There is a difference between autonomy and automation. Autonomous equipment leverages learning systems through artificial intelligence (AI) and can perform without guidance from a human being. That differs from automation. Without the ability to “think” and “learn” via machine learning, neural networks or other means, it’s just automation. Certain machine functions can be performed automatically, but an operator is still needed to run the machine. While the groundwork is being laid in 2022 for autonomous solutions, automation is already here and paying big dividends for farmers.
When we look at autonomous systems today, they are still very early or “young” in terms of capabilities. I compare it to a young person who is just starting work on the farm. I’ll use myself as an example. When I first started to do chores on the farm, I was trusted with some of the easier tasks. One example was operating the grain carts. It’s a critical function, but it’s a great job for someone who is new to farming. That type of job is a good example of what would be some of the first tasks we see autonomy completing on the farm.
When we look at the autonomous chores that could be done on a dairy farm, a number of jobs are repetitive and high intensity. Those are among the first things that will begin to leverage AI to drive productivity. Autonomy could be used for milking, pushing manure, bulk packing within silage bays or bunks, re-bedding or even placing feed into feed troughs. Those are things I would have done at a young age and could be done as autonomous systems learn more and more.
But for the time being, for jobs that take a keen and trained eye, where the operator needs to take ownership of a task, automation comes into play. One of the things I expect to see more of is how we record real-time data from the crop itself as vehicles move through the field, especially where near-infrared reflectance (NIR) spectroscopy is concerned. A farmer will know the nutrient parameters and moisture of his crop – a critical factor when producing livestock feed.
Forage harvesters with yield and moisture systems can automatically vary the chopper’s length of cut based on the changing moisture content of the crop to ensure even packing and proper ensiling. The spout guidance system can automate truck or trailer filling by guiding the crop flow into the trailer. Camera systems automatically detect the trailer edge and crop mound, allowing the system to work with almost any trailer or truck.
Automation also provides ways to improve operator performance and can dramatically reduce operator fatigue since fewer operator interventions are needed.
A great example is on balers where sensors link the operation to the tractor. The baler can sense the density of the hay in the windrow and automatically match the tractor’s forward speed to crop load, maintaining a constant feed rate while baling. When the bale is completed, it also automates the tractor stop, bale wrap and tailgate raise and lower functions.
Another example is the automated engine management in self-propelled windrowers that adapts to changing crop conditions by lowering or increasing engine speed while ground speed remains constant to reduce noise and fuel consumption. And when long days of cutting turn into nights, operator fatigue can mean fewer acres are mown per hour. With just the push of a button, headland management automation can control ground speed, header lift and even merger lift to reduce fatigue and maintain high productivity.
In this challenging labor market, there’s a big benefit to automated technology. Automation that is available on today’s equipment can turn an average or inexperienced “C+” operator into a very productive “A+” operator.
- Precision Land Management Manager
- New Holland, North America