The NCO had three projects funded by the Ontario Agri-food Research Initiative, all ending in 2023:
- Automation & Robotics Adoption in Ontario’s Agricultural Chain (see below)
- Mobilizing Knowledge for the Adoption of BMPs in Ontario’s Horticulture Sector ( click here for more information on our BMP research)
- Niagara Agriculture Municipal Learning Network (NAMLN) (click here for more information on the NAMLN site)
AUTOMATION AND ROBOTICS ADOPTION IN ONTARIO’S AGRICULTURAL VALUE CHAIN
Grant titled Building a Competitive Production Systems in Niagara and Ontario’s Agri-foods Sector: Accelerating the Adoption of Automation and Robotics Technology
This is an Ontario Agri-food Research Initiative (OAFRI) project. OAFRI projects are funded through the Canadian Agricultural Partnership (the Partnership), a five-year, $3-billion investment by Canada’s federal, provincial and territorial governments to strengthen and grow Canada’s agriculture and agri-food sector.
In July 2020, the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) awarded a research grant to Brock University’s Niagara Community Observatory (NCO) to investigate both the barriers and drivers to the pursuit of globally competitive production systems in Ontario’s agri-food sector. The project will examine the factors impacting technology development, transfer, and adoption by agri-food businesses in Ontario. In particular, the primary research focus will be on automation and robotics technology transfer and adoption, examining their application across the full spectrum of the agri-food value chain. The project will generate solutions for accelerating technology transfer and adoption in Ontario’s agri-food sector.
The intended benefits of the project are to contribute to evidence-based decision-making and program development advancing mechanisms, structures and processes of knowledge translation and transfer, with a focus on robotics and automation technology transfer and adoption in Ontario’s agri-foods clusters.
The study will consist of four phases employing a mixed methods approach to collect and analyze quantitative and qualitative data, over a period of 32 months. The data will consist of surveys administered across southern Ontario, one-on-one in-depth interviews focusing on Niagara, field study of two Canadian Superclusters (in agri-foods and advanced manufacturing, respectively) and focus group discussions in Niagara. These activities will be organized into phases and sequenced to feed into each other. The four phases of the project are outlined below.
Phase 1: Survey of Agri-food Clusters in southern Ontario
The first phase of the study will consist of a distribution, collection and analysis of survey questionnaires. The survey questions are meant to identify: first, the barriers/drivers to innovative automation and robotics technology adoption by Ontario businesses in the agri-food sector; second, where agri-food businesses have adopted innovative automation and robotics, were the original reasons for making the investments achieved, and were the outcomes positive, negative or neutral; third, how were barriers to adoption overcome, and what specific steps could be taken to accelerate innovative automation and robotics technology transfer and adoption in this sector. The NCO has contracted with Rel8ted.to, a data analytics firm based in Niagara to administer, collect and analyze the above survey data. The data will be collected and analyzed over a period of six months.
Phase 2: Niagara Case Study – Personal Interviews
The second phase of the project will focus on Niagara’s agri-food sector as a case study with in-depth interviews. The interviews will follow the same themes as the questionnaires. However, a semi-structured interview will enable the research team to explore structures and processes shaping robotics and automation technology adoption in ways that cannot be directly observed or reflected in numbers. Furthermore, this method ensures some degree of comparability among the responses, but also allows the research team to probe for specific information based on the responses provided by interviewees.
Thank you to all those who attended the presentation of our latest policy brief! A special thank you to our panel: Rodney Bierhuizen (Sunrise Greenhouses), Kathryn Carter (OMAFRA), and Hussam Haroun (Vineland Research). You can watch the Dec. 8, 2021 presentation here:
Phase 3: Field Research of two Canadian Superclusters
The third phase of the project will be a month-long field study of two of Canada’s recently created Superclusters. The principal investigator, Dr. Charles Conteh, will undertake a two-week study of the Protein Industries Supercluster based in Regina, Saskatchewan and a two-week study of Next Generation Manufacturing Canada (NGen) Supercluster in Hamilton. The aim of this research is to deepen understanding of trends, opportunities, and barriers associated with robotics and automation technology adoption by Canadian businesses. The stakeholders in these two superclusters could provide considerable insights into the cluster dynamics of robotics and automation technology transfer and adoption within regional innovation systems. This phase of the project will consist of conducting interviews and focus group discussions with key stakeholders in the two superclusters
Phase 4: Niagara Focus Group Research to Generate Data-Informed Solutions
The fourth and final phase of the project will consist of six focus group discussions (maximum of 12 participants for each group) with agri-foods technology development, transfer, and adoption stakeholders in Niagara’s agri-food sector. This phase of the project will be focused on generating solutions to the problems and challenges uncovered in the earlier phase of the project. Findings will be incorporated into our final report, due January 2023
This study has been reviewed and received ethics clearance through Brock University’s Research Ethics Board (file #20-085). The REB application and monitoring process ensures that we conduct ourselves ethically while conducting this research and handle the data accordingly. This includes protecting the data from data breaches by keeping copies of the data in a locked room on computers behind an Internet fire wall.