IBM’s work in Agriculture & Farming
In our last article, we discussed the influence IBM Watson was having on the Agriculture industry and why it was critical for Agriculture to develop a new approach to its current challenges. As we documented in that article, as a recap, things like intensifying climate concerns, a growing population by the billions, and razor thin margins for farmers have all catapulted invested in AdTech. In other words, for businesses like IBM and Syngenta, new challenges require new solutions when it comes to working with agriculture and farming.
In our September article, we will look at what IBM is doing to combat the challenges in Farming and Agriculture, and what it means for Golf Superintends in the future.
Like Superintendents, Farmers are looking for solutions to their challenges on a daily, weekly, monthly, and yearly basis. How can [they] better manage their operations? Their staff? Their resources? Their budget? Their vendors? All in an effort to meet the external demands of the market. Because farmers do their best to answer these questions in their own ways, weather is the variable that no one can predict that affects all of these questions—for better or for worse. Therefore, IBM is trying to make weather work for farmers rather than against them.
“As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions,” said Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska. “For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.” (newsroom.ibm.com)
IBM ultimately developed a suite of agribusiness tools designed to help farmers better predict and manage their operations—especially in the midst of unpredictable externalities like weather. IBM’s agribusiness tools address 4 key areas for farmers—as of right now. It addresses 1.) Yield History and Forecast for Corn; 2.) Disease & Pest Indicators for Corn 3.) High Definition Normalized Difference Vegetation Index (HD-NDVI) for Crop Health Monitoring and 4.) High Definition Soil Moisture (HD-SM). IBM has created a dashboard where the APIs of all these software solutions live in an effort to keep the most relevant insights accessible to farmers when they need them.
According to the article published by IBM’s newsroom:
“The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 20362. Applying AI and analysis to 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.” (newsroom.ibm.com)
What can Superintendents take away from IBM’s work in Agriculture?
They should expect that technology companies are well on their way to solutions as profound as IBM’s work in Agriculture. The externalities of things like weather and geopolitical uncertainties create challenges Superintendents effectively and simply cannot predict. And while internal challenges like labor and equipment management are ongoing, Superintendents are going to experience a wave of matured technologies that will assist them in their endeavors. From creating a more accountable culture among staff, to knowing exactly when to use specific chemicals, fertilizers, and water as result of external variables like weather. As I wrote about in Part 1 and Part 2, a batch of technology companies have committed themselves to finding the insights that will bring Superintendents a new look into the properties that they never knew was possible. And we’re very close to making that a reality—just like IBM’s work in Agriculture.