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Remote Sensing Applications in Precision Agriculture
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Precision Crop Protection
Precision Dairy and Livestock Management
Decision Support Systems
Small Holders and Precision Agriculture
Education and Outreach in Precision Agriculture
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Authors
Aasen, H
Abonyi, J
Abu Kassim, F
Adamchuk, V
Ahmed, M
Al-Busaidi, A
Alchanatis, V
Aliabadi Farahani, H
Amaral, L.R
Archontoulis, S
Ashraf, E
Ashworth, A
Babar, I
Bajwa, S
Balasundram, S.K
Balboa, G
Balboa, G
Bareth, G
Bareth, G
Batchelor, W.D
Bazzi, C
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Beeri, O
Benő, A
Berdugo, C.A
Bernardi, A.C
Bettiol, G.M
Betzek, N.M
Bhansali, S
Blackmer, T.M
Bolten, A
Bonnardel, B
Boukhalfa, H
Bouroubi, Y
Bradford, J
Brand, H
Bruce, A.E
Brungardt, J.J
Burke, C.R
Burke, J
Burton, L
Callegari, D
Campana, M
Campos, L.B
Canata, T.F
Cao, Q
Chavan, H
Chen, M
Chen, Y
Chen, Y
Ciampitti, I
Ciampitti, I
Cisneros, M
Colaço, A.F
Colley III, R
Connor, J
Cosby, A
Cugnasca, C.E
Cushnahan, T
Dehne, H
Dehne, H
Dela Rue, B.T
Dela Rue, B.T
Dela Rue, B.T
Deng, W
Denton, A.M
Dimos, N.F
Dong, R
Dongare, M.L
Dornbusch, T
Draganova, I
Duncan, E
EMİNOĞLU, B.M
Eastwood, C
Erickson, B
Esau, K
Fajardo, M
Farooque, A
Ferguson, A
Ferguson, A
Finegan, M
Fiorio, P.R
Franzen, D.W
Franzen, J
Fraser, E
Frotscher, K.J
Fulton, J
Gómez, S
Gan, H
Gavioli, A
Gerighausen, H
Giselsson, T.M
Giselsson, T.M
Glewen, K
Gnyp, M.L
Gnyp, M.L
Gonzalez, J
Goorahoo, D
Grafton, M.C
Griffin, T
Griffin, T
Gérard, B
Han, Y.J
Howatt, K
Huang, S
Huang, Y
Hunt, E
Inamasu, R.Y
Irwin, M.E
Isakeit, T
J�??�?�¸rgensen, R.N
Jørgensen, R.N
Jadhav, B.T
Jago, J
Jago, J
Jago, J.G
Jansen, M
Jasper, J
Jasper, J
Jayachandran, K
Jayasuriya, H
Ji, Z
Kaiser, D
Kamphuis, C
Kamphuis, C
Kamphuis, C
Kaur, G
Kereszturi, G
Khalilian, A
Kharel, T
Khosla, R
Khosla, R
Khot, L
Knight, C.W
Koch, J.K
Kocsis, M
Kross, A
Kyveryga, P.M
Kyveryga, P.M
Laacouri, A
Lacroix, R
Lapen, D
Le Roux, M
Lebeau, F
Lee, J
Lee, W
Lenz-Wiedemann, V
Leroux, G.D
Li, M
Liakos, V
Liang, X
Lilienthal, H
Liu, J
Longchamps, L
Longchamps, L
Longchamps, L
