IBM has expanded its Watson Decision Platform for Agriculture to include AI technology tailored for new crops and specific regions to help feed the Earth’s growing population.

For the first time, IBM is offering a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and loT data to help give farmers around the world insights about planning, plowing, planting, spraying and harvesting.

New crop models include potato, but also corn, wheat, soy, cotton, and sugar cane with more coming soon. These models will now be available in the U.S., Canada, Mexico, and Brazil, as well as markets across Europe, Africa, and Australia.

“These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and loT sensors affixed to combines, seeders, sprayers, and other equipment,” noted Kristen Lauria, general manager of Watson Media and Weather Solutions, IBM. “Most of the time, this data is left on the vine – never analyzed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crop,” Lauria went on.

The average farm generates an estimated 500,000 data points per day, which will grow to 4m data points by 2036. Applying AI and analysis to the aggregated field, machine, and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers.

The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could aid to deliver French fries for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.