Agmatix launches new agricultural data technology platform to support sustainable food production

Agmatix, a start-up agtech business owned by leading global specialty minerals company, ICL, has launched a breakthrough data technology platform. As the world's first single engine that drives the agronomic innovation cycle from research and experimental data into meaningful real-life actions, the Agmatix technology creates a new data language that can read and interpret thousands of the different data points commonly used across the agricultural industry. The unique system then provides agronomists, researchers and farmers with the vital information needed to make better crop management decisions to increase yields and crop quality.

Utilizing machine learning and artificial intelligence, the Agmatix system provides agronomists, researchers and farmers with the vital information needed to make better crop management decisions

By digitizing field trials and agronomic experimentation, as well as standardizing data across the industry, the new Agmatix solution is also building a global database poised to unlock the mainstream use of big data in agronomy - shortening timelines, reducing waste and increasing profitability for agricultural professionals and farmers.

The new technology achieves this by utilizing machine learning and artificial intelligence to provide comprehensive advice as to soil, land topography, irrigation, weather and crop management. Importantly, the Agmatix platform enables the development of statistically and scientifically stronger agricultural models, which helps to reduce food waste and support the issues of world food poverty and a growing global population.

Ron Baruchi, CEO, Agmatix comments, "Growers, agronomists, researchers and ag industry experts are tackling today's biggest challenge - providing food security for the world's growing population. While searching for a solution, each of them is creating and collecting vast amounts of data and expertise. But In order to face this epic challenge, they will need to be able to share the data and knowledge between them. Our technology provides a solution that unites, standardizes and leverages agricultural data, allowing it to effectively manage agronomic research trials and translate them into real life practices in a one-stop-shop"

Agmatix's technology platform has now completed over 50,000 field trials, processing 17 million agronomic measurements and successfully analysing over 70 plus different crop types on a global scale. The company has partnered with leading global research institutes, universities, NGOs and leading agricultural companies who are now using Agmatix to build the largest and highest quality database of standardized data in the world. This will equip such institutions with the tools to develop machine-based models that can predict the environment's impact on plant nutrition, enabling short and long-term planning.

Empowering agro-tech professionals around the world, the Agmatix solution is a SaaS technology platform made-up of five key component modules, including:

• Field Trial Management Platform – The system digitally manages field trials including data collection and analysis from start to finish

• Trials and Research Data Ingestion – The system automatically ingests and standardizes legacy data from agronomic field trials and experimentation

• Data Insights & Predictive Models – A self-analysis tool using advanced machine learning models derived from field trials and experimentation data

• Decision Support Systems – For agro-professionals, the Agmatix Digital Crop Advisor tool enables the translation of insights into actual decision support systems

• Axiom Open - A collaborative and open portal that enables agro researchers and professionals from around the globe to share and view agronomic data to tackle common high-level challenges
  

Ron Baruchi concludes, "We must leverage big data to solve these global problems and find ways to collaborate across the agri-food industry. It begins with high-grade standardized agronomic data to enable change on a large scale."