Revolutionizing Farming with Data Technology

The power of data-driven practices and precision agriculture

What is data-driven agriculture?

Data-driven agriculture can be simply defined as the use of data to aid farmers in decision making, but there is nothing simple about the power of data-driven practices. While farmer experience and expertise cannot be discounted, neither can the value of insights derived from a variety of data sources and artificial intelligence (AI). With a database, internet connectivity, mobile devices, remote sensing devices, satellite data, and AI, farmers can optimize their agricultural practices to improve sustainability without relying on manual data-driven practices providing farmers and farm management with a wealth of real-time information at their fingertips.

Mobile devices such as cell phones and tablets enable farmers to skip the laborious process of manual data entry following data collection in the field with immediate data and metadata (like GPS location) upload to a server. Remote sensors like soil sensors, drones and other unmanned aerial vehicles (UAVs), and local weather stations record real-time conditions associated with GPS locations and other metadata. Alternatively, when local weather stations are unrealistic implementations, “virtual” weather stations provide hyperlocal weather predictions from a network of weather stations. Field collected (manual and remote sensing) data can be used in tandem with satellite and climate data to analyze trends throughout the growing season and year-to-year as well as create predictive models.

Improved harvests and costs savings with precision agriculture

Data-driven practices enable farmers to use precision agriculture, a strategy for site-specific management (SSM) that uses spatial and temporal data from various sources to inform decisions for improved productivity, quality, efficiency, profitability, and sustainability. SSM, also referred to as Variable Rate Technology (VRT), involves resource management at a smaller scale than field level due to the spatial and temporal variability that commonly occurs within fields. Rather than relying on field averages or recommendations, site-specific application of different inputs using VRT – referred to as variable rate application (VRA) – can cut costs and environmental impact and improve harvest quality and yield.

Management zoning

Due to within-field variability, management zoning is a powerful tool used in VRT to characterize areas of a field which require similar inputs – including seed type, fertilizer, pesticides, and water – to optimize their use and maximize crop yield. Satellite imagery and remote sensing devices are particularly valuable in zoning due to the ability to temporally monitor and gleam insights in real-time into various soil, climate, topographical properties, and crop health to determine zones that require similar levels of inputs. With sufficient historical and appropriate machine learning techniques, yield prediction maps can also be used for zoning.

Ultimately, data-driven agriculture and precision farming practices are revolutionizing the way farmers approach decision making and resource management. By integrating technology such as mobile devices, remote sensors, satellite imagery, and AI, farmers can capitalize on real-time information to optimize agricultural practices and maximize profitability and sustainability. Embracing site-specific management strategies allows for the tailoring of inputs to the unique needs of different areas within a field, reducing costs and environmental impact while enhancing harvest quality and yield. As we strive for continued growth and success in the agricultural industry, the integration of these advanced technologies and practices is essential for meeting the evolving demands of the market.

Sources

• Home | International Society of Precision Agriculture (ispag.org)
• Real Time Local Weather Data on your Devices (ambientweather.com)
• Precision Agriculture and Zone Management (sdstate.edu)
• Data-Driven Agriculture: The Future of Smallholder Farmer Data Management (usaid.gov)
• Site-specific management P2391.pdf (usda.gov)