Lowenberg-DeBoer, J
Luck, J
Magalhaes, P.G
Maharlooei, M
Mahlein, A
Maja, J.M
Mangus, D.L
Maréchal, P
Martello, M
Martello, M
Martinsson, J
Massinon, M
May-tal, S
McLendon, A
McNairn, H
McVeagh, P.J
McVeagh, P.J
Mekonnen, Y
Miao, Y
Miao, Y
Michelon, G.K
Midtiby, H.S
Midtiby, H.S
Mohd Hanif, A
Molin, J.P
Mostaço, G.M
Moulton, H
Mueller, N
Mulla, D
Mulla, D.J
Nichols, R.L
Nisa, M.U
Nowatzki, J
Nowatzki, J.F
Odvody, G.N
Oerke, E
Oerke, E
Oliveira, P.P
Ortiz-Monasterio, I
Owens, P
Pagani, A
Panitzki, M
Panneton, B
Patto Pacheco, E
Paulus, S
Payero, J.O
Pearson, R
Pennington, D
Perry, C
Piikki, K
Pimstein, A
Port, K
Porter, W
Portz, G
Prasad, V
Prasad, V
Pritsolas, J
Privette, C.V
Pullanagari, R.R
Puntel, L
Qian, J
Qiao, S
Qiao, X
Quirós, J.J
Rabello, L.M
Rasheed, R
Raz, J
Reddy, K
Reusch, S
Reusch, S
Rodrigues Jr., F.A
Rojo, F
Rondon, S.I
Rud, R
Rudy, H
SEYHAN, G.T
Sampson, T
Sanches, G.M
Sani, B
Sarwar, M
Sarwat, A
Schacht, R
Scharf, P
Schenatto, K
Schenatto, K
Schenatto, K
Schnug, E
Schulthess, U
Schumann, A
Seepersad, G
Seepersad, S
Shahzad, M.A
Shaligram, A.D
Sharda, A
Shinde, S
Shirzadi, A
Shurjeel, H.K
Siegfried, J
Simard, M
Sisák, I
Sivarajan, S
Smith, L
Souza, E
Souza, E.G
Souza, I.R
Stadig, H
Steiner, U
Steiner, U
Stenberg, M
Stevenson, M
Sun, C
Sunohara, M
Szabó, K
Söderström, M
TALEBPOUR, B
Tauqir, N.A
Thomasson, J.A
Thompson, L
Thomson, S.J
Tilly, N
Toledo, F.H
Tremblay, N
Trevisan, R.G
Trotter, M
Tucker, M
Turner, R.W
TÜRKER, U
Upadhyaya, S
Vadamalai, G
Valente, I.Q
Varela, S
Varela, S
Vellidis, G
Wallace, D
Wang, X
Whelan, B
White, M
Williams, E
Willis, L.A
Yang, C
Yang, Q
Yang, Q
Yang, X
Yao, Y
Yegul, U
Yuan, F
Yule, I
Yule, I
Yule, I.J
Yule, I.J
Zaman, Q
Zamzow, M
Zamzow, M
Zarco-Tejada, P.J
Zhang, Y
Zhao, C
Zhao, C
Zhao, T
Zhao, T
Zhou, J
Zillmann, E
Zur, Y
de Menezes, P.L
hassanijalilian, O
van Vliet, L
ÇOLAK, A
Topics
Remote Sensing Applications in Precision Agriculture
Decision Support Systems
Precision Crop Protection
Education and Outreach in Precision Agriculture
Small Holders and Precision Agriculture
Precision Dairy and Livestock Management
Type
Oral
Poster
Year
2016
2018
2012
2022
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Topics

