One of our customers once compared using soil moisture sensors to driving a new car with parking sensors.

“At first, you don’t trust them,” he said.
“You still turn your head. You still look in the mirrors. Only after a while do you start to rely on the beep.”

Smart irrigation works in much the same way.

Growers don’t suddenly hand over decisions to data. They learn to work with it. They test it against reality. And over time, they decide how much trust it deserves.

Irrigation decisions are made in the field, not in an app

In theory, irrigation decisions seem straightforward:
the soil dries out, the system signals it, and water is applied.

In practice, it’s rarely that simple.

Growers juggle limited irrigation capacity, fixed reel schedules, distance between fields, labour availability and changing weather forecasts. Often, several fields need attention at the same time, but only one can be irrigated first.

That’s where sensors start to add value — not by telling growers what to do, but by helping them decide where to start and what fields to prioritize.

Multiple growers described using the data mainly to set priorities:

• Which field is drying out fastest?
• Which one can safely wait another day?
• Where does irrigation actually make the most difference right now?

The final decision remains theirs. The data simply makes that decision easier to justify.

“I still dig — but I dig with more confidence”

Almost every grower says the same thing: they still check their fields themselves.

They dig. They feel the soil. They look at the crop.

What changes is the conversation they have with the data.

Sometimes the sensor confirms what they already suspected.
Other times it challenges assumptions — especially when the surface looks dry, but moisture is still available deeper in the root zone.

Several growers mentioned that without the sensor, they would have irrigated earlier. With the data showing the field still within range, they decided to wait.

That single decision can save time, fuel and water — but just as importantly, it builds confidence and helps them check when there is a reason to do so.

When “suboptimal” still delivers top results

A recurring theme in the interviews was how growers interpret the moisture bands.

Fields that spend much of the season in Agurotech’s “light green” or slightly suboptimal zone often still deliver excellent yields. In some cases, they perform better than fields that are kept constantly at the top of the optimal range.

Growers explained why:

• slightly drier conditions reduce disease pressure
• roots are encouraged to grow deeper
• soils remain more workable
• timing stays flexible

One grower put it simply:
“If I am in the orange zone, I’m already too late.”

Over time, growers learn how the bands relate to their own soils and crops. The data doesn’t dictate decisions — it becomes something they learn to read, much like weather forecasts.

Advice needs to fit the system — not the other way around

Another practical reality came up again and again: irrigation systems have limits.

Many growers work with standard gift sizes of 18–20 mm because that fits their reels, pumps and daily planning. When advice suggests higher volumes, they don’t reject it — they adapt it.

Instead of changing their entire setup, they adjust timing and frequency.

As one grower explained:
“I don’t change my system. I change my planning.”

This kind of translation is exactly how decision support is meant to work. Useful advice respects the way farms actually operate.

Trust builds over seasons, not weeks

Very few growers fully trust new data in the first year.

The first season is about comparison:

• does the sensor respond after irrigation or rain?
• does it match what I see when I dig?
• does it make sense on this soil?

In the second season, patterns start to emerge:

• which fields always dry out first
• when waiting pays off
• when acting early prevents stress later

Only after that does the data really become part of daily planning. Not because the technology changed, but because the grower learned how to work with it.

Just like parking sensors: you don’t stop checking your mirrors on day one. You stop because experience shows the signal is reliable.

Why this approach works

Growers aren’t looking for systems that take over control. They’re looking for tools that support better decisions in a complex, unpredictable environment.

The technology that sticks:

• fits existing workflows
• leaves room for judgement
• proves itself over time
• reduces doubt rather than adding complexity

Smart irrigation isn’t about following perfect advice. It’s about learning when to trust the signal — and when to rely on experience.

And once that balance is found, the system doesn’t feel new anymore.
It simply becomes part of how the farm runs.