Proceedings
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| Filter results15 paper(s) found. |
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1. The Effect Of Variable-Rate Fertilizer Nitrogen Decision-Making On Winter WheatPrecision ... J. Guo, L. Chen, X. Wang, R. Zhang, L. Zotarelli |
2. Detection Of Drainage Failure In Reconstructed Cranberry Soils Using Time Series AnalysisA cranberry farm is often a semi-closed water system, where water is applied by means of irrigation and drained using an artificial drainage system. Cranberry bogs must be drained to the water level inside the surrounding ditches in order to maintain an optimal pore pressure within the root zone, which is important for a number of reasons. First of all, Phytophthara causing root rot are commonly associated with irrigation with contaminated surface water (Oudemans, 1999)... S.J. Gumiere, Y. Périard, J. Caron, D.W. Hallema, J.A. Lafond |
3. Precision Agriculture Techniques for Crop Management in Trinidad and Tobago: Methodology & Field LayoutAgriculture in Trinidad and Tobago has not advanced at the same rate at which new agricultural technology has been released. This has led to large-scale abandonment of crop lands as challenges posed by labor availability and their agronomic capability could not meet the technological demands for agricultural production, competitiveness and sustainability. There is an urgent need to develop technology-based agriculture models to meet the demands of a modern agricultural sector and to maintain its... G. Seepersad, T. Sampson, S. Seepersad, D. Goorahoo |
4. Knowledge-based Approach for Weed Detection Using RGB ImageryA workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, wild... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu |
5. Establishment of a Canola Emergence Assessment Methodology Using Image-based Plant Count and Ground Cover AnalysisManual assessment of emergence is a time-consuming practice that must occur within a short time-frame of the emergence stage in canola (Brassica napus). Unmanned aerial vehicles (UAV) may allow for a more thorough assessment of canola emergence by covering a wider scope of the field and in a more timely manner than in-person evaluations. This research aims to calibrate the relationship between emerging plant population count and the ground cover. The field trial took place at the University... K. Krys, S. Shirtliffe, H. Duddu, T. Ha, A. Attanayake, E. Johnson, E. Andvaag, I. Stavness |
6. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn ProductionPhosphorus (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 |
7. Nitrogen Fertilization of Potato Using Management Zone in Prince Edward Island, CanadaPotato 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 |
8. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato ProductionIn modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam |
9. Mapping Marginal Crop Land on Millions of Acres in the Canadian PrairiesCrop fields cover more than 250,000 km2 of the Canadian Prairies, and many of these contain areas of marginal soil condition that are farmed annually at a loss. Setting aside these unprofitable areas may represent savings for growers as well as reductions in GHG emissions, while restoring them with perennial vegetation could create new natural carbon sinks. There is high potential for these in-field marginal zones to act as a nature-based climate solution in Alberta, Saskatchewan and Manitoba.... S. Shirtliffe, T. Ha, K. Nketia |
10. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane FeedstockPredicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland |
11. Utilizing Hyperspectral Field Imagery for Accurate Southern Leaf Blight Severity Grading in CornCrop 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 |
12. Digital Agriculture Driven by Big Data Analytics: a Focus on Spatio-temporal Crop Yield Stability and Land ProductivityIn the ever-evolving landscape of agriculture, the adoption of digital technologies and big data analytics has ushered in a transformative era known as digital agriculture. This paradigm shift is primarily motivated by the pressing imperative to address the growing global population's food requirements, mitigate the adverse effects of climate change, and promote sustainable land management. Canada, a significant player in global food production, has made a substantial commitment to reducing... K. Nketia, T. Ha, H. Fernando, S. Shirtliffe, S. Van steenbergen |
13. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision ExperimentationAssessing 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 |
14. Delineating Management Zones for Optimizing Soil Phosphorus Recommendations Under a No Till Field in Eastern CanadaCorn (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 |
15. Predicting the Spatial Distribution of Aflatoxin Hotspots in Peanut Fields Using DSSAT CSM-CROPGRO-PEANUT-AFLATOXINAflatoxin contamination in peanuts (Arachis hypogaea L.) is a persistent concern due to its detrimental effects on both profitability and public health. Several plant stress-inducing factors, including high soil temperatures and low soil moisture, have been associated with aflatoxin contamination levels. Understanding the correlation between stress-inducing factors and contamination levels is essential for implementing effective management strategies. This study uses the DSSAT CSM-CROPGRO-Peanut-Aflatoxin... S. Maktabi, G. Vellidis, G. Hoogenboom, K. Boote, C. Pilcon, J. Fountain, M. Sysskind, S. Kukal |