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Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Remote Sensing for Nitrogen Management
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Guidance, Robotics, Automation, and GPS Systems
Farm Animals Health and Welfare Monitoring
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Authors
Abd-Elrahman, A
Abdalla, K
Abdelghafour, F
Abdelghafour, F.Y
Acebron, K
Adamchuk, V
Adamchuk, V
Adamchuk, V
Adamchuk, V
Adamchuk, V
Adamchuk, V
Adamchuk, V.I
Alchanatis, V
Ameglio, L
Ameglio, L
Andrae, J
Apolo-Apolo, E
Backman, J
Badarch, L
Bai, X
Balkcom, K
Beeri, O
Beeri, O
Beeri, O
Ben-Halevi, I
Bennur, P
Berenstein, R
Biswas, A
Biswas, A
Biswas, A
Blasch, G
Blocker, A.K
Brant, V
Brorsen, B.W
Buelvas, R
Buelvas, R.M
Callegari, D
Cambouris, A
Cambouris, A
Cambouris, A
Cambouris, A
Carvalho, R
Carvalho, R
Cheng, Z
Cheng, Z
Chiang, R
Chokmani, K
Chokmani, K
Christiansen, M.P
Chung, S
Chyba, J
Claussen, J
Claußen, J
Cocciardi, R
Csatári, N
Da Costa, J
Da Costa, J
Dallago, G.M
Dallago, G.M
Dallago, G.M
Dallago, G.M
Darrozes, J
Diago, M
Diago, M
Domingues, G
Drechsler, K
Dreyer, J
Drummond, S.T
Dutra, R
Dyrmann, M
Dyrmann, M
Edan, Y
Egea, G
Eitelwein, M.T
Eriksen, J
Esau, T
Fageria, N.K
Fang, H
Farooque, A
Feng, H
Feritas Colaço, A
Fernandez-Novales, J
Ferraz, M.N
Figueiredo, D.M
Fuentes, C.L
Fulton, J.P
Gailums, A
Gan, H
Gao, L
Germain, C
Germain, C
Gerth, S
Gerth, S
Gislum, R
Gislum, R
Godinho, R
Godinho, R
Gonçalves Trevisan, R
Goyer, C
Gross, B
Gu, X
Gu, X
Guimarães, M
Guimarães, M
Gutierrez, S
Hafferman, A
Ham, W
Harsányi, E
Hatfield, J.L
Haymann, N
Heggemann, T
Hoerfarter, R
Hoffmann Silva Karp, F
Hu, H
Hu, J
Hülsbergen, K.J
Inamasu, R
Inamasu, R.Y
Jedmowski, C
Jeong, D
Ji, W
Ji, W
Jing, Q
Jørgensen, R.N
Jørgensen, R.N
Jørgensen, R.N
Kabir, M.S
Kaplan, G
Karp, F.H
Karstoft, H
Kaur, G
Keller, B
Keresztes, B
Keresztes, B
Khosla, R
Kim, Y
Kisekka, I
Kitchen, N.R
Kodaira, M
Kormann, G
Koszinski, S
Kraska, T
Krcek, V
Kross, A
Kroulik, M
Kwon, H
Lacroix, R
Lai, C
Lajili, A
Lapen, D
Laursen, M.S
Laursen, M.S
Leclerc, M
Lee, S
Lee, W.S
Leenen, M
Lefebvre, D
Leksono, E
Leksono, E
Levitan, N
Li, S
Li, T
Li, Z
Liu, J
Liu, X
Lobo Júnior, A
Lobo Júnior, A
Longchamps, L
Lopes, W
Lopes, W.C
Maidl, F.X
Maja, J.M
Marin-Barrero, C
Marmette, M
Martinez-Guanter, J
May-tal, S
McNairn, H
Meng, J
Meng, J
Mey-tal, S
Mey-tal, S
Mills, A
Min, C
Mohamed, M.M
Molin, J
Molin, J.P
Molin, J.P
Moreda, E.A
Moreda, E.A
Morgan, S
Mueller, J
Mueller, S
Mullen, R.W
Muller, O
Nagy, J
Najvirt, D
Nault, J
Neupane, S
Novais, W
Oksanen, T
Ortiz, B.V
Pacheco, G.B
Palacios, F
Panneton, B
Pelta, R
Pelta, R
Pentjuðs, A
Pereira, R.R
Perez-Ruiz, M
Perret, J.S
Perron, I
Perron, I
Perron, I
Perron, I
Pessl, G
Phillips, S.B
Pieger, K
Pieruschka, R
Pilz, C
Pingle, V
Porto, A
Porto, A.J
Potrpin, J
Pätzold, S
Qian, B
Ragán, P
Randriamanga, D
Rascher, U
Raun, W.R
Raun, W.R
Raun, W.R
Raz, J
Raz, Y
Rennó, L.N
Roberts, D.C
Rodriguez, J.C
Rosu, R
Rozenstein, O
Rud, R
Rud, R
Rudy, H
Rátonyi, T
Santos, A.B
Santos, R.A
Santos, R.A
Schmidt, J.P
Schmidt, K
Scholz, O
Schurr, U
Sell, S.G
Shang, J
Shibusawa, S
Shibusawa, S
Silveira, R.R
Silveira, R.R
Skerikova, M
Skovsen, S
Skovsen, S
Skovsen, S
Solie, J.B
Solie, J.B
Song, X
Sousa, R
Sousa, R.V
Spekken, M
Sripada, R.P
Steier, A
Stone, H
Strenner, M
Stuckey, E.G
Sudduth, K.A
Sunohara, M
Swe, K.M
Tabatabai, S
Tanny, J
Tardaguila, J
Tardaguila, J
Taylor, J.A
Taylor, R.K
Thomason, W.E
Trevisan, R.G
Tronco, M
Tumenjargal, E
Tuttle, G
Uhlmann, N
Uhrmann, F
Upadhyaya, S
Vargas, F
Vasseur, E
Vellidis, G
Vieira, J.A
Villalobos, J.E
Visala, A
Vories, E.D
Vántus, A
Wang, N
Wang, S
Warner, D
Weckler, P
Welp, G
Werner, R
Westfall, D.G
Whalen, J
Whitney, S
Wörlein, N
Xu, X
Xu, X
Yang, C
Yang, G
Yang, G
Yang, X
Zabransky, P
Zaman, Q
Zebarth, B
Zebarth, B
Zebarth, B
Zebrath, B
Zendonadi, N
Zimmermanm, L
Znoj, E
da Silva, L.D
da Silva, L.D
de Azevedo, K.K
de Azevedo, K.K
de Figueiredo, D.M
de Sousa, M.G
van Vliet, L
vanSanten, E
Ágnes, T
Topics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Farm Animals Health and Welfare Monitoring
Guidance, Robotics, Automation, and GPS Systems
Remote Sensing for Nitrogen Management
Type
Poster
Oral
Year
2018
2012
2008
Home » Topics » Results

