AI, Machine Learning, Deep Learning, Neural Networks. The words may be familiar or be a total mystery. Only recently have those terms been used in conjunction with agriculture and often as part of a marketing ploy because it sounds futuristic.  

Very rarely do you see proof of AI (Artificial Intelligence) use in agriculture, which is understandable considering it’s an area of technology that is still evolving, and the IP will prove to be incredibly valuable for those that conquer the algorithms.

As we’ve seen in the past few years, it’s easy enough to say you’re using AI but harder for a grower to ask for proof until the models bear fruit (excuse the pun).

In CEA or Controlled Environment Agriculture this method of growing crops is known for its sustainable practices in reducing land usage, water, pesticides and other factors that often impact outdoor crops. The concept of introducing AI to CEA creates even more exciting possibilities for the entire industry.  

Imagine what other savings could be made when you introduce accurate AI modelling into the production process.

When you talk about AI what exactly do you mean?

We’ve found the definition differs depending on who you ask but most would agree that AI or Artificial Intelligence is an umbrella term that includes the subfields machine learning, deep learning, neural networks, computer vision and natural learning processing.

Simply automating something to do a basic task is not applied AI nor is forecasting yield which is often mistaken for prediction.

Historically AI was used in military and cognitive science to look at problem solving methods and creating intelligent technology that can mimic human behaviour. It’s this idea that makes people think of robots invading the earth or losing control of decision making in your business. The truth is a lot easier.  

For WayBeyond, the use of modelling (mathematical algorithms that are “trained” using grower data and additional information) is where we believe actual AI begins and is the next level in data driven farming.

This graphic shows how we define AI and examples of how data is used.

How is AI being used now?

The potential for A.I. technologies is unlimited but what we do know is how it’s being used currently with yield prediction.

WayBeyond is working with some of the largest producers in the world supporting their programmes and increasing accuracy of yield by 5-15%.

An increase in accuracy allows growers to plan harvest dates, labour requirements, marketing campaigns, distribution channels and other pre and post-harvest activities. All saving time, labour and money.

Find out more on tomato crop yield prediction.