Pioneering Soil Health with Advanced Ag Revolution Techniques!
Introduction
A leading European farming company faced challenges due to strict market rules that impact all areas of food production. They were committed to running a business that is both sustainable and environmentally friendly. As the company grew, the high costs of traditional soil testing and lower crop outputs became a concern. Using the latest monitoring tools, they identified overlooked and poorly maintained parts of their land. In just two year, with smart actions based on these findings, they improved their soil quality and obtained stable crop outputs, despite climate change in the area of cultivation (droughts).
The Client
This major farming company has experienced more attention from regulators recently. Their board is fully dedicated to sustainability and minimizing harm to the environment. One of their main goals is to improve at least 4% of their land every year.
The Challenge
The main issue was finding a method that could measure the amount of carbon in the topsoil across all their land consistently. With a deadline to provide a detailed report on their efforts to protect the environment, the gaps in their existing data became a big problem.
The Solution
Enter the advanced ag revolution – our solution fuses the most sophisticated deep learning algorithms with satellite imagery technology. The system implemented was the Local Enhanced-AI mapping (LAIM). This revolutionary technique enabled retrospective analysis of the property’s soil health also in the past, from 2015 onwards. Relying on a few soil reference samples (between 0.5 and 5% of the total area), the LAIM, through transfer learning, enhanced these samples for local calibration. The outcome? A detailed report capturing the nuanced evolution of soil health over the specified period.
The Results
The in-depth report delivered clear insights into the property’s soil regeneration trajectory over the past year. Notably, areas exhibiting advanced soil regeneration, previously undetected due to the absence of manual sampling, came into focus.
The company witnessed measurable soil health improvements over the year.
Undiscovered areas of heightened regeneration were identified, offering potential for increased yield.
“We feared our inability to produce the report, suspecting that our manual testing data was lacking. However, thanks to the innovative techniques, we not only retrieved past data but also validated our progressive trajectory!” – [S.L., project leader].
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