Filter results82 paper(s) found.

1. Use of Non-Invasive Sensors to Detect Beneficial Effects of Fungicides on Wheat Physiology

Delay of leaf senescence is a beneficial side effect of fungicides several times studied on cereal crops. Strobilurins have been shown to extend the green leaf area duration (GLAD) for more than one week compared to untreated plants. The use of non-invasive sensors which allow to detect early changes in canopy pigmentation is an excellent method to assess the effect of fungicides on plant senescence. The objective of this study was to evaluate the effect of fungicides on wheat physiology by u... C.A. Berdugo, U. Steiner, E. Oerke, H. Dehne, A. Mahlein

2. Estimating the Plant Stem Emerging Points (PSEPS) of Sugar Beets at Early Growth Stages

Successful intra-row mechanical weed control of sugar beet (beta vulgaris) in early growth stages requires precise knowledge about location of crop plants. A computer vision system for locating Plant Stem Emerging Point (PSEP) of sugar beet in early growth stages was developed and tested. The system is based on detection of individual leaves; each leaf location is described by center of mass and petiole location. After leaf detection the true PSEP locations were annotated manually an... T.M. Giselsson, R.N. Jørgensen, H.S. Midtiby

3. Spatial Variability of Soil Properties in Intensively Managed Tropical Grassland in Brazil

For the intensification of tropical grass pastures systems the soil fertility building up by liming and balanced fertilization is necessary. The knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the variable rate application of lime and fertilizers. PA requires methods to indicate the spatial variability of soil and plant parameters. The objective of this work was to map and evaluate the soil properties and maps the site specific liming and fertil... G.M. Bettiol, R.Y. Inamasu, L.M. Rabello, A.C. Bernardi, M. Campana, P.P. Oliveira

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

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

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

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

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

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

7. Remote Collection of Behavioral and Physiological Data to Detect Lame Cows

Authors of abstract: C. Kamphuis, J. Burke, J. Jago ... J. Jago, J. Burke, C. Kamphuis, B. Dela rue

8. Two On-Farm Tests to Evaluate In-Line Sensors for Mastitis Detection

To date, there is no independent and uniformly presented information available regarding detection performance of automated in-line mastitis detection systems. This lack of information makes it hard for farmers ... B. Dela rue, J. Jago, C. Kamphuis

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

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

10. Modeling and Decision Support System for Precision Cucumber Protection in Greenhouses

The plant disease... X. Yang, C. Sun, J. Qian, Z. Ji, S. Qiao, M. Chen, C. Zhao, M. Li

11. Thermography as Sensor for Downy Mildew on Roses

Downy mildew caused by Peronospora sparsa is considered one of the most important diseases affecting cut roses under glass in the tropic. Under f... E. Oerke, H. Dehne, U. Steiner, S. Gómez

12. Field Evaluation of Automated Estrus Detection Systems - Meeting Farmers' Expectation

Automated systems for oestrus detection are commonly marketed as a suitable, or in some cases, a higher performing alternative to visual observation. Farmers, particularly those with larger herds relying on less experienced staff, view the perceived benefits of automated systems as both economic and physical, with expectations of improved oestrus detection efficiency with lower labour input. There is little evidence-based information available on the field performance of these systems to... B.T. Dela rue, C. Kamphuis, J.G. Jago, C.R. Burke

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

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

14. The Effect of Leaf Orientation on Spray Retention on Blackgrass

Spray application efficiency depends on the pesticide application method as well as target properties. A wide range of drop impact angles exists during the spray application process because of drop trajectory and the variability of the leaf orientation. As the effect of impact angle on retention is still poorly documented, laboratory studies were conducted... F. Lebeau, M. Massinon, P. Maréchal, H. Boukhalfa

15. BrainWeed - Teach-In System for Adaptive High Speed Crop / Weed Classification and Targeting

Conducting inter row mechanical weeding requires the precise location of each individual crop plant is known. One technique is to record the global position of each seed when sown using  RTK-GPS systems. An... R.N. JÃ???Ã??Ã?¸rgensen, H.S. Midtiby, T.M. Giselsson

16. Monitoring Soybean Root Development under Till-System Management (TSM) at Dry-Farming Conditions

Root system development is very importance for highest soybean (Glycine max L.) grain yield, especially under arid and semiarid conditions. In order to tillage system management (TSM) for achieved to the optimum yield of soybean in dry-farming cond... H. Aliabadi farahani, B. Sani

17. Challenges and Opportunities for Precision Dairy Farming in New Zealand.

A study was commissioned by DairyNZ, a dairy industry good organisation in New Zealand, to identify some of the key challenges and opportunities in the precision dairy space. In New Zealand there has been an increasing research focus on the use of information and communication technologies (ICT) ... I. Yule , C. Eastwood

18. The Use of Sensing Technologies to Monitor and Track the Behavior of Cows on a Commercial Dairy Farm

New Zealand farmers are facing rapidly increasing pressure to reduce nutrient losses from their farming enterprises to the environment caused by grazing ruminants. ... I. Draganova, I. Yule, M. Stevenson

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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