Topics

Filter results73 paper(s) found.

1. 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 developme... E. Tumenjargal, L. Badarch, W. Ham, H. Kwon

2. Path Generation Method with Steering Rate Constraint

The practical way to generate a reference path in path tracking is to follow an adjacent swath. However, if the adjacent swath contains sharp turnings, the reference path will eventually contain sharper turn than the tractor is able to follow. This occurs especially in the corner of a field plot when the field is driven around. In the headland, the objective is to minimize the time to reach the next swath. The commonly known method to generate the shortest path between two arbitrary... J. Backman, T. Oksanen, A. Visala

3. Research on Straight-Line Path Tracking Control Methods in an Agricultural Vehicle Navigation System

In the precision agriculture (PA), an agricultural vehicle navigation system is essential and precision of the vehicle path tracking is of great importance in such a system. As straight line operation is the main way of agricultural vehicles on large fields, this paper focuses on the discussion of straight-line path tracking control methods and proposes an agricultural vehicle path tracking algorithm based on the optimal control theory. First, the paper deduces a relative kinematics model of ... T. Li, J. Hu, L. Gao, H. Hu, X. Bai, X. Liu

4. Path Tracking Control of Tractors and Steerable Towed Implements Based On Kinematic and Dynamic Modeling

recise path tracking control of tractors became the enabling technology for automation of field work in recent years. More and more sophisticated control systems for tractors however revealed that exact positioning of the actual implement is equally or even more important. Especially sloped and curved terrain, strip till fields, buried drip irrigation tapes and high-value crop... G. Kormann, S. Mueller, R. Werner

5. 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

6. Optimizing Path Planning By Avoiding Short Corner Tracks

... J.P. Molin, M. Spekken

7. A Remote Interface for a Human-Robot Cooperative Vineyard Sprayer

... Y. Edan, R. Berenstein, I. Ben-halevi

8. Improvement Precision Agricultural Communication Schema agroXML Based on Multi-Agents System's Deliberation and Decision Making Processes

