2015 Essential Guide to Precision Farming Tools

Data management software is featured in the Fall 2015 edition of Precision Farming Dealer.

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We often “ooh and ahh” at the sight of fancy new gadgets, mesmerized as technology marketers dazzle us with reasons why we just have to have their product. Sometimes we give in to the hype and buy that new Apple Watch or that ShamWow towel that’s supposed to magically replace the “$20 per month” we spend on paper towels.

I remember learning about a technology research company, Gartner Inc.’s Hype Cycle, at the 2014 InfoAg Conference, and I thought, “What a great way to explain technology trends.” The initial phase is limited to early, proof-of-concept stories and media attention that sparks the hype. Then, expectations increase as a result of all the publicity. People begin to believe that “the hype is real.” This is the stage where many companies begin to enter the market.

In the third stage, the technology enters the “Trough of Disillusionment” where interest begins to fade, and producers of the technology either shake out or fail. After that, the surviving companies have enough data and success stories to demonstrate the proof of concept. The technology then begins to become widely understood by the general population. In the final stage, the “Plateau of Productivity,” these once emerging technologies begin to go mainstream.

Promises of maximum economic yield, less stress on the crop and greater efficiencies drive the hype of data management software in agriculture. During the past two-plus decades, farmers have seen the hype become reality.

Data management tools started making their way into farming in the 1980s with manual site-specific soil sampling and manual variable-rate fertilizer application. When variable-rate became more automated, we would burn Eprom data cards to run the VRA and record data. We didn’t have the overlays to be able to see correlation on our computers. In the ‘80s and ‘90s, we printed out soil type maps, soil test maps and yield maps and laid them out on a conference table to try to find correlations.

Today, we’re able to use laptops and tablets to pull up treatment analysis tools that will show comparisons among different things such as yield-to-soil type, yield-to-variety and yield-to-soil test levels, to name a few.

In the late ‘80s, I had customers who were doing site-specific sampling and site-specific application, but they were doing it manually with flags. They were going out to flag the different management areas within the field, manually setting the rate on their spreader and spread each area. Data management technology back then was certainly helping to improve production decisions, but there was still a lot of manual labor involved and wasn’t very efficient.

The mid-‘90s was the height of the technology hype in farming. Everyone was excited about grid sampling, variable-rate application and yield maps. These technologies were in every farming magazine. This was also around the time when GPS was made public. The problem was, no one made a consistent business out of it. So in the trend of the “hype cycle,” toward the end of the ‘90s and into the early 2000s, data management and the associated software tools dropped off the “hype scale.”

Many data management software technologies have become mainstream in farming and farm customers are seeing a return on their investments by using these technologies. Thirty years ago, the focus was on maximum economic yield for an operation. We then started to drill down to individual fields within those operations and today, we can be very specific and find troubled spots in specific areas of a field. Farmers are understanding that collection and management of data can increase their production, profits and also help them practice environmental stewardship in the process.

While there will always be hype surrounding technology in any industry, some of it is justified. Data management software has evolved exponentially over the course of time and will continue to provide farmers with solutions to achieve maximum economic yield.