Field Trials Podcast – Reliable, rapid, and reproducible field data | Part 1

What’s required to remove all guesswork from soil and crop analysis? According to Raj Khosla, professor, researcher, and precision agriculture expert at Kansas State University, inexpensive and practical sensors are the solution.

In the first part of this episode of Field Trials, Khosla discusses how different types of field sensors could close the gap between on-the-ground realities and estimates based on surrogate data provided by pre-existing – albeit increasingly effective – tools like UAVs and satellite imagery.

“If we take a soil measurement at one point and another two feet apart, the likelihood those samples are related in space is high. If the second sample is 20 or 200 feet away…as we increase the distance from one to the other, we’re reducing the chances the two locations, and hence the properties of those locations, are related in space. That’s called spatial distance at which the relationship between two points break-off,” says Khosla.

“For us to be able to derive what’s happening between the two points, we need to take measurements at a shorter distance where two points are related in space.”

Want to know more? Listen to part 1 of the interview below and make sure to visit our Youtube channel for more Field Trials content.

Do you have an interesting topic or opinion to discuss? Make sure to get in touch with the Future Farming team by emailing to futurefarming@misset.com.