Sometimes, you’re wrong.
When you model a crop or weather, you are sadly bound by the laws of comparison. The outcome of your model depends entirely on the analog years you input into the model. Essentially, you observe trends in the current year, match them to comparable years from the past, and base outcomes on the outcomes of those comparable years. The problem is that any minor shift in a trend leads to a different outcome.
It’s much like trying to draw two parallel lines. If they’re not exactly perfectly parallel, somewhere down the line, they start to diverge, wildly sometimes, and you stop to wonder if they were ever parallel in the first place.
Who cares, right? Well, if you don’t, go ahead and stop reading now. You’ll be one less person to whom I admit that I was wrong this year. Or I wasn’t totally wrong, but…
At some point in recent history, I said that our corn crop would struggle to be average this year. I didn’t predict any major catastrophe, but I said that our corn would end up with light test weight. It’s obvious now that this prediction was incorrect. Our corn isn’t light test weight at all. In fact, it’s a bit heavy. It didn’t struggle to be average at all—in fact, it exceeded average.
So I wasn’t totally wrong, but I was kind of wrong. Fortunately, it’s the kind of wrong that we (including myself) can be happy about: things are better than what I predicted.
But I’m unused to being wrong—those of you who know me know this—and I gotta ask: What happened?
What happened was about three weeks of clouds mid-season. The lack of sun drove down temperatures, which reduced nighttime respiration (a good thing), but also drove down photosynthetic activity (not a good thing). I thought that our loss from reduced photosynthetic activity would be greater than our gain from reduced nighttime respiration, thus a net loss for us and our crops, and thus light corn.
Except the net loss wasn’t nearly as great as I thought it would be.
To further divide the models from the reality, during these three weeks, our corn was accumulating only 10-12 GDUs per day instead of the predicted 27-28. Much like a snow day in December gets tacked onto the end of the school year in May, these unaccumulated GDUs get tacked onto the end of the growing season. In all, the three weeks of clouds resulted in a growing season 13-14 days longer than usual.
And here’s the awesomeness and the point at which my prediction of light test weight corn became very wrong: those 13-14 extra growing days were great. For the first time in recent history, we ended our growing season with adequate water and our plants were in good shape and super happy. So they took major advantage of those extra days and boom! Heavy corn.
There are a few lessons here:
1) Plant physiology rules the day. Know it. Love it.
2) Don’t predict. Especially me. MZ=no more predictions. It’s not really my job to predict anyhow, but rather to lay out the possibilities that exist. I don’t know what the weather is going to do, or what tomorrow is going to bring. But I do know that if the weather does this, we should do this, or if the weather does that, we had better do that.
Those of you who know me might also be thinking here, hey, he’s just covering his butt. But I’m not. Any prediction is a null proposition: its right until its proven wrong. Then that new thing becomes the proposition and its right until its proven wrong. Maybe this is unsettling if we think too much about it, but really, that’s what the entire process of learning is.
I’m humble enough to admit that I am still learning. I learn every day. And when I learn that I was wrong, I’m agronomist enough to admit it.
(And what a sweet way to be wrong, right? Enjoy your better-than-average harvests, dear friends.)