Artificial-Intelligence Powered Digital Agronomy

[fa icon="calendar"] January 10, 2018 8:45:00 AM EST / by Jonathan Feist


By Jonathan Feist,  Business Development Manager

Easily viewing your crop progress and standardizing your recipes

When asking greenhouse growers about how they grew their best crop, you normally receive some combination of “we used last year’s crops as a standard,” to intuition, to good luck (read: the weather) and more.

This does have varying degrees of success, mind you.  But as we begin to see trends of traditional farming systems move into controlled environments (greenhouses, indoor farms, etc.,) we unlock the potential for data to help us standardize our growth processes, and therefore repeat and improve upon them. 

This one reason Motorleaf has created an artificial-intelligence powered Grow Journal, organizing recorded environmental data into a hyper-intuitive, multimedia record of crop cycles.  This comes as one part of our larger software platform, 


Doing it right, again and again

If you grew a very successful crop—i.e you enjoyed high yields, better tasting vegetables, better smell, etc.,—how do you ensure that this happens the same way next time?  Often, we’ve spoken to greenhouse operators who rely on the know-how and experience of their head grower.  But if that grower decides to take a job up the road, the operator might find themselves stuck trying to fill in the blanks of best practices for their vegetable, greens, or cannabis plants.

“Keeping a record of your crops allows greenhouse operators to have a detailed understanding of exactly what the environmental conditions were during their crop cycle,” says Motorleaf co-founder and CEO Alastair Monk, “and without a record, it’s a lot of best guesses and reliance on a small band of growers.” 

Part of our solution, included in the software platform, was the Grow Protocol Journal. Humidity, C02, temperature, light spectrum levels, time-lapse video, as well as user-inputted notes and pictures all can be recorded, and divided into neat, organized “journal entries,” or crop protocols, per crop cycle.  This means a huge increase in the standardization of the way we grow crops, and an intuitive interface to make the experience easier and more effective.

Incorporating Machine Learning and Artificial Intelligence

As the accumulation of data occurs, it is categorized and analyzed: we call this the grow vault. Then we build a system, using artificial intelligence, that improves in its ability to address challenges related to a specific growing environment. This is how we are able to incorporate services like yield predictions (read about it right here) and crop modelling into logo 3-1.jpg

By increasing the amount of data that is received, and building custom machine learning algorithms for each greenhouse environment, we can help greenhouses continuously improve their grow protocols, by analyzing the data and finding patterns until…. wait for it… the perfect crop blooms!

You can find more about the Grow Protocol Journal and the platform by downloading our brochure:

Read Now

Sleep Well, Grow Well.


Topics: indoor agriculture, agriculture, ai, data, artificial intelligence, machine learning, greenhouse, tomato, agronomist, virtual agronomist, controlled environment agriculture, cannabisbusinesstimes, automation, cucumber, cannabis, vegetable, marijuana, grow journal, agronomy, peppers, yield prediction

Jonathan Feist

Written by Jonathan Feist

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