Mapping the Potential of Soil

In the past, agriculture mapping technology focused on appearances and taxonomy. Satellite and aerial data showed topographical features and the color of the topsoil hinted at the composition of what lay underneath. But appearances only run skin deep.

 

 

Purdue scientists have developed algorithms that account for how soil in specific locations interact with landscape features like streams and water catchments. These algorithms provide farmers with differences in soils and the minimum number of places required to properly sample field soil. Working from these patterns and soil samples, Dr. Phillip Owens and his team then produce maps with three-dimensional modelling.

 

Video: predictive weed Management saves on herbicide costs and increases yield potential

Gowan Canada is partnering with Geco Strategic Weed Management to help Canadian growers take a strategic approach to weed control through data-driven prediction and planning.

Geco’s technology uses data and AI to map where weeds have been over the past five years and predict where patches are likely to emerge next season. These insights allow farms and retailers to plan ahead and target actions in the most challenging areas.

“Our technology enables the question: if you could know where your most problematic patches are and where they are spreading to, what could you do differently? That’s what our technology makes possible,” said Greg Stewart, CEO of Geco. “Many of our farms are already using our prescriptions along with Gowan products, so this collaboration is a natural next step.”