Proceedings

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O'Sullivan, N
Rousseau, J
Burns, J
Godinho, R
Khakbazan, M
Jia, M
Roberts, A
Giriyappa, M
Chang, Y.K
Pearson , R
Kocsis, M
Livens, S
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Authors
Greer, K
Burns, J
Bremer, E
Zaman, Q
Esau, T.J
Farooque, A.A
Schumann, A.W
Percival, D.C
Chang, Y.K
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Douche, H
Rousseau, J
Kyveryga, P.M
Blackmer, T.M
Pearson , R
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Moulin, A
Khakbazan, M
Delauré, B
Baeck, P
Blommaert, J
Delalieux, S
Livens, S
Sima, A
Boonen, M
Goffart, J
Jacquemin, G
Nuyttens, D
Moulin, A
Khakbazan, M
Khakbazan, M
Moulin, A
Huang, J
Michiels, P
Xie, R
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Sisák, I
Benő, A
Szabó, K
Kocsis, M
Abonyi, J
King, W
Dynes, R
Laurenson, S
Zydenbos, S
MacAuliffe, R
Taylor, A
Manning, M
Roberts, A
White, M
Dhal, S
Louis, J
O'Sullivan, N
Gumero, J
Soetan, M
Kalafatis, S
Lusher, J
Mahanta, S
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Lord, E
Boatswain Jacques, A.A
Diallo, A.B
Khakbazan, M
Cambouris, A
Asgedom, H
Hehar, G
Willness, C
Anderson, W
Duddu, H
Mooleki, P
Schoenau, J
Khakbazan, M
Lemke, R
Derdall, E
Shang, J
Liu, K
Sulik, J
Karppinen, E
Mbakwe, I
Topics
Modeling and Geo-statistics
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Unmanned Aerial Systems
Site-Specific Nutrient, Lime and Seed Management
Profitability and Success Stories in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Site-Specific Pasture Management
Decision Support Systems
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results18 paper(s) found.

1. Oenoview : Bringing Remote Sensing To Wine Quality

  Oenoview is born in 2006 from the partnership between Infoterra, an EADS Astrium company specialised in earth observation and the Institut Cooperatif de Vin, a French company of services for the wine industry. Oenoview is an operating precision viticulture service, dedicated to vine monitoring, harvest optimisation and input management. In France, this service implemented in 2009 on a commercial scale is now used by clients as different as large... H. Douche, J. Rousseau

2. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within Fields

Using uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) deficiencies of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Digital aerial imagery taken later during the growing season is more accurate in identifying areas deficient in N. Even so, the quantitative use of late-season DAI across many fields is still limited because the imagery is not truly calibrated. This study... P.M. Kyveryga, T.M. Blackmer, R. Pearson

3. Evaluation of PRS(TM) Probe Technology and Model for Variable Rate Fertilizer Application in Hummocky Fields in Saskatchewan

... K. Greer, J. Burns, E. Bremer

4. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry Fields

An automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang

5. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

6. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular India

               Groundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi

7. Statistical Variability of Crop Yield, Soil Test N and P Within and Between Producer’s Fields

Soil test N and P significantly affect crop production in the Canadian Prairies, but vary considerably within and between producer's fields.  This study describes the variability of crop yield, soil test N and P within and between producer's fields in the context of variable fertilizer rates.  Yield, terrain attribute, soil test N and P data were collected for 10 fields in Alberta, Saskatchewan and Manitoba Canada in 2014 and 2015.  The influence of fertilizer... A. Moulin, M. Khakbazan

8. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera System

The COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitoring... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens

9. Spatial Variability of Canola Yield Related to Terrain Attributes Within Producer's Fields

Canola production in the Canadian Prairies varies considerably within and between producer's fields.  This study describes the variability of crop yield in producer's fields in the context of terrain attributes, and in relation to fertilizer rates in management zones determined from historical yield.  Canola yield data were collected for 27 fields in Alberta, Saskatchewan and Manitoba Canada in 2014, 2015, 2016 and 2017.  Several terrain attributes accounted for a considerable... A. Moulin, M. Khakbazan

10. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case Study

Precision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are described... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie

11. 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 through... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

12. 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 between... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

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

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

14. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm Profitability

Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White

15. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-up

The concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta

16. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia

17. Deep Learning for Predicting Yield Temporal Stability from Short Crop Rotations

Investigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris

18. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management Zones

Investment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed with... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe