Farms.com Home   Farm Equipment News

Farmers Deserve the Right to Repair Their Tractors

By Hannah Packman

Thanks in large part to the introduction of machinery like tractors and combines, farms today are far more efficient and productive than they were a handful of generations ago. Though these time- and labor-saving technologies can run tens or even hundreds of thousands of dollars, farmers often aren’t able to fix their machinery themselves – which has significant implications for their finances, privacy, and security.

A few decades ago, any given farmer often had the skills and tools needed to quickly make repairs if their machinery broke down. These days, however, it’s not so straightforward. Most modern farm equipment is technologically advanced, containing computers and sensors that collect and transmit data. As a result, specific software tools are typically necessary to address mechanical failures and other issues.

However, most companies refuse to make those tools available to farmers, making it exceptionally difficult to fix broken machinery on their own. They can’t even go an independent mechanic, since manufacturers won’t sell them parts or diagnostic tools either. This leaves farmers essentially no choice but to take their broken equipment to a licensed dealership.

This isn’t cheap. A farmer might spend thousands of dollars on a simple adjustment they could have done themselves with the appropriate resources. On the other hand, this arrangement has proven wildly lucrative for manufacturers; for Deere, as an example, parts and repairs are up to six times more profitable than selling the equipment itself.

But money isn’t the only problem – it’s also a matter of time. Oftentimes on a farm, tasks like planting and harvesting have to be done within a window of just a few days when the moisture content, ripeness, or weather conditions are just right. If, god forbid, machinery breaks during that window and a dealership can’t make an appointment immediately, the wait can cut severely into the farmers’ annual yields and income.

There’s also the issue of privacy. Equipment manufacturers collect lots and lots of data about soil, weather, yields, and other factors, which they can then share with or sell to “affiliates and suppliers.” This intentional data sharing in and of itself is worrying for farmers’ privacy, but even worse is the possibility of hackers accessing that information. Just last month, a security expert found vulnerabilities in John Deere’s apps that would have allowed outsiders to download the company’s data on farm equipment and vehicle owners.

In addition to data breaches, there are other potential security risks. Because most modern tractors can be operated and shut off remotely, some farmers and experts worry that hackers could disable thousands of tractors at a time. Such a widespread disruption could affect the entire country’s agricultural production, threatening livelihoods and food security.

Click here to see more...

Trending Video

Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.