SoiLiNQ - News & Events #R&DSoiLiNQ - News & Events #R&Dhttp://soilinq-test.zohosites.ca/news_and_events/tag/research-n-developmentThu, 09 Apr 2026 20:13:17 -0400http://zoho.com/sites/<![CDATA[Trust is a Requirement, Not a Feature]]>http://soilinq-test.zohosites.ca/news_and_events/post/trust-is-a-requirementGinkgo, OCI, and Vineland Research are cooperating on Machine Learning R&D for GreenTech. This ML Project will be by Sean Militello at Ginkgo Sustainability, and Rhoda de Jonge, at Vineland Research and Innovation Centre. It will leverage the SoiLiNQ proprietary sensor.]]>

Driving Smarter Plant Health Insights Through Partnership and Innovation

At Ginkgo Sustainability Inc., we believe that better data leads to better decisions - especially when it comes to the health of the living environments we help build and maintain. That’s why we’re thrilled to launch a collaborative project with Vineland Research & Innovation Centre and the Ontario Centre of Innovation, funded in part by OCI’s Critical Industrial Technologies program, to push the boundaries of machine learning to create a classification and prediction systems that we can trust.

This project marries cutting-edge technology with practical horticultural expertise. We’re using SoiLiNQ™, our soil and plant health IoT platform, to gather high-quality environmental data and build machine learning (ML) infrastructure that turns that data into meaningful insights.



What Makes This Collaboration Special

  • Real-world expertise meets advanced technology
    Vineland brings scientific and analytical rigor to carefully guide data collection and ensure it’s accurate and verifiable. The ML pipeline will be built using clean, trustworthy data, and deliver business intelligence customers can rely on.

  • Technology that works for many communities
    Using SoiLiNQ sensors to capture continuous data from a range soil and plant combinations, the project will deliver multiple narrowly scoped, highly effective machine learning models that users can trust, rather than a single model that gets it right some of the time.

  • Building for the future 
    Our goal is not only to analyze data but to create an efficient ML pipeline that scales with user needs, delivering predictive and prescriptive insights that help users act with confidence.

We look forward to sharing progress as the project evolves toward completion this September 2026. Stay tuned for updates, and if you haven’t already, follow SoiLiNQ at www.soilinq.ca to learn how actionable plant health insights can support your work.

]]>Wed, 25 Mar 2026 17:32:34 +0000