Satellite and yield data identify unprofitable acres

Whether it’s a house, hobby, or piece of machinery, there’s just something special about investing in a proverbial money-pit.

Like a combine that requires frequent and costly repairs, though, land that consistently doesn’t pay for itself is a major issue for some farmers.

Identify unprofitable field areas

At a recent agricultural conference in Ontario, Canada (called the SouthWest Agricultural Conference) American researchers from Michigan State University (MSU) identified how a combination of satellite imaging and accumulated yield data allows them to identify unprofitable field areas across millions of acres in the Midwestern United States.

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Like a combine that requires frequent and costly repairs, land that consistently doesn’t pay for itself is a major issue for some farmers. – Photo: AFP

“Unstable yields offer opportunities for site specific adaptations,” says Dr. Bruno Basso, a researcher from MSU’s Earth and Environmental Sciences department and head of the school’s digital agronomy and spatial analytics lab.

Triad of technologies

In his presentation to conference attendees, Basso used the term “unstable yield” when referring (generally) to acres that consistently drain financial resources. A triad of technologies are employed to determine whether each part of a given field are stable or not:

1. Thermal satellite imaging – to indicate whether crop transpiration is occurring, and where plants are starved for water.
2. Reflective satellite imaging – Using NASA technology to look closer at plant health.
3. Historical yield data – to see accumulated on-the-ground results, and compare each area with those surrounding it.

Yield stability maps on a sub-acre scale

When analysed together, Basso and his team of researchers are able to generate yield stability maps on a sub-acre scale. These maps, says Basso, indicate variability more specifically than those generated using one metric alone – enabling growers to make more accurate management decisions.

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“Unstable yields offer opportunities for site specific adaptations,” says Dr. Bruno Basso. This might include selecting for drought-tolerant varieties on unstable high ground, reducing population counts, or even taking an area out of production altogether. – Photo: Dr. Bruno Basso, Michigan State University

The premise of variable rate application, for example, dictates inputs should be applied based on what is specifically required in a given area. Knowing the overall stability of that area, though, shows what is truly possible.

If an area consistently receives nitrogen, but the benefit of that nitrogen is consistently not being realised – or at least not realised enough to pay for the application – it’s probably not worth it.

Take an area out of production altogether

The aforementioned “site specific adaptations,” says Basso, could then be made. This might include selecting for drought-tolerant varieties on unstable high ground, reducing population counts, or even taking an area out of production altogether; converting field edges to grass drives, for example, would both take the unprofitable area out of production while providing driveways for equipment – thus reducing things like compaction pressure.

“This is an example of how digital tools can increase profitability and reduce environmental impact,” Basso says.

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Mental barriers

However, he adds mental barriers on the part of producers are still a factor. It’s hard, after all, for a farmer to see land within a field and decide it’s actually more profitable not to grow crops on it.

“Farmers need to be rewarded and not squeezed […] they need good policies,” says Basso when referring to increasing societal and governmental pressure to reduce the negative impacts agriculture can have on the environment as a whole.

He reiterates accurate and effective management decisions can only be made with all-encompassing geospatial sensing systems – specifically those that combine and measure the interaction between soil, water, nutrients, plant health, topography, and other factors.