Big Data was a big deal just a few years ago. Farmers worried about who had access to their data; farm groups worried about who owned a farmer’s data; and the agribusiness sector was trying to figure out how to make money with data. Year after year, farmers were able to collect more and more data, but the practical benefits of all this data remained somewhat limited.
Yield data was the first to be deeply analyzed and still remains one of the main reasons growers subscribe to data analysis services. Crop inputs were next as growers learned how to determine which inputs were needed, which performed well, and which actually were worth the investment. With the ever-growing sophistication of the technology, we are moving from examining the past to forecasting the future.
Today, growers are able to forecast with relative accuracy the amount of nitrogen they have in their soil based on weather data, application data, and crop history. Using satellite photos, weather data, and harvest records, a farmer can make a yield projection on his fields; and traders can make crop size predictions more accurate than the USDA reports.
Analysis of Big Data is expanding beyond the agronomic realm. Big Data analysis can now help a farmer calculate his profitability by field and by acre. The algorithm will provide a “what if” analysis on a field, based on past history and current input and crop prices. With profit margins remaining very thin on many crops, this may be an analysis your lender will want to see before approving an operating loan.
This technology is moving very fast. A program, currently in the works, would allow a grower to simply take a photo on their phone of a plant and get an analysis of what disease is attacking that plant. The increasing use of artificial intelligence will not only take some of the guess work out of farming, but will make recommendations on how a farming operation should be run. The wisdom and experience of Dad has been concentrated into a bunch of ones and zeros put together with very long mathematical equations.
Self-driving tractors, drones, robots, and artificial intelligence may paint a future of agriculture that makes some of us very nervous. Yet, remember, farming is a risky business, and computer analysis cannot always account for mother nature and the uncertainty of the marketplace. Big Data is finally beginning to deliver on its promise of helping farmers farm better. Yet it is has some dangers, like trying to take the farmer out of farming.
By Gary Truitt