40. 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

41. 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

42. 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

43. 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

44. 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

45. 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

46. 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

47. 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

48. 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

49. 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

50. 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

51. 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

52. 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

53. 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

54. Refractive Index Based Brix Measurement System for Sugar and Allied Industries

An attempt has been made to design optimization of Refractormetric based method for the measurement of Brix.  Optimization of various constructional parameters including selection and location of source, prism and detector, position of source, angular position and height of source from prism plane, divergent angle of source, refractive index of prism, size of prism, the location of detector to pick up the optimum reflected light, refractive index of sample, critical angle, choice of suit... M.L. Dongare, B.T. Jadhav, A.D. Shaligram

55. From Data to Decisions - Ag Technologies Provide New Opportunities and Challenges with On-Farm Research

U.S. farmers are challenged to increase crop production while achieving greater resource use efficiency.  The Nebraska On-Farm Research Network (NOFRN), enables farmers to answer critical production, profitability, and sustainability questions with their own fields and equipment. The NOFRN is sponsored by the University of Nebraska – Lincoln Extension and derives from two separate on-farm research efforts, the earliest originating in 1990.  Over the course of the last 29 years... L. Thompson, K. Glewen, N. Mueller, J. Luck

56. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry Harvesting

Wild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the p... K. Esau, Q. Zaman, A. Farooque, A. Schumann

57. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?

This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed wit... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis

58. Learn, Share, Connect and Be Inspired: How One Farming Group in Australia is Driving PA Adoption

The use of Precision Agriculture (PA) technologies and techniques continues to expand in Australia. The Society of Precision Agriculture Australia (SPAA) has been instrumental in driving the adoption and development of these techniques to support industry and Australian farming communities. SPAA supports innovation, and innovation includes people. Founded in 2002, SPAA, a not for profit extension body, is Australia’s only dedicated farming group communicating and advocating fo... N.F. Dimos, J.K. Koch

59. Utilizing GPS Technology and Science to Improve Digital Literacy Among Students in Australia and the United States of America

A key issue facing regional, rural and remote communities, in both Australia and the United States of America (USA), is the low level of digital literacy among some cohorts of students. This is particularly the case for students involved in agricultural studies where it is commonly perceived that digital literacy is not relevant to their future occupation. However, this perception is far from the truth, as the reality of farming today means students who intend on entering the agricultural wor... C.W. Knight, A. Cosby, M. Trotter

60. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenou... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

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

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

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

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

63. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aire... L. Puntel, A. Pagani, S. Archontoulis

64. Field Test of a Satellite-Based Model for Irrigation Scheduling in Cotton

Cotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table a... O. Beeri, S. May-tal, J. Raz, R. Rud

65. Variable Selection and Data Clustering Methods for Agricultural Management Zones Delineation

Delineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster anal... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto

66. Creating Thematic Maps and Management Zones for Agriculture Fields

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

67. Data Power: Understanding the Impacts of Precision Agriculture on Social Relations

Precision agriculture has been greatly promoted for the potential of these technologies to sustainably intensify food production through increasing yields and profits, decreasing the environmental impacts of production, and improving food safety and transparency in the food system through the data collected by precision agriculture technologies.  However, little attention has been given to the potential of these technologies to impact social relations within the agricultural industry.&nb... E. Duncan, E. Fraser

68. Field Grown Apple Nursery Tree Plant Counting Based on Small UAS Imagery Derived Elevation Maps

In recent years, growers in the state are transitioning to new high yielding, pest and disease resistant cultivars. Such transition has created high demand for new tree fruit cultivars. Nursery growers have committed their incoming production of the next few years to meet such high demands. Though an opportunity, tree fruit nursery growers must grow and keep the pre-sold quantity of plants to supply the amount promised to the customers. Moreover, to keep the production economical amidst risin... M. Martello, J.J. Quirós, L. Khot

