Mark Lefsrud, Mohamed Debbagh, McGill University
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Abstract:
With the growing prevalence of challenges in global food systems, including restricted access to fresh produce in remote areas and issues faced within traditional cultivation practices, outlooks on controlled environment agriculture (CEA) offer prospective solutions through precision methods of localized food production. Controlled environments within crop production systems provide opportunities to observe and cultivate plants with diverse characteristics, or phenotypes, making it suitable for specialized applications from trait selection for cultivar development and biopharming to food production in extreme and resource scarce environments. Subsequently, the ability to accurately predict and represent the phenotypic expression of a plant and its trajectory at various points in its growth cycle demonstrates a fundamental step towards advancing simulation and modeling research within CEA. In this talk we discuss the predictions and representations of plant growth patterns in simulated and controlled environments that are important for addressing various challenges in plant phenomics research and focus on the spatiotemporal modeling of plant traits and the integration of dynamic environmental interactions. We provide an examination of deterministic, probabilistic, and generative modeling approaches, emphasizing their applications in high-throughput phenotyping and simulation-based plant growth forecasting. Key topics include regressions and neural network-based representation models for the task of forecasting, limitations of existing experiment-based deterministic approaches, and the need for dynamic frameworks that incorporate uncertainty and evolving environmental feedback.
Bios:
Mark Lefsrud
Dr. Mark Lefsrud is an Associate Professor at McGill University and leads the Biomass Production Laboratory. His upbringing on a farm and work in the oil fields of Alberta, Canada combined with his B.Sc. and M.Sc. in Agricultural and Bioresource Engineering and a Ph.D. in Plant Physiology gives him a very strong background in the fields of agriculture, biology, and engineering. His research program deals with the development of bioprocesses and improvements in plant growth and environmental energy usage.
The laboratory is focused on four areas: 1) The development and improvement of new sources of biomass (food, fibre and/or fuel); 2) The improvement of energy efficiency of greenhouses and plant growth environments (light (LEDs) and heating systems); 3) The development quality practices for cannabis production; and 4) Development of monitoring techniques for plants and microorganisms using machine vision, nutrient monitoring, proteomics and metabolomics. His overall research philosophy is a holistic one in which focus on individual facets of an issue leads to a solution to the problem as a whole.
Mohamed Debbagh
Mohamed Debbagh is a Ph.D candidate at McGill University under the co-supervision of Professors Mark Lefsrud and Shangpeng Sun. He holds a B.Eng and M.Sc in Bioresource Engineering and Precision Agriculture and is driven by finding solutions to challenges faced within multi-scale food systems. His industry background covers sensor development, sensor fusion methods and robotics for various controlled environment producers. His Ph.D research focuses on the application of probabilistic computer vision and sensor fusion techniques for assessing plant development to improve crop throughput in controlled environment agriculture.