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Breakout Room 5 Poster Presentation Event Akshara Chandrabalan 2020 NSERC USRA Bioresource Engineering, Supervisor Dr. Prasher 2020 Undergraduate Student Research Awards Predicting Biochar Sorption Capacities Using VIEW THE POSTERS Artificial Neural Networks Poster Presentation Event Breakout Room 5 Daniel Moses 2020 NSERC USRA (ZOOM) SEPTEMBER 17, 2020 @ 4pm Parasitology, Supervisor Dr. Salavati In search of the cryptic motif VI on trypanosomatid RNA editing ligases Richard Boivin 2020 NSERC USRA Antoine Gaudreau 2020 NSERC USRA 1 Natural Resource Sciences, Supervisor Dr. Humphries Bioresource Engineering, Supervisor Dr. Akbarzadeh Muriel Wong Min 2020 AES Brown Martlet USRA Evaluating regional patterns of traditional wildlife 3D Printed Agricultural Wastes for Advanced Food Science & Ag. Chemistry, Supervisor Dr. Karboune harvest in northern Quebec Biocomposites A Database Platform for The Selection of Appropriate Fat Substitutes as "Natural" Katerina Lazaris 2020 NSERC USRA Rowena Groeneveld 2020 NSERC USRA Food Ingredients Animal Science, Supervisor Dr. Bordignon Parasitology, Supervisor Dr. Beech Review: Methods to Improve Oocyte Competence and Modelling of a ligand gated ion channel from embryo Development in Prepubertal Animals to Caenorhabditis elegans experimentally shown to bind Liana Fortin-Hamel 2020 NSERC USRA Accerlerate genetic Gain 6 dopamine Parasitology, Supervisor Dr. Scott 2 Trisha Sackey 2020 NSERC USRA Effects of maternal nematode infection on spatial Food Science & Ag.Chemistry, Supervisor Dr. George Alex Zvezdin 2020 NSERC USRA learning and memory of young mouse pups Natural Resource Sciences, Supervisor Dr. Head Genotypic and Phenotypic Profiling of Staphylo- coccus aureus strains isolated from Canadian Impacts of Agricultural Practices on Yellow Perch Xavier Godin 2020 NSERC USRA Dairy Cattle for Antimicrobial Resistance Spawning Sites in Lac-Saint Pierre Québec Plant Science, Supervisor Dr. Seguin Increasing the production and utilization of alfalfa- based forage mixtures in Canada Sreedurga Cherukamalli 2020 NSERC USRA 7 Catherine Bergeron 2020 NSERC USRA Bioresource Engineering, Supervisor Dr. Adamowski Tatiana Rayvich 2020 NSERC USRA Plant Science, Supervisor Dr. Charron Quantification of participatory sociohydrological Bioresource Engineering, Supervisor Dr. Lefsrud Differentiation of Garlic cultivars Growing in Quebec model of the Lake Atitlan watershed in Guatemala A comparison of cost and yield of lactuca sativa Using Phenotypic and Genotypic Traits grown on porous concrete as a function of concrete Bridget O’Brien 2020 NSERC USRA use and LED lights Lakshitaa Lugun 2020 NSERC USRA Animal Science, Supervisor Dr. Ronholm Bioresource Engineering, Supervisor Dr. Zhiming Qi Keepin' it Fresh: A Review on the Application of A comprehensive literature review on the evaluation Nanopillars for Meat Packaging Joel Harms 2020 NSERC USRA of crop models' performance 5 Bioresource Engineering, Supervisor Dr. Adamowski 3 Jonathan Sangiovanni 2020 NSERC USRA Coupling of socioeconomic system dynamic models with Benjamin Vonniessen 2020 AES Brown Martlet USRA Natural Resource Sciences, Supervisor Dr. Head the SWAT+ hydrological model for accessible Integrated Natural Resource Sciences, Supervisor Dr. Lyle Whyte Water Resource Management model development Transcriptomic Profile of BaP in Japanese Quail and Mining archeal MAGs and SAGs for archaeocin double-creted Cormorant Alexandra Kerasias 2020 NSER USRA production related sequences School of Human Nutrition, Supervisor Dr. Kubow Gut microbial biotransformation and first pass metabolism of anthocyanins from purple potato digests: A 4 metabolomic approach to identify bioavailable REGISTER NOW microbial anthocyanin metabolites https://www.mcgill.ca/macdonald/research Yijiang Liu 2020 AES RUDI DALLENBACH USRA /seminars/undergrads Animal Science, Supervisor Dr. Duggavathi Identification of transcriptional mechanisms of H3K4me3 in the regulation of ovulatory genes Quantification of participatory sociohydrological model of the Lake Atitlán watershed in Guatemala Cherukumalli, S., Malard, J.J., Adamowski, J.F. Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, QC, Canada Abstract A participatory sociohydrological model was built of the Lake Atitlán watershed in Guatemala to address the issue of nutrient pollution and cyanobacterial + 3 Results Expected blooms. Part of the model was quantified using data-based and conjectural Preliminary findings, however, more quantification remains to be done: vegetable approaches. Preliminary findings from the model include: vegetable production forms Expected supplied Agricultural land submodule: balancing loops in land required, quantity, and price; tourism and cyanobacterial price quantity of ▪ Vegetable production forms balancing loop between expected and + blooms form a balancing loop; and lake volume is very sensitive to hydraulic gradient. vegetables actual implementation (Fig. 1). Land required, quantity, and price fluctuate then stabilize over time (Fig. 2). Actual + vegetable Land required for vegetable production Vegetable supplied quantity Vegetable price 1 Background Expected land price 200 3 M 1.5 ▪ Lake Atitlán in Guatemala is a popular tourist destination, source of water and for vegetable livelihood for surrounding indigenous community. - production 150 2.25 M 1.125 ▪ Nutrient pollution led to toxic cyanobacterial blooms causing decline in tourism, Actual supplied 100 1.5 M .75 Hectares + Kilograms fishing incomes, and locals’ quality of life. quantity of 50 USD kilogram per vegetables 750,000 .375 ▪ System dynamics is approach to understand the complex, nonlinear behaviours1 2 and Actual land required feedback loop structures of water resources management over time. + 0 0 0 for vegetable 0 24 48 72 96 120 0 24 48 72 96 120 0 24 48 72 96 120 ▪ Participatory modelling, involving stakeholder engagement and group model- Deaths production Time (Month) Time (Month) Time (Month) Expected Actual building, allows for combined3 4knowledge of locals, NGOs, government, etc. Expected Actual Expected Actual Figure 2. Ten-year trends for agricultural land submodule variables. See Figure 1. Objective: Quantify sociohydrological model of Lake Atitlán watershed by writing Population + equations to relate variables. Persons on + Tourism and cyanobacteria submodule: Births sewer network ▪ Tourists and bloom occurrence form balancing loop (Fig. 1). Tourism Tourists causes pollution and probability of a bloom to increase, causing tourism 2 Methodology to then decrease (Fig. 3). + - ▪ Literature review to quantify relationships in e.g. Total agricultural land ▪ Hydraulic gradient of lake (influences seepage) is sensitive parameter qualitative model. required (conjectural Inflow Tourist memory affecting lake volume and total nutrients. approach): of P of bloom ▪ Modelling software used: VENSIM PLE 8.0.9. ▪ Assume subsistence ▪ Each variable interaction required different + agriculture, vegetable, and Total phosphorus approach to quantify. Examples are below. Figure 3. Fifty-year coffee production make up in lake Cyanobacterial trends for tourism e.g. Probability of cyanobacterial bloom (data- majority. bloom occurrence and cyanobacteria based approach): submodule ▪ Land priority given to Outflow + variables. See Figure ▪ Bayesian inference calibration of equation subsistence agriculture. of P Probability of 1. based on observed phosphorus and bloom Remaining land distributed cyanobacterial data: + between vegetable and bloom coffee proportional to ퟏ + Probability of cyanobacterial bloom = − ퟑ.ퟗퟐퟒ+ퟒ.ퟏퟏퟗ 풍풐품 푷 market prices. Seepage ퟏ + ⅇ Concentration + ▪ Land for subsistence based + of P in lake Conclusion e.g. Tourist memory of bloom (conjectural Hydraulic approach): on percent population living Two balancing loops (vegetable production land requirement and tourism gradient on subsistence farms. and cyanobacteria) and one unexpected effect of hydraulic gradient found. ▪ Memory based on whether a bloom occurred in last 60 months. SMOOTH function takes time Figure 1. Simplified agricultural land (above) and tourism and cyanobacteria (below) In the future: ▪ Land for coffee and vegetable submodules of main model. Arrows indicate causal relationships; plus or minus indicate averages and represents expectations: production based primarily positive or negative relationships. Both are balancing loops. ▪ Determine how much nutrient runoff to lake is from agricultural land. on intersection of supply and ▪ Finish quantification then validate using data and stakeholder input. Acknowledgement: References: 푇표푢푟푖푠푡 푚푒푚표푟푦 표푓 푏푙표표푚 = 푺푴푶푶푻푯푰(푩풍풐풐풎, ퟔퟎ, ퟎ) demand curves. This research was supported by funding from the 1. Forrester, J. (1995). 3. Malard, J.J., et al. (2015). ▪ Established model can be used as a policy decision-making tool. Natural Sciences and Engineering Research Council 2. Winz, I. et al. (2008). 4. Mostashari & Sussman ▪ Goal is to facilitate local control of policy discourse. of Canada. (2004). Keepin’ it Fresh: A Review on the Application of Nanopillars for Meat Packaging Bridget O’Briena & Jennifer Ronholma a Department of Food Science and Agricultural Chemistry, McGill University Introduction The Bactericidal Mechanism Bacterial Cell Type and the Effect on the • The physical rupturing of bacterial cells is caused by pillar-shaped Pogodin et al. (2013): The Biophysical Model Bactericidal Mechanism nanostructures, referred to as nanopillars – a structure first iden@fied • Many studies show that Gram-nega@ve bacteria are more 1,2 on the
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