Physics-Informed Machine Learning Overcomes Particle-Size Nonlinearities That Confound the Raman Spectrometry of Granular Carbonaceous Materials
Raman spectroscopy supports multivariate regression models that can offer a rapid and nondestructive approach to quantifying the composition of granular materials. Soils constitute a class of such materials for which chemical analysis provides vital information for agriculture and environmental stewardship.
Quantifying Soil Total Inorganic Carbon Using Shifted-Excitation Raman Difference Spectroscopy (SERDS) and Machine Learning
Accurate quantification of soil inorganic carbon, which is stored predominantly in carbonate minerals, is essential for understanding the soil chemistry, agricultural productivity, and carbon sequestration processes.
Announcing DIGITAL Future of Mining and Energy Project Funding
Miraterra is celebrating the announcement of successful funding under the DIGITAL Future of Mining and Energy program, for the project “Multi‑lens Ecological Restoration Monitoring and Forecasting”, led by our project-partners Koonkie.
Quantification of Soil Organic Carbon by Shifted-Excitation Raman Difference Spectroscopy with Machine Learning and Common Mode Rejection
Soil organic carbon (SOC) is an important indicator of soil
health and productivity in agricultural and natural ecosystems. Conventional measurement techniques, such as combustion analysis, yield accurate results but consume time and material resources.
BetaKit: Miraterra announces $16 million to advance its soil measurement tech
March 25, 2026 | Josh Scott
Terramera subsidiary looks to build on its recent Trace Genomics acquisition with seed extension.
Miraterra Soil raises $16 million in oversubscribed financing round
Combined with Trace Genomics acquisition, new capital will scale AI-driven platform that decodes soil’s biological and chemical intelligence
Canada prioritizes sovereign sensors and digital systems
The DIS invests in dual-use technologies built by Canadian SMBs. We're one of them — and soil intelligence is exactly that. The same data that helps a farmer grow more food tells a government what's happening to its land.
Calibrated Uncertainty Estimation for Soil Organic Carbon from Raman Spectra
Identifying sources of measurement uncertainty is one of the first steps to producing reliable, usable data.
ALL IN Agritech Winner
Miraterra is honoured to be recognized as the winner of the @ALL IN Agritech Competition 2025.
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Soil Carbon Quantification by Shifted-Excitation Raman Difference Spectroscopy with Common-Mode Rejection
Quantifying soil organic carbon (SOC) has a vital role to play in advancing soil health, optimizing agricultural productivity, and helping mitigate climate change.
AgFunderNews: Miraterra acquires soil DNA startup Trace Genomics: ‘Independent growth wasn’t sustainable’
July 9, 2025 | Jennifer Marston
Trace Genomics said its focus shifted "to finding the right home" for its soil-measurement technology amid market headwinds.
Image credit: Trace Genomics
Miraterra acquires Trace Genomics
Miraterra, a British Columbia-based technology company known for unlocking measurement and insight across soil, plants, and food through breakthroughs in Raman spectroscopy, has acquired the assets of Bay Area-founded Ag-tech company, Trace Genomics Inc., including the full suite of Intellectual Property (IP), in-market products, and an analytical lab in Ames, Iowa.
Miraterra Announces Novel Soil Digitizer and Close of Seed Funding Round
Miraterra, a company revolutionizing advanced soil measurement, today announced the close of its Seed funding round led by At One Ventures, marking a pivotal moment in the company's mission to transform soil insight. New investors S2G Ventures, One Small Planet, Overview Capital, iSelect Fund, Starshot Capital, Pelican Ag, and Cisco Foundation also participated in the round.
Machine Learning Analysis of Raman Spectra To Quantify the Organic Constituents in Complex Organic–Mineral Mixtures
Raman spectroscopy applied with machine learning quantifies the amino acid constituents of complex mixtures in the presence of interfering fluorescence and mineral features
Collaboration between Miraterra Inc. and the University of British Columbia