Verification in Field Application: Going the Last Six Feet
While I love a good road trip out in the country as much as any agriculture industry editorial type out there, it’s always nice to get the occasional visit from companies wishing to show us the ins and outs of their product offerings.
As an aside, this is probably more commonplace for most of our media friends, but we here in the Cleveland area are a bit more off the beaten path, so folks need to make the extra effort.
Anyway, it was the team from UAV manufacturer AeroVironment, and we got a peek at their Quantix system, including a cool new drone and tablet-on-steroids hardware combination paired with imagery interpretation software with some nifty capabilities.
There were some things I liked, in particular their approach to the product. It’s a tool to give the human experts more usable data for both immediate action and long-term planning. The system is very simple to use. I also appreciate that they’re a one-stop shop — if there’s an issue with any part of the system, there’s one number to call for help.
Definitely interesting — but not the primary focus of this month’s editorial. It was the between-the-lines discussion that led to what I’m about to impart.
Matt Strein, Director of Business Development and our master of ceremonies for the demonstration, was providing some case studies to help illustrate the benefits of employing his system. One that frequently arose with his corn belt examples was “verification.”
It took a little time into the case study to see where he was going with this, but it soon emerged. The farmer is convinced he’s doing the right thing, that there’s no significant variability in the field. The drone flies the field and records the reflectance imagery, only to find swaths of sickening, yield-challenged light green in some areas of the field.
Which takes us to the term “verification,” which is really just a nice way of saying, “The cooperative messed up the application, and here’s your proof.”
Apparently, the spinner-spreader malfunctioned somewhere during the application, leading to a noticeable issue with nutrient availability to part of the field.
I stopped thinking about the benefit of “drone-based verification” and flipped to how, after more than two decades of variable-rate applying fertilizer, are we still falling short on the last 6 feet?
Was it the machine failing to warn the applicator, or was the applicator, under seasonal duress, too quick to dismiss a malfunction and simply carried on?
I understand that things can happen. Hopefully, the cooperative was every bit as upset as I was and took steps to reduce the potential for another problem. I hope the equipment dealer was made aware of any issue that may have occurred with the unit and sent the message to corporate, which in turn looked into mitigating any systemic problem. I hope that everyone involved got appropriate training to ensure that the occurrence of issues like these get minimized.
“Verification” is likely to proliferate with improvements in imagery and the availability of more tools. At the end of the day, we’re judged by the service we provide. Trust erodes when, for whatever reason, something goes wrong.
Mistakes happen. But we, along with the equipment dealers we ally with, and the manufacturers behind the machines need to work closely to ensure we’re not only on time but also on target to the best of our abilities.