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| Filter results4 paper(s) found. |
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1. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, CanadaManagement zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath |
2. 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 |
3. 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 |
4. Machine Learning–driven Insights into Nitrogen Dynamics and Greenhouse Gas Emissions in Potato Production SystemsNitrogen (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 |