... A. Pentjuðs, A. Gailums

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

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

10. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields

  ... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten

11. Compatible ISOBUS Applications Using a Computational Tool for Support the Phases of the Precision Agriculture Cycle

... W.C. Lopes, G. Domingues, R.V. Sousa, A.J. Porto, R.Y. Inamasu, R.R. Pereira

12. Nitrogen Management in Lowland Rice

Rice is staple diet for more than fifty percent of the world population and nitrogen (N) deficiency is one of the major yields limiting constraints in most of the rice producing soils around the world. The lowland rice N recovery efficiency is <50% of applied fertilizers in most agro-ecological regions. The low N efficiency is associated with losses caused by leaching, volatilization, surface runoff, and denitrification. Hence, improving N use efficiency is crucial for higher yields, low c... N.K. Fageria, A.B. Santos

13. Prediction of Nitrogen Needs with Nitrogen-rich Strips and Ramped Nitrogen Strips

Both nitrogen rich strips and ramped nitrogen strips have been used to estimate topdress nitrogen needs for winter wheat based on in-season optical reflectance data. The ramped strip system places a series of small plots in each field with increasing levels of nitrogen to determine the application rate at which predicted yield response to nitrogen reaches a plateau. The nitrogen-rich strip system uses a nitrogen fertilizer optimization algorithm based on optical reflectance measures from the ... D.C. Roberts, B.W. Brorsen, W.R. Raun, J.B. Solie

14. Spatial Patterns of Nitrogen Response Within Corn Production Fields

Corn (Zea mays L.) yield response to nitrogen (N) application is critical to being able to develop management practices that reduce N application or improve N use efficiency. Nitrogen rate studies have been conducted within small plots; however, there have been few field scale evaluations. This study was designed to evaluate N response across 14 corn fields in central Iowa using different rates of N applied in strips across fields. These fields ranged in size from 15 to 130 ha with N... J.L. Hatfield

15. Developing Nitrogen Algorithms for Corn Production Using Optical Sensors

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

16. Variability in Observed and Sensor Based Estimated Optimum N Rates in Corn

Recent research showed that active sensors such as Crop Circle can be used to estimate in-season N requirements for corn. The objective of this research was to identify sources of variability in the observed and Crop Circle-estimated optimum N rates. Field experiments were conducted at two locations for a total of five sites during the 2007 growing season using a randomized complete block design with increasing N rates applied at V6-V8 (NV6) as the treatment factor. Field sites were selected ... R.P. Sripada, J.P. Schmidt

17. 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 r... R.K. Taylor, P. Bennur, J.B. Solie, N. Wang, P. Weckler, W.R. Raun

18. Estimating Cotton Water Requirements Using Sentinel-2

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management.  Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance.  In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse.  Kc was estimated as the ratio between reference evapotrans... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny

19. Soil Microbial Communities Have Distinct Spatial Patterns in Agricultural Fields

Soil microbial communities mediate many important soil processes in agricultural fields, however their spatial distribution at distances relevant to precision agriculture is poorly understood. This study examined the soil physico-chemical properties and topographic features controlling the spatial distribution of soil microbial communities in a commercial potato field in eastern Canada using next generation sequencing. Soil was collected from a transect (1100 m) with 83 sampling points in a l... B. Zebarth, C. Goyer, S. Neupane, S. Li, A. Mills, S. Whitney, A. Cambouris, I. Perron

20. Understanding Temporal and Spatial Variation of Soil Available Nutrients with Satellite Remote Sensing

Soil available nutrients are the key determinants in crop growth, field stable output and ecological balance. The soil nutrients loss and surplus can strongly influence the stability of field ecological environment and cause unnecessary pollution. Hence, optimizing the status of soil available nutrients status has significant ecological and economic significance. With the advancement of mechanized farming and control technologies, soil available nutrients can be optimize by variable rate fert... J. Meng, H. Fang, Z. Cheng

21. Development of a Small Tracking Device for Cattle Using IoT Technology

The US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef.  This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the c... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae

22. Mapping Cotton Plant Height Using Digital Surface Models Derived from Overlapped Airborne Imagery

High resolution aerial images captured from unmanned aircraft systems (UASs) are recently being used to measure plant height over small test plots for phenotyping, but airborne images from manned aircraft have the potential for mapping plant height more practically over large fields. The objectives of this study were to evaluate the feasibility to measure cotton plant height from digital surface models (DSMs) derived from overlapped airborne imagery and compare the image-based estimates with ... C. Yang

