Our team has created the first ever digital twin of the soil microbiome for G.E.M. analysis. Objective and rapid scans of the entire soil profile trained using the hashtag#digitalsoilcore sensors and deep machine learning to predict and quantify the soil micro-biometric environment and populations.

More than a century ago, Dutch microbiologist Martinus Beijerinck helped frame one of the central ideas in microbial ecology: Microbes may be widely distributed, but the environment determines which communities emerge. Lourens Becking later captured that idea in the famous line: “Everything is everywhere, but the environment selects.” That idea is exactly why conventional laboratory methods cannot fully classify and quantify the soil microbiome.

One of the most fascinating discoveries from the digital twin analysis is that more of the beneficial bacterial and fungal signal appeared below 15 cm than above. That matters because many soil health and microbiome programs focus heavily on the upper topsoil (because it’s easy). What if there is a deeper biological reserve? A “deep bench” of beneficial microbes that becomes active, moves, or influences the root zone as soil moisture, oxygen, carbon, chemistry, and management conditions change?

Dense lab testing at this level of depth and spatial detail would cost tens of thousands of dollars and take weeks. Even then, it would still lack the continuous physical and chemical context and fidelity needed to understand why microbial communities appear where they do. Conventional microbiome data is not suited for advanced analytics.

This is the next frontier in regenerative agriculture: Not just measuring microbes. Understanding the environment that selects them and how management can be tailored for the maximum benefit.

Learn more at: https://landscan.ai/

We will be looking for the right strategic partners and quantitative soil microbiomists to bring this revolutionary approach to the market as part of our broader tech stack.

Biome Makers Inc. Trace Genomics Bayer Corteva Agriscience Syngenta Nutrien Wilbur-Ellis OCP Nutricrops The Wonderful Company John Deere AGCO Corporation Novonesis Mars

hashtag#digitaltwin hashtag#regenerativeagriculture hashtag#soilhealth hashtag#agtech hashtag#rootcauseanalytics hashtag#soilscience