Recent advancements in precision agriculture and data analytics have paved the way for the next important step forward in agriculture: incorporating big data on the farm. While the idea of using big data for agriculture may sound complex, it boils down to analyzing all the data generated on the farm to reveal insightful patterns and trends. Data comes from a wide variety of sources. Planters, combines, sprayers, soil tests, remote rainfall monitors and more are just some of the primary tools farmers use to record and analyze the efficiency of their operations.
Farmers feed this information into analytical software to develop highly detailed, valuable production plans capable of:
- Increasing yield
- Maximizing resources
- Improving sustainability
Having access to such data enables farmers to easily identify problems and take steps to correct the issues. The prescriptive recommendations received from the farm-management software can even be used to decide which varieties to plant, proper seeding rates and how much fertilizer to use. And the recommendations align with specific soil types and the productivity index of each section of land.
The advent of cloud-computing technology has given farmers the ability to access real-time data about their farming operations. Farm machinery sensors beam harvest data, rainfall totals and other information directly to internet-based servers for on-demand access. This can save time, effort and paperwork, as well as make it easier to compare results, analyze trends and reach decisions more quickly.