23. An Active Thermography Method for Immature Citrus Fruit Detection

Fast and accurate methods of immature citrus fruit detection are critical to building early yield mapping systems. Previously, machine vision methods based on color images were used in many studies for citrus fruit detection. Despite the high resolutions of most color images, problems such as the color similarity between fruit and leaves, and various illumination conditions prevented those studies from achieving high accuracies. This project explored a novel method for immature citrus fruit d... H. Gan, W.S. Lee, V. Alchanatis, A. Abd-elrahman

24. A Precision Management Strategy on Soil Mapping

With the experience of field mapping practice during the last decade, a simple conclusion of four-level-field-management strategy was summarized. Level 1 was to describe the spatio-temporal variability of the fields, such as soil mapping and yield/quality mapping, and then to recognize the evidence in the field. Level 2 was to understand why the variability came out with help of farmers’ experience, such as mushing up of the date, memorizing the work history and the environmental condit... S. Shibusawa

25. Multi-Temporal Yield Pattern Analysis - Adaption of Pattern Recognition to Agronomic Data

In precision agriculture, the understanding of yield variability, both spatial and temporal, can deliver essential information for the decision making of site-specific crop management. Since commercial yield mapping started in the early 1990s, most research studies have focused on spatial variance or short-term temporal variance analyzed statistically in order to produce trend maps. Nowadays, longer records of high-quality yield data are available offering a new potential to evaluate yield va... G. Blasch, J.A. Taylor

26. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, Canada

Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction se... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath

27. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning Algorithms

Machine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expen... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre

28. The Animal Welfare of Dairy Cows Housed in Free-Stall Barn According to the Welfare Quality® Protocol: Good Feeding and Good Housing Principles

The objective of the present study was to evaluate the animal welfare of dairy cows according to good feeding and good housing principles of the Welfare Quality® protocol. The protocol was applied to animals kept confined in a free-stall barn during their lactation. The farm was located in São João Batista do Glória, Minas Gerais state - Brazil. One hundred and one animals were evaluated (47 primiparous and 54 multiparous). The welfare measures were collected mostly t... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

29. Developing an Integrated Approach for Estimation of Soil Available Nutrient Content Using the Modified WOFOST Model and Time-Series Multispectral UAV Observations

Soil available nutrient (SAN) plays an important role in crop growth, yield formation, and plant-soil-atmosphere system exchange. Nitrogen (N), phosphorus (P) and potassium (K) are recognized as three primary nutrients in crop production. Accurate and timely information on SAN conditions at key crop growth stages is important for developing beneficial management practices. While traditional field sampling can obtain reliable information for limited number of sites, it is infeasible for spatia... Z. Cheng, J. Meng, J. Shang, J. Liu, B. Qian, Q. Jing

30. Assessment of the Information Content in Solar Reflective Satellite Measurements with Respect to Crop Growth Model State Variables

To increase the utilization of satellite remote sensing data in precision agriculture, it is necessary to retrieve the most relevant variables from the satellite signals so that the retrievals can be directly utilized by agricultural management entities. The variables that make up the state vector description of existing crop growth models provide inherent relevance to on-farm decision making because they can be used to predict future crop status based on changing farm inputs. In this study, ... N. Levitan, B. Gross

31. Data Fusion of Imagery from Different Satellites for Global and Daily Crop Monitoring

Satellite-based Crop Monitoring is an important tool for decision making of irrigation, fertilization, crop protection, damage assessment and more. To allow crop monitoring worldwide, on a daily basis, data fusion of images taken by different satellites is required. So far, most researches on data fusion focus on retrospective analysis, while advanced crop monitoring capabilities mandate the use of data in real time mode. Therefore, our project goals were: (1) to build a data-fusion online sy... O. Beeri, R. Pelta, S. Mey-tal, J. Raz

32. Joint Structure and Colour Based Parametric Classification of Grapevine Organs from Proximal Images Through Several Critical Phenological Stages

Proximal colour imaging is the most time and cost-effective automated technology to acquire high-resolution data describing accurately the trellising plane of grapevine. The available textural information is meaningful enough to provide altogether the assessment of additional agronomic parameters that are still estimated either manually or with dedicated and expensive instrumentations. This paper proposes a new framework for the classification of the different organs visible in the trellising... F.Y. Abdelghafour, R. Rosu, B. Keresztes, C. Germain, J. Da costa

33. The Correlation Between Criteria from Welfare Quality® Protocol Applied to Dairy Cows Housed in Free-Stall Barn

The objective of this study was to evaluate correlations between animal welfare criteria from the Welfare Quality® protocol applied to dairy cows. The protocol was applied on 47 primiparous and 54 multiparous dairy cows housed in a free-stall barn located in São João Batista do Glória, Minas Gerais - Brazil. Twelve welfare criteria were obtained from mostly animal-based welfare measures as proposed by the protocol. Pearson correlation coefficients (r) were calculated ... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

34. Designated Value for a Field Polygon Based on Imagery Data: A Case Study of Crop Vigor in Agricultural Application for Irrigation

Any irrigation action for a field management zone, which is based on images, requires a transformation into single value. Since data distribution is ab-normal in an image, using a mean value to estimate the crop coefficient (Kc), an overlaid polygon may not represent properly its water demand. Therefore, this project’s aim was to examine to which extent different statistics of potential designated values will affect an estimated Kc, and consequently affect irrigation practices. ... R. Rud, O. Beeri, S. Mey-tal

35. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping Applications

Currently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the parti... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen

36. Nitrogen Sensing by Using Spectral Reflectance Measurements in Cereal Rye Canopy

Cereal rye (cereale secale L.) is a winter crop well suited for cultivation especially besides high yield areas because of its relatively low demands on the soil and on the climate as well. In 2016 about 4.9% of arable land in Germany was cultivated with cereal rye (Statistisches Bundesamt, 2017). Unlike other crops such as wheat, there is little research on cereal rye for site specific farming. Furthermore, also in a cereal rye cultivation it is necessary to minimize nitrogen loss.... M. Strenner, F.X. Maidl, K.J. Hülsbergen

37. Delineation of Site-Specific Nutrient Management Zones to Optimize Rice Production Using Proximal Soil Sensing and Multispectral Imaging

Evaluating nutrient uptake and site-specific nutrient management zones in rice in Costa Rica from plant tissue and soil sampling is expensive because of the time and labor involved.  In this project, a range of measurement techniques were implemented at different vintage points (soil, plant and UAVs) in order to generate and compare nutrient management information.  More precisely, delineation of site-specific nutrient management zones were determined using 1) georeferenced soil/tis... J.E. Villalobos, J.S. Perret, K. Abdalla, C.L. Fuentes, J.C. Rodriguez, W. Novais

38. Real-Time Fruit Detection Using Deep Neural Networks

Proximal imaging using tractor-mounted cameras is a simple and cost-effective method to acquire large quantities of data in orchards and vineyards. It can be used for the monitoring of vegetation and for the management of field operations such as the guidance of smart spraying systems for instance. One of the most prolific research subjects in arboriculture is fruit detection during the growing season. Estimations of fruit-load can be used for early yield assessments and for the monitoring of... B. Keresztes, J. Da costa, D. Randriamanga, C. Germain, F. Abdelghafour

39. A Comprehensive Stress Index for Evaluating Plant Water Status in Almond Trees

This study evaluated a comprehensive plant water stress index that integrates the canopy temperature and the environmental conditions that can assist in irrigation management. This index—Comprehensive Stress Index (CSI)—is based on the reformulation of the leaf energy balance equation. Specifically, CSI is the ratio of the temperature difference between a dry leaf (i.e. a leaf with a broken stem) and a live leaf (on the same tree) [i.e. Tdry-Tleaf] and the difference between the v... K. Drechsler, I. Kisekka, S. Upadhyaya

40. Two-Layer Multiple Soil-Property Mapping Measured with a Real-Time Soil Sensor

We obtained calibration models for 32 soil properties based on Vis-NIR (350 - 1700 nm) underground soil diffuse reflectance spectra collected using a real-time soil sensor (SAS3000) with a DGPS system, in order to generate soil property maps. We have previously demonstrated one-layer soil maps for soil management decision making by growers; however, for effective crop management, growers often wish to obtain complex layer information for their fields. Thus, in the present study, we measured t... M. Kodaira, S. Shibusawa

41. Proximal Soil Sensing-Led Management Zone Delineation for Potato Fields

A fundamental aspect of precision agriculture or site-specific crop management is the ability to recognize and address local changes in the crop production environment (e.g. soil) within the boundaries of a traditional management unit. However, the status quo approach to define local fertilizer need relies on systematic soil sampling followed by time and labour-intensive laboratory analysis. Proximal soil sensing offers numerous advantages over conventional soil characterization and has shown... A. Biswas, W. Ji, I. Perron, A. Cambouris, B. Zebarth, V. Adamchuk

42. Farm Soil Moisture Mapping Using Reflected GNSS SNR Data Onboard Low Level Flying Aircraft

Soil moisture/water content monitoring (spatial and temporal) is a critical component of farm management decision primarily for crop/plant growth and yield improvement, but also for optimization of practice such as tillage and field treatments. Satellite humidity probes do not deliver the relevant resolution for farming purposes. Ground moisture probes only provide punctual measurements and do not reflect the true spatial variability of soil moisture. Previous studies have demonstra... L. Ameglio, J. Darrozes, J. Dreyer

43. Detecting Variability in Plant Water Potential with Multi-Spectral Satellite Imagery

Irrigation Intelligence is a practice of precise irrigation, with the goal of providing crops with the right amount of water, at the right time, for optimized yield. One of the ways to achieve that, on a global scale, is to utilize Landsat-8 and Sentinel-2 images, providing together frequent revisit cycles of less than a week, and an adequate resolution for detection of 1 ha plots. Yet, in order to benefit from these advantages, it is necessary to examine the information that can be extracted... O. Beeri, S. May-tal, R. Rud, Y. Raz, R. Pelta

44. Review of Developments in Airborne Geophysics and Geomatics to Map Variability of Soil Properties

Over the past 40 years, airborne geophysics and geomatics has become an effective and accepted technology for mapping various signatures on the Earth’s surface and sub-surface. But so far, its airborne application in agriculture is perceived as sub-practical and/or its real value unknown to most stakeholders. In this paper, we are reviewing major technical and commercial achievements and latest developments to date, but also potentials for new developments and applications, of airb... L. Ameglio

45. Sensor Comparison for Yield Monitoring Systems of Small-Sized Potato Harvesters

Yield monitoring of potato in real time during harvesting would be useful for farmers, providing instant yield and income information. In the study, potentials of candidate sensors were evaluated with different yield measurement techniques for yield monitoring system of small-sized potato harvesters. Mass-based (i.e., load cell) and volume-based (i.e., CCD camera) sensors were selected and tested under laboratory conditions. For mass-based sensing, an impact plate instrumented with load cells... K.M. Swe, Y. Kim, D. Jeong, S. Lee, S. Chung, M.S. Kabir

46. On-the-Go Nir Spectroscopy and Thermal Imaging for Assessing and Mapping Vineyard Water Status in Precision Viticulture

New proximal sensing technologies are desirable in viticulture to assess and map vineyard spatial variability. Towards this end, high-spatial resolution information can be obtained using novel, non-invasive sensors on-the-go. In order to improve yield, grape quality and water management, the vineyard water status should be determined. The goal of this work was to assess and map vineyard water status using two different proximal sensing technologies on-the-go: near infrared (NIR) reflectance s... J. Tardaguila, M. Diago, S. Gutierrez, J. Fernandez-novales, E.A. Moreda

47. Quantification of Seed Performance: Non-Invasive Determination of Internal Traits Using Computed Tomography

The application of the 3D mean-shift filter to 3D Computed Tomography Data enables the segmentation of internal traits. Specifically in maize seeds this approach gives the opportunity to separate the internal structure, for example the volume of the embryo, the cavities and the low and high dense parts of the starch body. To evaluate the mean-shift filter, the results were compared to the usage of a median-smoothing filter. To show the relevance of the mean-shift extended image pipeline an au... J. Claussen, N. Wörlein, N. Uhlmann, S. Gerth

48. Innovative Assessment of Cluster Compactness in Wine Grapes from Automated On-the-Go Proximal Sensing Application

Grape cluster compactness affects berry ripening homogeneity, fungal disease incidence, grape composition and wine quality. Therefore, assessing cluster compactness is crucial for sorting wine grapes for the wine industry. Nowadays, cluster compactness assessing methodology is based either on visual inspection performed by trained evaluators (OIV method) or on morphological features of clusters. The goal of this work was to develop an innovative and automated, non-destructive method to assess... J. Tardaguila, F. Palacios, M. Diago, E.A. Moreda

