote sensing is a promising technology that provides information about the crop's physiological and phenological status. This information is based on the spectral absorption and scattering features of the plants. Many different vegetation indices (VI) have been developed, and are in use to estimate quantitatively the relationship between multi and hyper-spectral reflectance and effective crop physiological parameters, i.e. nitrogen (N) content, biomass, leaf area index (LAI). The CropCircle... A.A. Gitelson, D.J. Bonfil

39. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North Dakota

A recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indicated... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen

40. Precision Design Of Vegetative Buffers

Precision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, variable-width,... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey

41. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation Approaches

Nitrogen (N), an essential element, is often limiting to plant growth.  There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses.  Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs.  Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen

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

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

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

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

44. Automatic Detection And Mapping Of Irrigation System Failures Using Remotely Sensed Canopy Temperature And Image Processing

Today there is no systematic way to identify and locate failures of irrigation systems mainly because of the labor costs associated with locating the failures. The general aim of this study was to develop an airborne thermal imaging system for semi - automatic monitoring and mapping of irrigation system failures, specifically, of leaks and clogs. Initially, leaks and clogs were simulated by setting controlled trials in table grapes vineyards and olive groves. Airborne thermal... V. Alchanatis, Y. Cohen, M. Sprinstin, A. Cohen, I. Zipori, A. Dag, A. Naor

45. Value Of Connectivity In Rural Areas: Case Of Precision Agriculture Data

The introduction of precision agricultural technologies in the early 1990’s was made possible through the utilization of global positioning system (GPS). However, unlike GPS which has worldwide coverage allowing field-level precision agricultural activities to occur. Collecting spatial and machinery data into a repository efficiently is not currently feasible in real-time due to lack of broadband and wireless connectivity in many rural areas even in developed counties. Lack... T. Griffin, T. Mark

46. A Method To Estimate Irrigation Efficiency With Evapotranspiration Data

Irrigation efficiency is defined as the ratio of irrigation water consumed by the crops to the water diverted (Wg) from a river or reservoir or wells. This terminology serves for better irrigation systems designation and irrigation management practices improvement. But it is hard or high cost with labor intensity to estimate irrigation efficiency from field measurement. This paper proposes an estimating method of irrigation efficiency at the scale of irrigation... H. Zeng, B. Wu, N. Yan

47. Suitability Of Fluorescence Sensors To Estimate The Susceptibility Degree Of Spring Barley To Powdery Mildew And Leaf Rust

The overall role of precision agriculture is not restricted to those systems for in-field and in-season sensing of the impact of stresses. Much more, its contribution comprises the prevention of stresses, amongst others by supporting the selection of appropriate and stress-tolerant genotypes in breeding programs. In this context, the development, selection and use of cultivars which are tolerant to pathogens establish an essential tool for a more sustainable and environmental-friendly... G. Leufen, G. Noga, M. Hunsche

48. Selection Of Fluorescence Indices For The Proximal Sensing Of Single And Multiple Stresses In Sugar Beet

The use of fluorescence indices for sensing the impact of abiotic and biotic stresses in agricultural crops is well documented in the literature. Pigment fluorescence gives a precise picture about the plant physiology and its changes following the occurrence of stresses. In general, alterations in such optical signals is caused either by the stress-induced accumulation of one or more fluorophores, or the degradation of specific molecules like chlorophyll. Unfortunately, many stresses... G. Leufen, G. Noga, M. Hunsche

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

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

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

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

51. Disease Scouting For Aerial Blight Based On Logical Areas Of Collection In Soybean Fields Rotated With Rice

Rhizoctonia solani AG1-IA causes sheath blight in rice and aerial blight in soybean.  In Arkansas, rice and soybean rotations facilitate a continuous source of R. solani AG1-IA inoculum from one year to the next.    Aerial blight is a two stage disease where colonization of the plant occurs during the early vegetative growth stages and aerial blight symptoms occur during the reproductive growth stages after canopy closure.  At canopy closure,... C.S. Rothrock, W.S. Monfort, T.W. Griffin, T.N. Spurlock

52. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of India

Nutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Bengal... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti

53. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield Prediction

Yield predictions based on remotely sensed data are not always accurate.  Adding meteorological and other data can help, but may also result in over-fitting.  Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the sugar... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton

