Etienne Lord

Research scientist - Digital agronomy et A.I.

Development of technologies and models related to image technologies, phenomics and robotics.

https://profils-profiles.science.gc.ca/fr/centre-recherche/centre-de-recherche-et-de-developpement-de-saint-jean-sur-richelieu

Current research and/or projects

•   Bioinformatics: Use of graph neural networks and microbiome data for biovigilance and yield forecasting.
•   Deep learning: Use of image technologies (satellite, dronic and robotic) to characterize the agricultural ecosystem and create predictive models
•   Biodiversity: Measuring the impact of agricultural practices using soundscape.

Research and/or project statements

The digital agronomy laboratory seeks to develop high quality datasets and algorithms using artificial intelligence (AI) to better monitor the resilience of ecosystems (biodiversity, soil components). More specifically, image technologies (e.g. hyperspectral), connected sensors (IoT) and robotics are at the heart of Dr. Etienne Lord's research. Dr. Lord's work aims to develop and understand technologies that can more closely connect the fields to the various stakeholders (producers, advisors and researchers) in order to better anticipate the resources needed (water, organic matter, labor, biodiversity) to make the agricultural sector more competitive, innovative and sustainable. Current projects reflect the multidisciplinary nature of these issues.

Current projects:

•   J-002491 Smart land management for soil and water conservation and increased profitability
•   J-002634 Screening of Invasive Alien Species using metabarcoding and its biovigilant continuum through predictive models forecasting risks for potential IAS introduction, movement and establishment related to climate changes
•   J-002490 Implementing a living laboratory in Québec – Lake St-Pierre region
•   J-002366 Genomics-enhanced biovigilance to improve crop disease management
•   J-002302 Biovigilance pour la durabilité des sols organiques

Professional activities / interests

•   Bioinformatics
•   Artificial Intelligence and Deep Learning
•   Hyperspectral imaging and robotic

Education and awards

Ph.D. Computer Sciences, Université du Québec à Montréal (2010-2015)
Thesis : Workflows and their Applications in Bioinformatics

Diplôme d’études supérieures spécialisées (DESS) en bioinformatique, Université du Québec à Montréal (2009-2010)

M.Sc. Veterinary Sciences, Université de Montréal (2002-2006)

B.Sc. Biology, Specialty in Microbiology, Université de Sherbrooke (1998-2001)

Key publications

Tremblay, É.D., Goulet, B.B., Lord, E., Samson, S., Liu, M., Tambong, J.T., Brunet, B.M.T., Khanal, R., Parent, J.-P., and Chen, W. (2023). Surveillance of crop-associated microbes using high-throughput sequencing of environmental and seed samples. In 12th International Congress Of Plant Pathology (Lyon, France).
2023 - View publication details
Tremblay, É.D., Goulet, B.B., Lord, É., Samson, S., Liu, M., Brunet, B.M.T., and Parent, J.-P. (2023). Fungal diversity, surveillance and incidence forecasting of crop-associated phytopathogens using metabarcoding of aerial spore and suction traps. In The Canadian Tri-Society meeting (Ottawa, ON, Canada)
2023 - View publication details
Tremblay, É. D., Goulet, B. B., Brunet, B. M. T., Lord, É., & Parent, J.-P. (2023, 2023/05/31 - 2023/06/02). Diversity of crop-associated oomycetes using metabarcoding data from aerial spore and suction traps. Talk presented at the 4th Annual CanFunNet Fungal Biology Conference, Virtual Event.
2023 - View publication details
Denault, J.-T., Benjamin, L.-D., Lord, É., Boivin, C., Ricard, S. & Bourgeois, G. 2023. Climatology of the synchronism of late spring frost with sensible phenological stages of five major horticultural crops in Quebec. Poster presented at the 57th Canadian meteorological and oceanographic society congress. St.John's, NL.
2023 - View publication details
Ste-Croix, D.T., Gendron St-Marseille, A.-F., Lord, E., Bélanger, R.R., Brodeur, J., Mimee, B. 2021. Single nematode sequencing of the soybean cyst nematode highlights different strategies to breakdown resistance. SÈVE2021.
2021 - View publication details
Mimee, B., Lord, E., Véronneau, P.Y., Masonbrink, R., Yu, Q., den Akker, S.E.v. (2019). The draft genome of Ditylenchus dipsaci. Journal of Nematology, [online] 51(1), 1-3. http://dx.doi.org/10.21307/jofnem-2019-027
2019 - View publication details
St-Marseille, A.F.G., Lord, E., Véronneau, P.Y., Brodeur, J., Mimee, B. (2018). Genome scans reveal homogenization and local adaptations in populations of the soybean CYST nematode. Frontiers in Plant Science, [online] 9 http://dx.doi.org/10.3389/fpls.2018.00987
2018 - View publication details