Off-target chemical application can produce strange patterns in fields. Some areas are not damaged, some are very damaged, and some are nearly dead. I’ve heard people say this unusual pattern will make it nearly impossible to prove yield damage in a field was attributable to dicamba drift. That might have been true in the past, but farmers with detailed scouting reports and accurate yield maps this season will disprove this. Overlay a map of plant tissue after off-target application with a map of yields after harvest.. If decreased yield corresponds with the areas affected by off-target dicamba damage—then the answer is pretty clear. Chemical drift caused the damage.
Likewise, if it is true that moderate dicamba drift will help the yield on non-dicamba tolerant beans this fall—I’ve heard this many times this summer—the yield map will show this correspondence. Climate Corporation's data will be able to prove this by this fall, if it is true.
Dicamba will also show us the limits of ag data platforms today. Google can tell where the flu is trending based upon online health data and where people are searching for cold medications. In theory, American farmers should be able to predict whether a particular pesticide is causing off-target problems based upon the number of complaints, satellite images, and ag data uploads. But there is no single database that collects and analyzes this information. States each have their own complaint database and farmers, retailers, and applicators are using dozens of different platforms to store ag data information, such as applications of pesticides, what crops are planted, etc.
This decentralized system of storing information won't help us predict when a certain pesticide is failing. That isn't just a dicamba issue, but a food security issue. Wouldn't it be great if we knew, based upon collective data reporting, where certain pests are problematic in the United States so that we could predict where these pests would appear next?
Big data platforms ought to be able to answer these questions before we get into the widespread mess we find ourselves in now.
But we still have a long ways to go.
One thing is certain, sorting out liability for dicamba damage is going to come from ag data platforms. Just wait and see.