With the backing of technology giant Alphabet, a new ag tech company called Mineral has been unveiled with the ambition to help scale sustainable agriculture.
“We’re doing this by developing a platform and tools that help gather, organize, and understand never-before known or understood information about the plant world - and make it useful and actionable,” Elliott Grant, Mineral CEO, said in a blog post.
After five years incubating its technology at X, Alphabet’s moonshot factory, Mineral is a now a commercial company within California-based Alphabet, the parent company of Google, YouTube and other technology firms, Grant said in the post.
Prior to his work at Alphabet’s X and Mineral, Grant was the CEO of ShopWell, where he built an artificial intelligence engine to inform consumer choices about food. Before that, Grant was the founder and CEO of HarvestMark, a food and produce traceability company.
The focus of Mineral is in three key areas, Grant said in the blog post:
- Developing sensing technology that can generate rich data sets about plants.
- Organizing agriculture data from disparate sources for machine learning and building powerful software algorithms.
- Conducting research that can meaningfully advance the fundamental understanding of plants.
“Together with our partners across the food production system, we’re hopeful that these tools will - over time - drive a deeper understanding of the complex interactions of plant genes, the environment, and farm management practices,” Grant said in the post.
While Mineral is “early” in its journey, Grant said one observation is that most companies are not collecting the quantity, diversity or quality of data needed to take full advantage of machine learning.
“That’s why we built tools to better capture, curate, clean and augment multimodal data; and assembled our own bootstrap ag dataset,” he said in the post.
Grant said there is no single mode of data collection suited to every agriculture task or crop.
“We began with a plant rover that could capture huge quantities of high quality images, and over time expanded to building generalized perception technology that can work across platforms such as robots, third party farm equipment, drones, sentinel devices, and mobile phones,” he said in the post.
Mineral analyzes large, multimodal, unstructured sets of the world’s agricultural data, sourced from satellite images, farm equipment, public databases and Mineral’s own proprietary data streams, according to a company fact sheet.
To date, the Mineral team has analyzed over 10% of the total farmland on Earth, modeled more than 200 plant traits, phenotyped 17 crop varieties and developed more than 80 high-performance machine-learning models, the company said.
The data is helping farmers, researchers and breeders across five continents predict crop yields, increase production, target pests and weeds, reduce waste, minimize chemical and water use and reduce the impact of agriculture on the planet, the company said.
