Bringing predictive decision support to the paddock: our investment in Flurosat

Flurosat’s founder Anastasia Volkova

Here at AirTree, we are always thinking about industries where Australia has a significant competitive advantage in developing world class disruptive software solutions. We believe Agriculture is one of those industries, with over 50% of Australia’s land mass used for agricultural purposes. We are excited to announce our first AgTech investment into Flurosat’s seed round.

In order to optimise their crop yields, farmers enlist the help of agronomists. An agronomist will take manual plant tissue samples and send them to a lab for analysis in order to make recommendations to farmers. This process is often flawed. Agronomists can only take a limited number of samples and labs take at least several days to return results. Unfortunately the delay in sampling and processing can mean issues are picked up later than is ideal and the limited data points are not sufficient to optimise variable rate application of water, fertiliser or pesticides. In the best case, farmers get “hectare-level” optimisation recommendations and the delay on these recommendations can mean they are irrelevant by the time they are received (i.e. it rains in between sampling and results).

Enter Flurosat.

Flurosat uses computer vision and smart algorithms to improve crop yields. In real time.

The company uses remote sensing technology to capture images from satellites, planes and drones and applies hyperspectral imaging and analysis to identify nutrient deficiencies, water stress, heat stress, weeds or disease long before these issues would be visible to the naked eye. Often crop stressors and deficiencies will vary across a paddock and Flurosat’s machine learning algorithms identify and highlight small areas suitable for specific treatment.

In the short-medium term, Flurosat will provide agronomists and farmers with detailed data on variability across paddocks, allowing agronomists to scale their services and farmers to tailor their water, fertiliser and pesticide application to optimise yield and reduce waste. The beauty of machine learning is that Flurosat’s recommendations will become increasingly more accurate over time as more data is uploaded to Flurosat with each harvest, allowing the system to adapt and learn to further improve outcomes for crop farmers.

In the longer term, Flurosat will serve up highly specific and granular insights for agronomists and farmers delivered in near real time. Flurosat will enable a future in which an autonomous tractor sprays crops delivering the precise amount of water, fertiliser or pesticide required for each plant’s individual needs. Flurosat is building the toolset to make this a reality and it has the power to not only improve an individual farmer’s yield and reduce their costs, but also significantly reduce water consumption and fertiliser/pesticide waste at a much larger scale.

A big vision like this takes an outstanding founder to execute it. We are very excited to be working with Flurosat’s founder Anastasia Volkova. Anastasia has many of the qualities we see in extraordinary founders. Anastasia cares deeply about improving outcomes for farmers and reducing the environmental impact of crop farming. She was managing a team of 370 people when she was just 19 years old and she hasn’t slowed down since. Anastasia is completing her PhD in autonomous drone navigation at The University of Sydney and won first prize in the university’s Inventing the Future program for top postgraduate students. While growing Flurosat, Anastasia has hustled her way into key industry partnerships which have allowed her to prove out Flurosat’s technology across multiple crops and growing seasons in the 12 months since the business was founded.

We look forward to working with Anastasia and the Flurosat team and are excited to be supporting their seed round alongside our friends at Main Sequence Ventures and the CRDC.

by Elicia McDonald & John Henderson