35. Growth forecasts: how to make them and what they really mean

In advanced indoor farming, growing is no longer about "observe and react," but about predicting and optimizing.
Growth forecasting is one of the key steps that separate an automated plant from a truly data-driven system.

In this article we analyze:

• what growth forecasts are,

• what data are needed to construct them,

• how they should be interpreted,

• and why they are central to Tomato+ systems.

What is meant by "growth forecast"

A growth forecast is a probabilistic estimate of a plant's future development, based on real data and mathematical models.

It covers not only how much a plant will grow, but:

• speed of development

• final biomass

• harvest timing

• uniformity of the cycle

• risk of stress or slowdown

In summary: anticipate biological behavior before it becomes visible.

Why predictions are impossible without data

In traditional cultivation, predictions are often intuitive.
In professional indoor farming, however, they are statistical.

To be reliable, continuous and structured data are needed, including:

• light (intensity, spectrum, photoperiod),

• air and solution temperature,

• humidity,

• EC and pH,

• growth images,

• history of previous cycles.

Without time series, there is no prediction: there is only hypothesis.

Static vs. dynamic forecasts

Static forecasts

Are based on:

• a variety,

• a set of fixed parameters,

• an "ideal" cycle.

They work only if nothing changes.
In reality, they are always changing.

Dynamic forecasts

They continuously update the estimate based on actual data coming in from the system:

• if the plant grows more slowly → the prediction is corrected,

• if it reacts better than expected → the cycle is shortened,

• if a stress emerges → it is anticipated.

Tomato+ systems work exclusively on dynamic predictions.

The role of artificial intelligence

AI does not "guess" growth.
It recognizes patterns.

It compares:

• current growth,

• thousands of previous cycles,

• similar environmental conditions,

• known physiological responses.

From here it constructs:

• predicted growth curves,

• optimal harvest windows,

• probability of deviation from target.

The value is not the single prediction, but the vanishingly small error over time.

What a growth forecast really means

A forecast is not a promise.
It is a decision-making tool.

It is used to:

• plan crops,

• optimize energy consumption,

• compare varieties,

• test parameters without production risks,

• standardize quality.

Those who interpret forecasting as "absolute truth" misuse it.
Those who use it as a compass, scale.

Common mistakes to avoid

1. Relying on a few cycles
   Early data are for learning, not decision-making.

2. Not contextualizing
   The same variety may grow differently in different environments.

3. Ignoring biological variability
   The plant is not a machine: prediction is always probabilistic.

4. Do not close the feedback loop
   Without comparison between predicted and actual, the system does not improve.

Forecasting and competitive advantage

In advanced indoor farming, the advantage is not producing more.
It is knowing ahead of time what will happen.

Companies that master this aspect:

• reduce waste,

• increase uniformity,

• they plan better,

• they turn every cycle into a data asset.

And this is where farming becomes technology infrastructure, not traditional agriculture.

Conclusion

Growth forecasting is not about "controlling nature," but about collaborating with it intelligently.

In the Tomato+ model, each cycle:

• produces vegetables,

• but more importantly it produces data,

• which improves all future crops.

The result is not just more yield, but more predictability, and that is what makes a system truly scalable.

Thank you for reading this article. Keep following us for new content on hydroponics, vertical farming, and smart agriculture.
Tomato+ Team