Precision and Smart Farming

Smart farming and precision agriculture: what’s the difference

People use the two terms loosely, but they mean slightly different things. Precision agriculture is about variation inside a field. Instead of one seeding rate, one fertilizer rate and one irrigation schedule for the whole field, you measure how soil and crop differ from place to place and manage each zone on its own terms. Our explainer on what precision agriculture is walks through the measure, analyze, act and review cycle.

Smart farming is the wider idea. It covers any use of data, connectivity and automation across the farm business: sensors on tanks and pumps, livestock tags, machine telematics, farm records software and robots, as well as precision field work. So all precision farming is smart farming, but a dairy that installs milking robots is doing smart farming without touching a field map.

Precision farming techniques in use today

Most farms adopt these one at a time, roughly in this order:

Guidance usually pays back first because the savings show up on every pass. Variable-rate work pays where fields are genuinely variable, so it’s worth looking at a few seasons of yield maps or imagery before buying a variable-rate controller. Our step-by-step piece on adopting digital farming practices in the right order puts rough costs against each step.

Farm automation and computerized farming

Computerized farming has been around longer than the phrase suggests. Grain dryers, irrigation pivots and feed mixers have run on controllers for decades. What has changed is that machines now share data. ISOBUS (ISO 11783) lets a tractor terminal run implements from different manufacturers, and telematics sends machine location, fuel and engine data to the office.

Full automation is still narrow. Driverless tractors are on sale for some tillage and grain cart jobs, robotic weeders and laser weeders work in vegetables, and milking robots are common on dairies. Most field operations still need someone in the cab or watching remotely. Our roundups of autonomous farm vehicles and IoT systems on farms describe what’s working now.

Precision farming examples by type of farm

On a corn and soybean farm, the usual sequence is auto-steer, then yield maps, then zone-based seeding and nitrogen rates on the fields where yield varies most. On an orchard or vineyard, the focus is water: blocks are irrigated separately, and imagery shows which blocks are stressed. On a smallholding, the tools are lighter, often just a phone and satellite-based advice.

One example from our own platform: a blueberry grower in Citrus County, Florida, monitors 25 blocks across 124 acres with our satellite crop monitoring. In one week the reports said no irrigation was needed on 78 of 175 block-days, and no fertilizer on 8 of 25 blocks. In his words, he has optimized both irrigation and fertilizer use by 30–50%. That’s his own estimate rather than a measured trial, but it shows where the savings tend to come from: the days and places where the crop doesn’t need an input.

Where to start with smart farming tools

Start with the decision you make most often or the input you spend most on, and pick the smallest tool that improves it. For many farms that’s guidance on the tractor or sprayer. For irrigated crops it may be soil moisture probes or satellite water-stress maps, which need no equipment in the field. Use the data you already have first: yield monitor files sitting on a USB stick are a common untapped source. Ask any vendor what format their data comes out in and whether you can take it with you if you switch.

Limits worth knowing

Precision tools are only as good as their calibration and the agronomy behind them. An uncalibrated yield monitor produces confident-looking maps that are wrong. Imagery shows that a zone is stressed, not always why, so someone still has to walk to it. Rural connectivity limits real-time systems in many regions, and data from different brands often doesn’t combine without effort. None of these are reasons to avoid the technology, but they’re good reasons to adopt it in steps.

Cost is the other limit. A tool that saves a few dollars an acre pays back quickly on a large farm and slowly on a small one, so work out the payback on your own acres before buying. Subscription services that need no hardware, such as satellite monitoring, are usually the cheapest way to test whether field-level data changes your decisions.