Is the Intelligent Vineyard the Future of Winegrape Growing?
Phil Asmundson is by no means a veteran viticulturist, but a half-dozen years ago, after watching his wife and business partner, Kim, auguring soil samples, he recalls turning to her and saying, “No offense, but there’s got to be a better way.”
And so began the Asmundsons’ quest to farm a 20-acre high-tech vineyard in Willcox, AZ, designed to produce ultra-premium wines. The term “high-tech” doesn’t do Deep Sky Vineyard justice, however. In fact, it is managed by a company called n.io so that once it is up and going, it could potentially be run with only minimal input from the grower — if that’s what the grower wants.
For example, they’re going to let n.io handle all facets of irrigation this coming year. It seemed like a logical next step after seeing the results of implementing the n.io system in 2016.
“It changed how we looked at the world rapidly,” says Phil Asmundson. “Most growers water by the hour. We did. But emitters can clog and we found what we thought we were putting on the vineyard was off by as much as 45%. Time is not the important metric; it’s how much you put on.”
Adds Kim: “And we have many, many different soils, which all react to irrigation differently.”
Clearly, a more individualized system was called for, Phil says. That, in essence, is what the n.io software platform provides.
“We have 15,000 vines and we listen to every one of them,” he says.
Blake Duhame is Program Director for n.io Ag. It is a division of n.io Innovation, a three-year-old Colorado company whose CEO, Doug Standley, worked with Phil Asmundson at Deloitte & Touche. Asmundson is an investor in n.io.
An artificial intelligence platform, n.io was built to be industry agnostic. In addition to agriculture, n.io has also been applied to industry where it is currently digitizing 45 factories, n.io’s core technology being the “secret sauce” behind all of them, Duhame says.
“What n.io can do in ag is become the farm’s universal nervous system for all sensing, logic, and control,” he says. “All this dumping of disparate, useless data on farmers becomes overwhelming. With n.io, real-time data from the field is not only being gathered, but autonomously acted upon in an intelligent way.”
For example, frost can be a devastating problem in the high desert of Arizona in the spring, where the average high temperature in April is 77°F, but the average low is 37°F. If n.io senses temperatures approaching freezing in the fruit zone, high humidity, and moisture on the leaves, it will turn on a frost fan, and text the grower that the fan has been turned on. As the temperature rises it will turn the frost fan off, sending the grower another text and warning that according to the forecast there could be another frost that evening.
“The possibilities are endless,” Duhame says. “You no longer have to manually keep track of all this information and then make decisions after the fact.”
Growers can let n.io make as many or as few decisions as they want, Duhame says.
“You can go all the way from n.io offering suggestions to n.io acting completely autonomously on the farmer’s behalf,” he says. “The beauty of n.io is in its simplicity.”