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Jurado-Expósito, M
Silverman, N
Schepers, J
Soni, R
Trevisan, R
Tremblay, N
Henties, T
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Authors
Zhang, Y
Tremblay, N
Schepers, J
Holland, K.H
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
Garcia-Torres, L
López-Granados, F
deCastro, A.I
Pattey, E
Jego, G
Tremblay, N
Drury, C
Ma, B
Sansoulet, J
Beaudoin, N
Tremblay, N
Vigneault, P
Bouroubi, M.Y
Dorais, M
Gianquinto, G.P
Tempesta, M
Vigneault, P
Tremblay, N
Bouroubi, M.Y
Belec, C
Fallon, E
Anselmi, A.A
Molin, J.P
eitelwein, M.T
Trevisan, R
Colaço, A
Tremblay, N
Khun, K
Vigneault, P
Bouroubi, M.Y
Cavayas, F
Codjia, C
Morris, T
Tremblay, N
Kyveryga, P.M
Clay, D.E
Murrell, S
Ciampitti, I
Thompson, L
Mueller, D
Seger, J
Kumar, S
Singh, M
Mirzakhaninafchi, H
Modi, R.U
Ali, M
Bhardwaj, M
Soni, R
Maxwell, B.D
Bekkerman, A
Silverman, N
Payn, R
Sheppard, J
Izurieta, C
Davis, P
Hegedus, P.B
Morris, T
Tremblay, N
Khun, K
Vigneault, P
Fallon, E
Tremblay, N
Codjia, C
Cavayas, F
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Cook, S
Lacoste, M
Evans, F
Tremblay, N
Adamchuk, V
Scholz, O
Uhrmann, F
Weule, M
Meyer, T
Gilson, A
Makarov, J
Hansen, J
Henties, T
Topics
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Remote Sensing Applications in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Precision Horticulture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Spatial Variability in Crop, Soil and Natural Resources
Unmanned Aerial Systems
Standards & Data Stewardship
Small Holders and Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Applications of Unmanned Aerial Systems
Decision Support Systems
Workshops
Robotics and Automation with Row and Horticultural Crops
Type
Oral
Poster
Year
2010
2012
2014
2016
2018
2024
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Filter results16 paper(s) found.

1. Evaluation Of The Multiplex® Fluorescence Sensor For The Assessment Of Corn Nitrogen Status

The Multiplex® is a new hand-held optical fluorescence sensor for non-destructive measurement of about 20 parameters descriptive of plant physiological status. The Multiplex is of potential value for in-season assessment of crop nitrogen status, but no evaluation has been released for that matter as of yet. An experiment was therefore conducted which consisted of four nitrogen fertilization treatments with 0, 20, 50... Y. Zhang, N. Tremblay

2. Active Sensor For Real-time Determination Of Soil Organic Matter

  Soil organic matter influences chemical and physical properties in the root zone as well as soil biological activity and plant vigor. As such, it is reasonable to assume that there are probably opportunities for producers to incorporate soil organic matter concentration information into their management decisions. However, soil organic matter is usually notoriously variable within fields. An active sensor based on in-soil reflectance was developed to provide apparent real-time... J. Schepers, K.H. Holland

3. Position Error of Input Prescription Map Delineated From Remote Images

     The spatial variability of biotic factors... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, L. Garcia-torres, F. López-granados, A.I. Decastro

4. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate Variations

Improving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and seeding... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin

5. Remote Sensing of Nitrogen and Water Status on Boston Lettuce Transplants in a Greenhouse Environment

Remote sensing is the stand-off collection through the use of a variety of devices for gathering information on a given object or area. Applied as a warning tool in plant stock production, it is expected to help in the achievement of better, more uniform and more productive organic cropping systems. Remote sensing of vegetation targets can be achieved from the... N. Tremblay, P. Vigneault, M.Y. Bouroubi, M. Dorais, G.P. Gianquinto, M. Tempesta

6. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In Corn

A number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon

7. Positioning Strategy of Maize Hybrids Adjusting Plant Population by Management Zones

Choice of hybrid and accurate amount of plants per area determines grain yield and consequently net incomes. Local field adjustment in plant population is a strategy to manage spatial variability and optimize environmental resources that are not under farmer control (like soil type and water availability). This study aims to evaluate the response of hybrids by levels of plant population across management zones (MZ). Six different hybrids and five rates of plant populations were analyzed starting... A.A. Anselmi, J.P. Molin, M.T. Eitelwein, R. Trevisan, A. Colaço

8. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in Corn

Remotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia

9. Rationale for and Benefits of a Community for On-Farm Data Sharing

Most data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger

10. Practical and Affordable Technologies for Precision Agriculture in Small Fields: Present Status and Scope in India

The objective of this review paper is to find out practical and affordable precision agriculture(PA) technologies present status and scope in India that are suitable for small fields. The judicious use of inputs like water, fertilizers, herbicides, pesticides and better management of farm equipments will increase the net profit for farmers. The important components of PA in India which are being used for small lands are Geographic Information System(GIS), laser land leveler, leaf color chart,... S. Kumar, M. Singh, H. Mirzakhaninafchi, R.U. Modi, M. Ali, M. Bhardwaj, R. Soni

11. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?

Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management strategies... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus

12. Draft Privacy Guidelines and Proposal Outline to Create a Field-Scale Trial Data Repository for Data Collected by On-Farm Networks

Implementing better management practices in corn and soybeans that increase profitability and reduce pollution caused by the practices requires large numbers of field-scale, replicated trials. Numerous complex and often unmeasurable interactions among the environment, genetics and management at the field scale require large numbers of trials completed at the field scale in a systematic and uniform manner to enable calculation of probabilities that a practice will be an improvement compared with... T. Morris, N. Tremblay

13. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial Vehicle

Above-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas

14. 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

15. On-Farm Experimentation and Decision-Support Workshop

This 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta-analyses... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk

16. Creating a Comprehensive Software Framework for Sensor-driven Precision Agriculture

Robots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if their... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties