Putting Data to Work to Ensure the Safety and Security of our Food Supplygenerated in the last two years alone. And the data pool just keeps growing and growing.
This data is bringing a wealth of real-time figures to our fingertips, giving us a deeper understanding into processes and outcomes. But our data is only as good as the insights it helps inform. If we don’t put it to work for us, we run the risk of being data-rich and information-poor.
When it comes to regulations in agriculture and the use of genetic modification in enhancing crops to ensure we have enough food, feed, fuel, and fiber, data is the backbone of everything we do. For genetically modified crops, for instance, we have more than 20 years of data, giving us comprehensive insights into the traits and characteristics of every product, helping us confirm that plants and crops developed with GM traits are nutritious and safe for humans, animals, and the environment.
As we work in partnership with regulatory agencies—the U.S. Department of Agriculture, U.S. Food and Drug Administration, U.S. Environmental Protection Agency, European Food Safety Authority, Health Canada and countless others across the globe—having access to this level of data helps us show not only the safety of the crops we are developing, but also helps us communicate the life-changing benefits of adopting modern agriculture.
We can analyze portions of this data at a universal level to describe the food security, environmental sustainability, and socioeconomic benefits, but we can also use some of the data collected to dig in to the most basic elements of nutrition. Consider protein levels in a crop like soybean as an example. Protein is measured as part of the nutrition and safety assessment of GM crops, and in studies conducted for regulatory submissions, has also been measured in numerous varieties of conventionally bred soybeans grown throughout many different locations around the world and across different years. Much of this data is curated in the Crop Composition Database, maintained by the International Life Sciences Institute, and has contributed to the wealth of information we now have on the variability of nutrient content in soybean. The data available helps demonstrate how, where and when a soybean is planted can affect its nutritional composition. This can be valuable information to analyze as we strive to maximize yield and nutrition produced on every acre to increase sustainability in agriculture.
Food allergies are another area where data can help ensure food safety, especially in the context of biotechnology. A significant amount of data exists around the identity of protein allergens in food, and this information is collected in publicly accessible databases. We can compare the data contained in these databases to the proteins we are planning to use to improve our new crop products and ensure the newly introduced proteins are not similar to any allergens. This screening process occurs early in product development and provides an added level of assurance of safety of the new crop variety.
These are just a couple ways researchers in modern agriculture are putting data to work. Data science is also poised to continue helping farmers in significant ways. Today, digital technology helps farmers collect information in the field, enabling them to monitor individual plots of land to pinpoint exactly what it needs to produce thriving crops, while reducing the use of unnecessary resources.
The principles of data science in agriculture are the same ones we use when we buy a fitness tracker: The more easily we can see and understand what’s happening, the better choices we make. For instance, when we see that taking the stairs will burn a few more calories and add 50 extra steps on a busy day when we have to skip the gym, we can actively make decisions that work best for us and our circumstances. This is the same with farmers using data and insights from their fields as they seek to make better daily decisions for their crops, both as a steward of the land and as a business owner.
The benefits of data are endless, but without taking time to analyze patterns and learn what they mean, data is just a never-ending list of numbers and figures. When we bring our informed insights, we can put the data to work for us, for the safety and security of our food, feed, fuel, and fiber supply—and the planet.