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Are You a Precision Grower?

From Cotton Grower Magazine – November 2017

 

Are you a “precision grower”?

Don’t answer this question too quickly. Some specialty crop growers are steeped in cutting-edge technologies yet don’t see themselves as being practitioners of precision agriculture. Conversely, there are thousands of row crop growers in the U.S. using fairly commonplace technology – GPS-guided autosteer, for instance – who consider themselves precision adopters.

So who’s right, and who’s wrong?

To answer this question, we must get to a durable definition of precision agriculture that is specific enough to distinguish between real users and non-users, yet is at an altitude high enough to transcend multiple crop areas and constantly evolving technologies. At Meister Media, we feel precision programs are as real for specialty crop growers they are for row crop growers. Let me tell you why.

An Enduring Definition of Precision

More than 20 years ago, a representative of a high-tech defense contractor that was vitally interested in entering ag markets gave me an in-person demo of GPS in action. It was a memorable experience, yet his definition of precision agriculture was equally unforgettable. “It’s really all about use of data,” he told me then. “Data gathering, data analysis, and data application – that’s it.”

I believe this definition of precision agriculture remains largely valid today, and it’s expressed in the accompanying chart that is guiding our ongoing coverage of PrecisionAg® Cotton. By our definition, a true precision grower must do all three of the following:

Data gathering (G). This once was mostly about grid soil sampling and yield monitors in row crops. But in today’s specialty crops, we have imagery from drones and airplanes and satellites, data from soil sensors and moisture sensors, sophisticated weather forecasting, and on and on. The list of data sources is now nearly endless, but it’s also nearly useless if there isn’t …

Data synthesis and analysis (Syn-An). In the early days of precision, this often meant one-dimensional colored field maps of, say, yield and fertilization. But today’s sophisticated farm management software platforms can house dozens of data points and layer them so that a grower, agronomist or consultant can compare, contrast, and analyze the data to their heart’s content. How did X variety do in field X in a rainy season with heavy insect pressure and light nitrogen application? Such programs can theoretically give you that answer.

Data application (Appl). Data gathering, synthesis, and analysis are moot if the wisdom they represent doesn’t reach the field – e.g., if the variable-rate planter breaks down, or if the hi-res camera installed to monitor pest populations and regulate the release of mating disruptors misfires. In fact, I think precision is soon going to see a resurgence in the design and engineering of practical field application tools.

In the meantime, I do think a fourth dimension of technology merits consideration in any precision grower’s operation:

Postharvest (PH). Technology, data, and connectivity – vital to linking up and giving the full picture to in-field production – are extending as well to packinghouse automation, to storage and transport sensors, and to the traceability/sustainability programs that are increasingly favored by large food manufacturers and retailers.

“Moneyball” for Agriculture

You ask: But haven’t we growers been doing all this all along – gathering, analyzing, and applying information?

You have. But here’s an analogy. Precision agriculture rightly has been compared to “Moneyball” in sports. Baseball scouts long have collected data on players and analyzed it and used it to make batting orders or draft-day decisions. And yet, are baseball executives who are armed merely with radar guns, laptop computers, and “hunches” about their players entitled to call themselves “Moneyball” practitioners? I think not.

They do merit that distinction, however, if they collect multiple data points on individual players in myriad game situations, mix data and crunch it in countless ways, and filter it through their own lens of practical experience – all in the service of producing pre-agreed-upon, highly measurable outcomes.

In baseball, the intended outcome of “Moneyball” typically is wins. In precision agriculture, it’s typically yield or crop quality, and often both.

So I ask again: Are you a precision grower? If you’re not, are you ready to become one? You may be closer than you think.

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