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Choi, J
Morellas, V
Camberato, J
McClintick-Chess, J
Squires, T
Ulman, M
Van Den Wyngaert, L
Swanson, G
Strickland, E.E
Shinde, S
Le-Khac, N
Mahmood, S
Martin, R
Silva, R.P
Lejealle, S
Saberioon, M
Cranfield, G
Song, X
Owens, P
Cointault, F
Mishra, A.R
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Authors
Gholizadeh , A
Mohd Soom , M
Saberioon, M
Cointault, F
Gouton, P
Billiot, B
Song, X
Zhao, C
Chen, L
Huang, W
Cui, B
Ehsani, R
Salyani, M
Maja, J.M
Mishra, A.R
Larbi, P.A
Camargo Neto, J
Goffart, J
Leonard, A
Buffet, D
Defourny, P
Van Den Wyngaert, L
Cointault, F
Hijazi, B
Dubois, J
Vangeyte, J
Paindavoine, M
Lejealle, S
Cointault, F
Marin, A
Journaux, L
Miteran, J
Martin, R
Morris, E
Clarke, A
Sunley, S
Hill, C
Cranfield, G
Dong, Y
Wang, Y
Song, X
Gu, X
Borùvka, L
Saberioon, M
Vašát, R
Gholizadeh, A
Schepers, J.S
Mclure, B
Swanson, G
Gholizadeh, A
Saberioon, M
Borůvka, L
Song, X
Yang, G
Ma, Y
Wang, R
Yang, C
Walsh, O.S
Belmont, K
McClintick-Chess, J
Marshall, J
Jackson, C
Thompson, C
Swoboda, K
Walsh, O.S
Belmont, K
McClintick-Chess, J
Mulla, D
Zermas, D
Kaiser, D
Bazakos, M
Papanikolopoulos, N
Stanitsas, P
Morellas, V
Jarolimek, J
Stočes, M
Ulman, M
Vaněk, J
Sung, N
Chung, S
Kim, Y
han, K
Choi, J
Kim, J
Cho, Y
Jang, S
Bauer, P.J
Stone, K.C
Bussher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Ngo, V.M
Le-Khac, N
Kechadi, M
Xu, X
Li, Z
Yang, G
Gu, X
Song, X
Yang, X
Feng, H
Kitchen, N.R
Yost, M.A
Ransom, C.J
Bean, G
Camberato, J
Carter, P
Ferguson, R
Fernandez, F
Franzen, D
Laboski, C
Nafziger, E
Sawyer, J
Laamrani, A
Berg, A
March, M
McLaren, A
Martin, R
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Oliveira, M.F
Morata, G.T
Ortiz, B
Silva, R.P
Jimenez, A
Karampoiki, M
Todman, L
Mahmood, S
Murdoch, A
Paraforos, D
Hammond, J
Ranieri, E
Oliveira, L.P
Ortiz, B.V
Morata, G.T
Squires, T
Jones, J
Ashworth, A
Kharel, T
Owens, P
Topics
Sensor Application in Managing In-season Crop Variability
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Engineering Technologies and Advances
Precision A-Z for Practitioners
Modeling and Geo-statistics
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Sensor Application in Managing In-season Crop Variability
Unmanned Aerial Systems
Precision Crop Protection
Engineering Technologies and Advances
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Applications of Unmanned Aerial Systems
Decision Support Systems
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Small Holders and Precision Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Authors

Filter results29 paper(s) found.

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

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

2. New Power-leds Based Illumination System For Fertilizer Granule Motion Estimation

Environmental problems have become more and more pressing in the past twenty years particularly with the fertilization operation, one main contributor to environmental imbalance. The understanding of the global centrifugal spreading process, most commonly used in Europe, can contribute to provide essential information about fertiliser granule deposition on the soil. This last one can be predicted using a ballistic flight model and several fertilizer characteristic’s determination... F. Cointault, B. Hijazi, J. Dubois, J. Vangeyte, M. Paindavoine

3. Multiplex : A New Diagnostic Tool For Management Of Nitrogen Fertilization Of Turfgrass

Multiplex is a fluorescence-based optical sensor that measures in real time and in vivo the leaf content of compounds such as chlorophyll and several families of polyphenols (anthocyanins, flavonoïds, hydroxycinnamic acids). We propose here to show that the measurement of leaf chlorophyll and flavonoïd content permits us to evaluate nitrogen status of turfgrass. Actually, experiments have shown that chlorophyll content increases whereas flavonoïd content decreases with increased... S. Lejealle

4. Wheat Growth Stages Discrimination Using Generalized Fourier Descriptors In Pattern Recognition Context

... F. Cointault, A. Marin, L. Journaux, J. Miteran, R. Martin

5. Attaching Multiple Conductivity Meters To An Atv To Speed Up Precision Agriculture Soil Surveys

Ground conductivity meters are used in a number of precision agriculture applications, including the estimation of water content, nutrient levels, salinity and depth of topsoil. Typically the Geonics EM38 conductivity meter, and to a lesser extent the EM31, are used for soil surveys. Most conductivity surveys involve towing a ground conductivity meter behind an all-terrain vehicle (ATV). In some situations, such as rutted or sloping fields, it is preferable to mount the conductivity meter directly... E. Morris, A. Clarke, S. Sunley, C. Hill, G. Cranfield

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

Many methods are available to monitor nitrogen content of rice during various growth stages. However, this monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera (ADC) was used to acquire high spatial and temporal resolution in order to determine the status of nitrogen (N) and predict the grain yield of rice (Oriza sativa L.). In this study, 12 pots of rice with four different N treatments (0, 125,... A. Gholizadeh , M. Mohd soom , M. Saberioon

7. 3D Acquisition System Applied to Agronomic Scenes

To enable a better decision making by the farmer in order to optimize the crop management, it is essential to provide a set of information on basic parameters of the crops. These information are numerous and the image processing is increasingly used for disease detection, weed detection or yield estimation. We will focus initially on assessing the yield of a wheat crop in automatic way. This yield is directly related to the number of ears per square meter for which the counting is currently... F. Cointault, P. Gouton, B. Billiot

8. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

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

9. Young Leaf Detection for Spot Spray Treatment of Citrus Canopies to Control Psyllids

Huanglongbing (HLB) is an important disease of citrus that is spread mainly through a vector, psyllid (Diaphorina citri), that feeds predominantly on young leaves.  Given the selective feeding of the insect, treating only the young flush, instead of spraying the entire... R. Ehsani, M. Salyani, J.M. Maja, A.R. Mishra, P.A. Larbi, J. Camargo neto

10. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial Information

Farmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farmland.... Y. Dong, Y. Wang, X. Song, X. Gu

11. Visible And Near-Infrared Spectroscopy For Monitoring Potentially Toxic Elements In Reclaimed Dumpsite Soils Of The Czech Republic

Due to rapid economic development, high levels of potentially harmful elements and heavy metals are continuously being released into the brown coal mining dumpsites of the Czech Republic. Elevated metal contents in soils not only dramatically impact the soil quality, but also due to their persistent nature and long biological half-lives, contaminant elements can accumulate in the food chain and can eventually endanger human health. Conventional methods for investigating potentially... L. Borùvka, M. Saberioon, R. Vašát, A. Gholizadeh

12. Beyond The 4-Rs Of Nutrient Management In Conjunction With A Major Reduction In Tillage

Agribusiness and government agencies have embraced the 4-R concept (right form, rate, time, and place) to improve nutrient management and environmental quality. No-tillage... J.S. Schepers, B. Mclure, G. Swanson

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

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

14. Spatial and Temporal Variation of Soil Nitrogen Within Winter Wheat Growth Season

This study aims to explore the spatial and temporal variation characteristics of soil ammonium nitrogen and nitrate nitrogen within winter wheat growth season. A nitrogen-rich strip fertilizer experiment with eight different treatments was conducted in 2014. Soil nitrogen samples of 20-30cm depth near wheat root were collected by in-situ Macro Rhizon soil solution collector then soil ammonium nitrogen and nitrate nitrogen content determined by SEAL AutoAnalyzer3 instrument. Classical statistics... X. Song, G. Yang, Y. Ma, R. Wang, C. Yang