54. Use Of Vegetation Indices In Variable Rate Application Of Potato Haulm Killing Herbicides

Variable rate application (VRA) of pesticides based on measured spatial variation in crop biomass is possible with currently available crop reflection sensors (remote and proximity), GNSS technology and modern field sprayers. VRA has the potential to contribute to a more sustainable use of pesticide. Dose rates are optimized based on local requirements at a scale of about 5-50 m2, leading to less adverse side effects, less costs and higher yields. In the longer term, we... C. Kempenaar, T. Been, F.V. Evert

55. Understanding Complex Soil Variability: the Application of Archaeological Knowledge to Precision Agriculture Systems in the UK.

As higher resolution datasets have become more available and more accessible within commercial agriculture, there has been an increasing expectation that more data will bring more answers to questions surrounding soil, crop and yield variability. When this does not happen, trust and confidence in data can be lost, affecting the uptake and use of precision agriculture. This research presents a novel approach for understanding complex soil variability at a variety of different scales.... H. Webber

56. Site-specific Scale Efficiency Determined by Data Envelopment Analysis of Precision Agriculture Field Data

Since its inception and acceptance as a benchmarking tool within the economics literature, data envelopment analysis (DEA) has been used primarily as a means of calculating and ranking whole-farm entities marked as decision making units (DMU) against one another.  Within this study, instead of ranking the entire farm operation against similar peers that encompass the study, individual data points from within the field are evaluated to analyze the site-specific technical efficiencies estimated... J.L. Maurer, T.W. Griffin, A. Sharda

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

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

58. 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 length... A.M. Denton, H. Chavan, D.W. Franzen, J.F. Nowatzki

59. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision Agriculture

The use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães

60. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

61. Integrated Approach to Site-specific Soil Fertility Management

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

62. Value of Map Sharing Between Multiple Vehicles Using Automated Section Control in the Same Field

Large area farms and even moderate sized farms employing custom applicators and harvesters have multiple machines in the same field at the same time conducting the same field operation.  As a method to control input costs and minimize application overlap, these machines have been equipped with automatic section control (ASC). Over application is a concern especially for more irregularly shaped fields; however modern technology including automated guidance combined with automatic section control... J. Bennett, C. Wilson, A. Sharda, T. Griffin

63. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor Algorithm

Nitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

64. Real-time Gauge Wheel Load Variability on Planter with Downforce Control During Field Operation

Downforce control allows planters to maintain gauge wheel load across a range of soil resistance within a field. Downforce control is typically set for a target seed depth and either set to manually or automatically control the gauge wheel load. This technology uses load cells to actively regulate downforce on individual row units by monitoring target load on the gauge wheels. However, no studies have been conducted to evaluate the variability in gauge wheel load observed during planter operation... A. Sharda, S. Badua, D. Flippo, I. Ciampitti, T.W. Griffin

65. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

66. Terrain Modeling to Improve Soil Survey in North Dakota

Users of site-specific technologies would prefer to use digitized soil survey boundaries to help in delineating management zones for nutrient application. However, the present scale of soil type does not allow meaningful zone delineation. A project was conducted to use terrain modeling and other site- specific tools to delineate smaller-scale soil type boundaries that would be more useful for directing within-field nutrient management. Topography, soil EC, yield mapping and satellite imagery were... D.W. Franzen, J.L. Boettinger

67. Regional Usefulness of Nitrogen Management Zone Delineation Tools

In the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman

68. Summary of Forty Years of Grid Sampling Research

Between the years of 1961 and 2001, two 12.5-ha fields in Illinois were sampled for soil pH, and available P and K in a 24.3-m grid. One field was sampled beginning in 1961 while the other field was sampled from 1982. At each sampling, the samples were obtained in the same grid. This resulted in the ability not only to compare grid sample density to delineate fertility patterns within the fields, but also to determine the rate of soil test change with P and K applications, the change in fertility... D.W. Franzen