69. Optimising Nitrogen Use in Cereal Crops Using Site-Specific Management Classes and Crop Reflectance Sensors

The relative cost of Nitrogen (N) fertilisers in a cropping input budget, the 33% Nitrogen use efficiency (NUE) seen in global cereal grain production and the potential environmental costs of over-application are leading to changes in the application rates and timing of N fertiliser. Precision agriculture (PA) provides tools for producers to achieve greater synchrony between N supply and crop N demand. To help achieve these goals this research has explored the use of management classes derive... B. Whelan, M. Fajardo

70. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor Networks

Mobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is ta... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza

71. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast China

The objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla

72. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water f... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

73. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in Oman

Agriculture under arid environment is always become a challenge due to water scarcity and salinity problems.  With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstractio... H. Jayasuriya, A. Al-busaidi, M. Ahmed

74. Harness the Power of the Internet to Improve Yield

It’s rare to find a fertile farm or ranch that has complete cellular coverage across the entirety of its property. Because networking options like Wi-Fi are limited by restricted infrastructure in these areas, maintaining a reliable flow of connectivity is difficult. Yet, even if consistent cellular coverage is available, it’s frequently cost prohibitive for farm monitoring. Similarly, alternate wireless devices that require batteries aren’t practical because of high mainten... M. Finegan, D. Wallace

75. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of th... J. Lee, J. Fulton, K. Port, R. Colley iii

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

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

77. Exploring Wireless Sensor Network Technology in Sustainable Okra Garden: A Comparative Analysis of Okra Grown in Different Fertilizer Treatments

The goal of this project was to explore commercial agricultural and irrigation sensor kits and to discern if the commercial wireless sensor network (WSN) is a viable tool for providing accurate real-time farm data at the nexus of food energy and water. The smart garden consists of two different varieties of Abelmoschus esculentus (okra) planted in raised beds, each grown under two different fertilizer treatments. Soil watermark sensors were programed to evaluate soil moisture and dictate irri... L. Burton, K. Jayachandran, S. Bhansali, Y. Mekonnen, A. Sarwat

78. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. ... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

79. Precision Agriculture: A Paradigm Shift for Espousal of Advanced Farming Practices Among Progressive Farmers in Punjab –Pakistan

Precision agriculture provides innovative farm information tools for improved decision making regarding crop growth and yield. Creating awareness for future applications of precision agriculture among progressive farmers in Pakistan was an instrumental force to conduct this study. The purpose was to appraise the awareness level of the respondents for applications of precision agriculture in the field. The objectives such as assessing the awareness level, available information sources, future ... E. Ashraf, H.K. Shurjeel, R. Rasheed

80. Low Cost Smartphone Camera Accessory to Digitally Measure Leaf Color for Crop Nitrogen Status Assessment

Crop nitrogen (N) status is a desirable information for crop nutrition management. In addition to the traditional leaf sampling with subsequent laboratory analysis, the use of chlorophyll meters is a well-studied and accepted practice to indirectly measure crop N status. Nevertheless, chlorophyll meters are dedicated devices that still cost at least a few hundred dollars, thus being unsuitable to large scale use among low budget smallholders. Aiming to address this issue, a new low cost smart... G. Portz, S. Reusch, J. Jasper

81. Evaluating How Operator Experience Level Affects Efficiency Gains for Precision Agricultural Tools

Tractor guidance (TG) improve environmental gains relative to non-precision technologies; however, studies evaluating how tractor operator experience for non-guidance comparisons impact gains are nonexistent. This study explores spatial relationships of overlaps and gaps with operator experience level (0-1; 2-3; 6+ years) during fertilizer and herbicide applications based on terrain attributes.  Tractor paths recorded by global navigation satellite systems were used to create overlap pol... A. Ashworth, T. Kharel, P. Owens

82. Farmer Charlie - Low Cost Data Analytics for Farmers Accessible in the Field

Farmer Charlie, a spin-off of AB5 Consulting Ltd, is based on an affordable business model including five elements: a data analytics platform, an agribusiness ecosystem app, capable of connecting with local third-party apps; weather and in field sensors; wi-fi Internet connectivity; and power to the field and farms via solar panels, where necessary. Farmer Charlie brings information to farmers in their own fields, in an easy plug and play solution, affordable to the farmers and addressing the... B. Bonnardel