15. UAV-based Crop Scouting for Precision Nutrient Management

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

16. Sensor-based Technologies for Improving Water and Nitrogen Use Efficiency

 Limited reports exist on identifying the empirical relationships between plant nitrogen and water status with hyperspectral reflectance. This project is aiming to develop effective system for nitrogen and water management in wheat. Specifically: 1) To evaluate the effects of nitrogen rates and irrigation treatments on wheat plant growth and yield; 2) To develop methods to predict yield and grain protein content in varying nitrogen and water environments, and to determine the minimum nitrogen... O.S. Walsh, K. Belmont, J. Mcclintick-chess

17. Early Detection of Nitrogen Deficiency in Corn Using High Resolution Remote Sensing and Computer Vision

The continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the detection and characterization of Nitrogen (N) deficiencies in corn fields. Current methods of field surveillance are either completed manually or with the assistance of satellite imaging, which offer... D. Mulla, D. Zermas, D. Kaiser, M. Bazakos, N. Papanikolopoulos, P. Stanitsas, V. Morellas

18. Technology Support for Game Monitoring As a Tool for Damages Reduction of Field Crops

Wild boars (Sus scrofa) are increasingly becoming the main cause of field crops damage in Czech Republic and central Europe area. There are many reasons why wild boars population is growing. The major reason is most likely change in the composition of field crops. In some areas in particular there is focus on oilseed rape and maize, for which there are also recorded the biggest losses. One of the key discussion topics is the issue of estimation of animal quantities and its traceability.... J. Jarolimek, M. Stočes, M. Ulman, J. Vaněk

19. Evaluation of a Sensor and Control Interface Module for Monitoring of Greenhouse Environment

Protected horticulture in greenhouses and plant factories has been increased in many countries due to the advantages of year-round production in controlled environment for improved productivity and quality. For protected horticulture, environmental conditions are monitored and controlled through wired and wireless devices. Various devices are used for monitoring and control of spatial and temporal variability in crop growth environmental conditions. Recently, various sensors and control devices,... N. Sung, S. Chung, Y. Kim, K. Han, J. Choi, J. Kim, Y. Cho, S. Jang

20. Site-specific Irrigation of Peanuts on a Coastal Plain Field

Irrigator-Pro is an expert system that prescribes irrigation for corn (Zea mays L.), cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea). We conducted an experiment in 2007 to evaluate Irrigator-Pro as a tool for variable rate irrigation of peanut using a site-specific center pivot irrigation system. Treatments were irrigation of whole plots based on the expert system, irrigation of individual soils within plots based on the expert system, irrigation of individual...

21. An Efficient Data Warehouse for Crop Yield Prediction

Nowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi

22. 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 managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng

23. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer Response

Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer

24. Use of UAV Acquired Imagery As a Precision Agriculture Method for Measuring Crop Residue in Southwestern Ontario, Canada

Residue management on agriculture land is a practice of great importance in southwestern Ontario, where soil management practices have an important effect on Great Lakes water quality. The ability of tillage or planting system to maintain soil residue cover is currently measured by using one or more of the common methods, line transect (e.g. knotted rope, Meter stick) and photographic (grid, script, and image analysis) methods. Each of these techniques has various advantages and disadvantages;... A. Laamrani, A. Berg, M. March, A. Mclaren, R. Martin

25. 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. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

26. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez

27. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri

28. Is Row-unit Vibration Affected by Planter Speeds and Downforce?

Row-unit vibration is an issue created mainly by planter`s opening disks and gauge-wheels contact with the ground. Variability on row-unit vibration could interfere on seed metering and delivery process, affecting crop emergence and final stand. With the amount of embedded technology present on planters, producers are being encouraged to increase planting speeds, which is also one of the main factors for row-unit vibration increasement. In this way, knowing the proper speeds, and using other instruments... L.P. Oliveira, B.V. Ortiz, G.T. Morata, T. Squires, J. Jones

29. 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 polygons.... A. Ashworth, T. Kharel, P. Owens