69. Controller Performance Criteria for Sensor Based Variable Rate Application

Sensor based variable rate application of crop inputs provides unique challenges for traditional rate controllers when compared to map based applications. The controller set point is typically changing every second whereas with a map based systems the set point changes much less frequently. As applied data files for a sensor based variable rate nitrogen applicator were obtained from a wheat field in north central Oklahoma. These data were analyzed to determine the magnitude and frequency of rate... R.K. Taylor, P. Bennur, J.B. Solie, N. Wang, P. Weckler, W.R. Raun

70. Evaluation of Utilization Potential for Methods of Georeference in the Management of Weed Contamination of Potato Cultures

Combating crop contamination with harmful invasive species is one of the main themes of agricultural research. For the potato cultures, the weed contamination decreases not only the quality but also the quantity of the harvest. The most invasive contamination for this culture is represented by the Agropyron repens and Sorgum halepense, two invasive and very nocive species characterized by underground stems able to penetrate the potato¢s tubercle and decrease their storage... L. Musetescu, M. Gidea

71. Elimination of Spatial Variability Using Variable Rate Drip Irrigation (VRDI) in Vineyards

Vineyards worldwide are subjected to spatial variability, which can be exhibited in both low and high yield areas meaning that the vineyard is not achieving his full yield potential. In addition, the grapes quality is not uniformed leading to different wine qualities from the same plot. The assumption is that a variability in available water for the plant due to soil variability leads to the observed yield variability. A variable rate drip irrigation (VRDI) concept was developed to reduce such... I. Nadav

72. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli

73. Agronōmics: Eliciting Food Security from Big Data, Big Ideas and Small Farms

Most farmers globally could make their farms more productive; few are limited by ambient availabilities of light energy and water. Similarly the sustainability of farming practices offers large scope for innovation and improvement. However, conventional ‘top-down’ Agricultural Knowledge and Innovation Systems (AKISs) are commonly failing to maintain significant progress in either productivity or sustainability because multifarious and complex agronomic interactions thwart accurate... R. Sylvester-bradley, D. Kindred, P. Berry

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

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

75. Spatial Variability of Optimized Herbicide Mixtures and Dosages

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

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

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

77. Predicting Dry Matter Composition of Grass Clover Leys Using Data Simulation and Camera-Based Segmentation of Field Canopies into White Clover, Red Clover, Grass and Weeds

Targeted fertilization of grass clover leys shows high financial and environmental potentials leading to higher yields of increased quality, while reducing nitrate leaching. To realize the gains, an accurate fertilization map is required, which is closely related to the local composition of plant species in the biomass. In our setup, we utilize a top-down canopy view of the grass clover ley to estimate the composition of the vegetation, and predict the composition of the dry matter of the forage.... S. Skovsen, M. Dyrmann, J. Eriksen, R. Gislum, H. Karstoft, R.N. Jørgensen

78. Using a Fully Convolutional Neural Network for Detecting Locations of Weeds in Images from Cereal Fields

Information about the presence of weeds in fields is important to decide on a weed control strategy. This is especially crucial in precision weed management, where the position of each plant is essential for conducting mechanical weed control or patch spraying. For detecting weeds, this study proposes a fully convolutional neural network, which detects weeds in images and classifies each one as either a monocot or dicot. The network has been trained on over 13 000 weed annotations... M. Dyrmann, S. Skovsen, R.N. Jørgensen, M.S. Laursen

79. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

80. Using Geospatial Data to Assess How Climate Change May Affect Land Suitability for Agriculture Production

Finding solutions to the challenge of sustainably feeding the world’s growing population is a pressing research need that cuts across many disciplines including using geospatial data. One possible area could be developing agricultural frontiers. Frontiers are defined as land that is currently not cultivated but that may become suitable for agriculture under climate change. Climate change may drive large-scale geographic shifts in agriculture, including expansion in cultivation at the thermal... K. Kc, L. Hannah, P. Roehrdanz, C. Donatti, E. Fraser, A. Berg, L. Saenz, T.M. Wright, R.J. Hijmans, M. Mulligan

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

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

82. Influence of Planter Downforce Setting and Ground Speed on Seeding Depth and Plant Spacing Uniformity of Corn

Uniform seed placement improves seed-to-soil contact and requires proper selection of downforce control across varying field conditions. At faster ground speeds, downforce changes and it becomes critical to select the level of planter downforce settings to achieve the desired consistency of seed placement during planting. The objective of this study was to assess the effect of ground speed and downforce setting on seeding depth and plant spacing and to evaluate the relationship of ground speed... A. Sharda, S. Badua, I. Ciampitti, R. Strasser, T.W. Griffin

83. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water Stresses

This paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman

84. The Impact of Precision Agriculture Technologies on Farm Profitability in Kansas

Even with more than a decade long adoption of the precision agriculture (PA) technologies in the United States, its impact on farm profitability is still not clear. This paper uses farm level data from Kansas Farm Management Association (KFMA) to conduct the ex-post evaluation of PA technologies on farm profitability in Kansas. The analysis of the data using propensity score matching method indicates that there is on an average $60,000 difference in net returns of the farm with at least one PA... S. Dhoubhadel, T.W. Griffin

85. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

86. Managing the Kansas Mesonet for Site Specific Weather Information

Weather data has become one of the most widely discussed layers in precision agriculture especially in terms of agricultural ‘big data’. However, most farmers (and even other researchers outside of meteorology) are not likely aware of the complexities required to maintain weather stations that provide data. These stations are exposed to the elements 24/7 and provide unique challenges for sustainment during extreme weather conditions. Based upon decades of experience, this paper discusses... T. Griffin, C. Redmond, M. Knapp

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

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

88. Application of Variable-Rate Irrigation for Potato Productivity

Variable-rate irrigation (VRI) has the potential to increase yields and reduce water consumption and energy costs. Spatial and temporal variability of soil and field properties can impact the efficiency of irrigation and crop yield. The VRI technology allows for the precise application of irrigation to meet crop water demands in controlled amounts prescribed for specific management zones within a field. Sensitivity to over and under-irrigation and the high-water requirements of potato make the... A. Yari, C. Madramootoo, S.A. Woods, V.I. Adamchuk, L. Gilbert

89. Yield Mapping in Fruit Farming

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

90. The Use of Spatial and Temporal Measures to Enhance the Sensitivity of Satellite-based Spectral Vegetation Indices to (Water) Stress in Maize Fields

Climate change and water scarcity are reducing the available irrigation water for agriculture thus turning it into a limited resource. Today calculating and estimating crop water requirements are achieved through the ETc FAO-56 model where the effect of climate on crop water requirement is determined through the water evaporation from the soil and plant (ETref), and a calendar crop coefficient (Kc). Models that... Y. Goldwasser, V. Alchanati, E. Goldshtein, Y. Cohen, A. Gips, I. Nadav

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

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

92. UAV-based Hyperspectral Monitoring of Peach Trees As Affected by Silicon Applications and Water Stress Status

Previous research has shown that the application of reduced doses of Silicon (Si) improves crop tolerance to water stress, which is common in commercial young peach trees because irrigation is not usually applied during their first two years. In this study, aerial images were used to monitor the impact of different Si and water treatments on the hyperspectral response of peach trees. An experiment with 60 young (under 1 year old) peach trees located at the Musser Fruit Research Center (Seneca,... J. Peña, J. Melgar, A. De castro, J. Maja, K. Nascimento-silva

93. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild Blueberry

Deep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White

94. Enhancing Spatial Resolution of Maize Grain Yield Data

Grain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops.  Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used to... J. Siegfried, R. Khosla, D. Mandal, W. Yilma

95. 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 usually... I. Turner, R. Kerry, R. Jensen, E. Woolley, N. Hansen, B. Hopkins

96. Nitrogen Placement Considerations for Maize Production in the Eastern US Cornbelt

Proper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production. ... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer

97. Functional Soil Property Mapping with Electrical Conductivity, Spectral and Satellite Remote Sensors

Proximal electrical conductivity (EC) and spectral sensing has been widely used as a cost-effective tool for soil mapping at field scale. The traditional method of calibrating proximal sensors for functional soil property prediction (e.g., soil organic matter, sand, silt, and clay contents) requires the local soil sample data, which results in a field-specific calibration. In this large-scale study consisting of 126 fields, we found that the traditional local calibration method had suffered weak... X. Xiong, D. Myers, J. Debruin, B. Gunzenhauser, N. Sampath, D. Ye, H. Underwood, R. Hensley