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Vincent, G
Ziadi, N
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Authors
Nze Memiaghe, J
Cambouris, A.N
Ziadi, N
Duchemin, M
Karam, A
Cambouris, A
Duchemin, M
Ziadi, N
Vincent, G
Kudenov, M
Balint-Kurti, P
Dean, R
Williams, C.M
Cambouris, A
Duchemin, M
Lord, E
Ziadi, N
Javed, B
Nze Memiaghe, J.D
Ramirez-Gonzalez, D.A
Nze Memiaghe, J
Cambouris, A
Duchemin, M
Ziadi, N
Karam, A
Javed, B
Cambouris, A
Smith, E
Dandrifosse, S
Ziadi, N
Karam, A
Topics
Decision Support Systems
In-Season Nitrogen Management
Artificial Intelligence (AI) in Agriculture
On Farm Experimentation with Site-Specific Technologies
Land Improvement and Conservation Practices
Precision Agriculture for Sustainability and Environmental Protection
Type
Oral
Poster
Year
2022
2024
2026
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Filter results6 paper(s) found.

1. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn Production

Phosphorus (P) is an essential nutrient for crops production including corn. However, the excessive P application, tends to P accumulation at the soil surface under crops systems. This may contribute to increase water and groundwater pollution by surface runoff. To prevent this, an agri-environmental P index, (P/Al)M3, was developed in Eastern Canada and USA. This index aims to estimate soil P saturation for accurate P fertilizer recommendations, while integrating agronomical aspects... J. Nze Memiaghe, A.N. Cambouris, N. Ziadi, M. Duchemin, A. Karam

2. Nitrogen Fertilization of Potato Using Management Zone in Prince Edward Island, Canada

Potato is sensible to nitrogen (N) and optimal N fertilization improve the tuber yield and its quality. Potato crop N response varies widely within fields. It is also well recognized that significant spatial and temporal variation in soil N availability occurs within crop fields. However, uniform application of N fertilizer is still the most common practice under potato production. Management zone (MZ) approach can help growers to achieve a part of this. The goal of the project is to compare the... A. Cambouris, M. Duchemin, N. Ziadi

3. Utilizing Hyperspectral Field Imagery for Accurate Southern Leaf Blight Severity Grading in Corn

Crop disease detection using traditional scouting and visual inspection approaches can be laborious and time-consuming. Timely detection of disease and its severity over large spatial regions is critical for minimizing significant yield losses. Hyperspectral imagery has been demonstrated as a useful tool for a broad assessment of crop health.  The use of spectral bands from hyperspectral data to predict disease severity and progression has been shown to have the capability of enhancing early... G. Vincent, M. Kudenov, P. Balint-kurti, R. Dean, C.M. Williams

4. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision Experimentation

Assessing the spatial variability of soil properties represents an important issue for on-farm sustainable management owing to high cost of sampling densities. Actual methods of soil properties measurement are based on conventional soil sampling of one sample per ha, followed by laboratory analysis, requiring many soil extraction processes and harmful chemicals. This conventional laboratory analysis does not allow exploring spatial variation of soil properties at desired fine spatial scale. Thus,... A. Cambouris, M. Duchemin, E. Lord, N. Ziadi, B. Javed, J.D. Nze Memiaghe, D.A. Ramirez-gonzalez

5. Delineating Management Zones for Optimizing Soil Phosphorus Recommendations Under a No Till Field in Eastern Canada

Corn (Zea mays L.) and soybean (Glycine max L.) represent the most common crop rotation in Eastern Canada. These crops are cultivated using no-tillage (NT) practice to enhance agroecosystem sustainability. However, NT practice can cause several agri-environmental issues related to phosphorus (P) stratification, movement and runoff leading to P eutrophication in waters. Another major challenge is the expensive costs of extensive soil sampling and laboratory tests needed for accurate... J. Nze Memiaghe, A. Cambouris, M. Duchemin, N. Ziadi, A. Karam

6. Machine Learning–driven Insights into Nitrogen Dynamics and Greenhouse Gas Emissions in Potato Production Systems

Nitrogen (N) is an essential nutrient for potato vegetative growth, yet it remains one of the most challenging elements to manage in modern agricultural systems. Despite its critical role in crop productivity, excessive or poorly timed N application can lead to significant environmental losses, particularly through groundwater nitrate (NO3-N) leaching and emissions of nitrous oxide (N2O), a greenhouse gas approximately 300 times more potent than CO2. Therefore,... B. Javed, A. Cambouris, E. Smith, S. Dandrifosse, N. Ziadi, A. Karam