49. Examining the Relationship Between SPAD, LAI and NDVI Values in a Maize Long-Term Experiment

In Hungary, the preconditions for the use of precision crop production have undergone enormous development over the last five years. RTK coverage is complete in crop production areas. Consultants are increasingly using the vegetation index maps from Landsat and Sentinel satellite data, but measurements with on-site proximal plant sensors are also needed to exclude the influence of the atmosphere. The aim of our studies was to compare the values measured by proximal plant sensors in ... P. Ragán, E. Harsányi, J. Nagy, T. Ágnes, T. Rátonyi, A. Vántus, N. Csatári

50. 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 for... S. Skovsen, M. Dyrmann, J. Eriksen, R. Gislum, H. Karstoft, R.N. Jørgensen

51. 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 annota... M. Dyrmann, S. Skovsen, R.N. Jørgensen, M.S. Laursen

52. Canopy Parameters in Coffee Orchards Obtained by a Mobile Terrestrial Laser Scanner

The application of mobile terrestrial laser scanner (MTLS) has been studied for different tree crops such as citrus, apple, olive, pears and others. Such sensing system is capable of accurately estimating relevant canopy parameters such as volume and can be used for site-specific applications and for high throughput plant phenotyping. Coffee is an important tree crop for Brazil and could benefit from MTLS applications. Therefore, the purpose of this research was to define a field protocol for... F. Hoffmann silva karp, A. Feritas colaço, R. Gonçalves trevisan, J.P. Molin

53. Machine Monitoring As a Smartfarming Concept Tool

Current development trends are associated with the digitization of production processes and the interconnection of individual information layers from multiple sources into common databases, contexts and functionalities. In order to automatic data collection  of machine operating data, the farm tractors were equipped with monitoring units ITineris for continuous collection and transmission of information from tractors CAN Bus. All data sets are completed with GPS location data. Acrea... M. Kroulik, V. Brant, P. Zabransky, J. Chyba, V. Krcek, M. Skerikova

54. Compensating for Soil Moisture Effects in Estimation of Soil Properties by Electrical Conductivity Sensing

Bulk apparent soil electrical conductivity (ECa) is the most widely used soil sensing modality in precision agriculture. Soil ECa relates to multiple soil properties, including clay content (i.e., texture) and salt content (i.e., salinity). However, calibrations of ECa to soil properties are not temporally stable, due in large part to soil moisture differences between measurement dates. Therefore, the objective of this research was to investigate the effects of temporal soil moisture variatio... K.A. Sudduth, N.R. Kitchen, E.D. Vories, S.T. Drummond

55. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter Wheat

Nitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization mana... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng

56. Precision Agriculture Research Infrastructure for Sustainable Farming

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

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

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

58. Ground Vehicle Mapping of Fields Using LiDAR to Enable Prediction of Crop Biomass

Mapping field environments into point clouds using a 3D LIDAR has the ability to become a new approach for online estimation of crop biomass in the field. The estimation of crop biomass in agriculture is expected to be closely correlated to canopy heights. The work presented in this paper contributes to the mapping and textual analysis of agricultural fields. Crop and environmental state information can be used to tailor treatments to the specific site. This paper presents the current results... M.P. Christiansen, M.S. Laursen, R.N. Jørgensen, S. Skovsen, R. Gislum

59. Soybean Plant Phenotyping Using Low-Cost Sensors

Plant phenotyping techniques are important to present the performance of a crop and it interaction with the environment. The phenotype information is important for plant breeders to analyze and understand the plant responses from the ambient conditions and the inputs offered for it. However, for conclusive analysis it is necessary a large number of individuals. Thus, phenotyping is the bottleneck of plant breeding, a consequence of the labor intensive and costly nature of the classical phenot... M.N. Ferraz, R.G. Trevisan, M.T. Eitelwein, J. Molin, F.H. Karp

60. Evaluation of Nutrient Intake in Sheep Fed with Increasing Levels of Crambe Meal (Crambe Abyssinica Hoscht)

The objective of this study was to evaluate the effects of increasing levels of crude protein (CP) substitution of the concentrate by CP of crambe meal (CM) (0, 25, 50 and 75% dry matter basis) on consumption of nutrients. Four rumen fistulated and castrated sheep (18 months old on average and initial body weight of 50 kg) were used distributed in a 4 x 4 Latin square design with 4 treatments and 4 experimental periods (repetitions). Diets were balanced to meet requirements for minimum gains ... K.K. De azevedo, D.M. De figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, R.A. Santos

61. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude Protein

The objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein ... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco

62. Mapping Leaf Area Index of Maize in Tasseling Stage Based on Beer-Lambert Law and Landsat-8 Image

Leaf area index (LAI) is one of the important structural parameters of crop population, which could be used to monitor the variety of crop canopy structure and analyze photosynthesis rate. Mapping leaf area index of maize in a large scale by using remote sensing technology is very important for management of fertilizer and water, monitoring growth change and predicting yield. The Beer-Lambert law has been preliminarily applied to develop inversion model of crop LAI, and has achieved good appl... X. Gu, S. Wang, G. Yang, X. Xu

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

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

64. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-base... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet

65. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning ... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

66. Towards Universal Applicability of On-the-Go Gamma-Spectrometry for Soil Texture Estimation in Precision Farming by Using Machine Learning Applications

High resolution soil data are an essential prerequisite for the application of precision farming techniques. Sensor-based evaluation of soil properties may replace or at least reduce laborious, time-consuming and expensive soil sampling with subsequent measurements in the lab. Gamma spectrometry usually provides information that can be translated into topsoil texture data after calibration. This is because the natural content of the radioactive isotopes 40-K, 232-Th, and 238-U as we... S. Pätzold, T. heggemann, M. Leenen, S. Koszinski, K. Schmidt, G. Welp

67. Main Stream Precision Farming - 7.000 VRA Maps for Winter Rapeseed

SEGES is owned by the Danish farmers and is an agricultural advisory centre advising landowners with a total of 2.1 mill hectare. One of SEGES’s goals is to make precision farming mainstream. One step in the process of making precision farming mainstream was in 2016 to give all farmers access to the free internet application CropSAT.dk. Here farmers can make variable rate application (VRA) maps based on satellite data from Sentinel-2. But this is not enough to m... R. Hoerfarter

68. Development of a Soil ECa Inversion Algorithm for Topsoil Depth Characterization

Electromagnetic induction (EMI) proximal soil sensor systems can deliver rapid information about soil. One such example is the DUALEM-21S (Dualem, Inc. Milton, Ontario, Canada). EMI sensors measure soil apparent electrical conductivity (ECa) corresponding to different depth of investigation depending on the instrument configuration. The interpretation of the ECa measurements is not straightforward and it is often site-specific. Inversion is required to explore specific depths. This inversion ... E. Leksono, V. Adamchuk, W. Ji, M. Leclerc

69. Laser Triangulation for Crop Canopy Measurements

From a Precision Agriculture perspective, it is important to detect field areas where variabilities in the soil are significant or where there are different levels of crop yield or biomass. Information describing the behavior of the crop at any specific point in the growing season typically leads to improvements in the manner the local variabilities are addressed. The proper use of dense, in-season sensor data allows farm managers to optimize harvest plans and shipment schedules under variabl... R.M. Buelvas, V.I. Adamchuk

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

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

71. Development of a Manual Soil Sensing System for Measuring Multiple Chemical Soil Properties in the Field

Variable Rate Fertilizer Application (VRA) requires the input of soil chemical data. One of the preferred methods for analyzing soil chemical properties in the field is by using Ion Selective Electrodes (ISEs). To accommodate portability in soil measurements, a manual soil sampling system was developed. Nitrate, Phosphate and pH ISEs were integrated to provide a general outlook on the condition of essential soil nutrients. These ISEs were placed on a modified hand-held soil sampler equip... E. Leksono, V. Adamchuk, J. Whalen, R. Buelvas

72. Optical High-Resolution Camera System with Computer Vision Software for Recognizing Insects, Fruit on Trees, Growth of Crops

With the inspiration of helping the farmer to grow his crop in the optimal way, Pessl Instruments GmbH, from Weiz, Austria, developed optical high-resolution camera system, together with a computer vision software which is able to recognize insects, fruits on trees and growth of crop. Pessl Instruments develops decision support system which is consisting from remote monitoring of insect traps and remote monitoring of fields and crops. Optical high-resolution camera system can be installed on ... J. Potrpin, G. Pessl, D. Najvirt, C. Pilz

73. Design of Ground Surface Sensing Using RADAR

Ground sensing is the key task in harvesting head control system. Real time sensing of field topography under vegetation canopy is very challenging task in wild blueberry cropping system. This paper presents the design of an ultra-wide band RADAR sensing, scanning device to recognize the soil surface level under the canopy structure. Requirements for software and hardware were considered to determine the usability of the ultra-wide band RADAR system.An automated head ... M.M. Mohamed, Q. Zaman, T. Esau, A. Farooque