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Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
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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
Apolo-Apolo, E
Beeri, O
Beeri, O
Beeri, O
Biswas, A
Biswas, A
Biswas, A
Blasch, G
Brant, V
Buelvas, R
Buelvas, R.M
Callegari, D
Cambouris, A
Cambouris, A
Cambouris, A
Cambouris, A
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
Darrozes, J
Diago, M
Diago, M
Drechsler, K
Dreyer, J
Drummond, S.T
Dyrmann, M
Dyrmann, M
Egea, G
Eitelwein, M.T
Eriksen, J
Esau, T
Fang, H
Farooque, A
Feng, H
Feritas Colaço, A
Fernandez-Novales, J
Ferraz, M.N
Fuentes, C.L
Gan, H
Germain, C
Germain, C
Gerth, S
Gerth, S
Gislum, R
Gislum, R
Gonçalves Trevisan, R
Goyer, C
Gross, B
Gu, X
Gu, X
Gutierrez, S
Hafferman, A
Harsányi, E
Haymann, N
Heggemann, T
Hoerfarter, R
Hoffmann Silva Karp, F
Hülsbergen, K.J
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
Kim, Y
Kisekka, I
Kitchen, N.R
Kodaira, M
Koszinski, S
Kraska, T
Krcek, V
Kross, A
Kroulik, M
Lai, C
Lajili, A
Lapen, D
Laursen, M.S
Laursen, M.S
Leclerc, M
Lee, S
Lee, W.S
Leenen, M
Leksono, E
Leksono, E
Levitan, N
Li, S
Li, Z
Liu, J
Maidl, F.X
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
Moreda, E.A
Moreda, E.A
Morgan, S
Muller, O
Nagy, J
Najvirt, D
Nault, J
Neupane, S
Novais, W
Palacios, F
Pelta, R
Pelta, R
Perez-Ruiz, M
Perret, J.S
Perron, I
Perron, I
Perron, I
Perron, I
Pessl, G
Pieger, K
Pieruschka, R
Pilz, C
Pingle, V
Potrpin, J
Pätzold, S
Qian, B
Ragán, P
Randriamanga, D
Rascher, U
Raz, J
Raz, Y
Rodriguez, J.C
Rosu, R
Rozenstein, O
Rud, R
Rud, R
Rudy, H
Rátonyi, T
Schmidt, K
Scholz, O
Schurr, U
Shang, J
Shibusawa, S
Shibusawa, S
Skerikova, M
Skovsen, S
Skovsen, S
Skovsen, S
Song, X
Steier, A
Strenner, M
Sudduth, K.A
Sunohara, M
Swe, K.M
Tabatabai, S
Tanny, J
Tardaguila, J
Tardaguila, J
Taylor, J.A
Trevisan, R.G
Uhlmann, N
Uhrmann, F
Upadhyaya, S
Vargas, F
Villalobos, J.E
Vories, E.D
Vántus, A
Wang, S
Welp, 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
van Vliet, L
Ágnes, T
Topics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Poster
Oral
Year
2018
Home » Topics » Results

Topics

Filter results50 paper(s) found.

1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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

40. 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

41. 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

42. 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

43. 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

44. 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

45. 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

46. 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

47. 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

48. 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

49. 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

50. 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