A stress detector for plants has raised $10.8m in a seed round. Agri-tech start-up Gardin is developing a low-cost optical phenotyping sensor that will give a real-time indication of plant health and predictions of ripening, nutritional content and yield.
The seed round was led by Molten Ventures, with investment by LDV Capital, Seedcamp, MMC Ventures, Alchimia Investments and angels.
Sumanta Talukdar, Gardin Founder & CEO, “Gardin are pleased to announce Molten Ventures as the lead investor for this seed round. We always put a huge emphasis on focused partnerships who share our ambition and we found exactly that when we met the team at Molten Ventures”
Gardin were featured in the Start-Up Showcase at REAP 2021, when lead biologist, Fabrizio Ticchiarelli, explained: “We can detect stress in the plant before it is detectable by eye.”
Most current sensors monitor the environment or the physical changes in the plant resulting from sub-optimal conditions, and there can be a delay before these appear. Gardin’s approach is to instead look at the cellular processes within the plant, which adapt on much faster timescales, and aims to provide recommendations for action.
Photosynthesis drives plant performance
Fabrizio explains that the goal when growing plants is to increase their biomass, and photosynthesis is the key to this: “It is possible to gauge how efficiently photosynthesis is occurring within each leaf of the plant by measuring fluorescence coming from the photosynthesis pigment, chlorophyll.
“As photosynthesis is so fundamental to plant health, it is linked to many molecular pathways in the plant. If a plant is stressed or limited by a lack of water or a nutrient, it diverts energy away from growth and towards other processes to compensate – we can pick up that change by monitoring chlorophyll fluorescence.
“We have completed trials, particularly with growers in controlled environments, to look at patterns of change across the plant in response to different stresses. We use computer vision to assess where the changes are happening, for example if they manifest first in younger or older leaves or if they are specific to a certain part of the plant.
“By looking at changes in the photosynthetic signal we will be able to determine what type of stress is occurring and how to get things back on track.”
The predictive power of the tool relies on data, so Gardin is currently building up its datasets for several uses: to optimise light usage in vertical farming; to identify where stress is occurring across a crop for precise interventions; to forecast yield; to quantify fruit ripening to infer the best time for picking; and to track and improve shelf-life and storage post-harvest.”
Commercial product for broadacre
Gardin has developed a sensing technology which has been trialled in vertical farms and is about to begin trials in greenhouses and polytunnels. The next iteration, which is close to the commercial product, will also be used for broadacre applications.
Mounted in a polytunnel, the sensor swivels to cover a large area of the canopy. If photosynthesis drops, due to drought, frost or overheating, the Gardin device will respond with an emergency alert.
Gardin’s machine learning algorithms deliver actionable, real-time insights that enable crop growers to optimise yield, improve unit economics, and sell products high in nutrition. By building up a large unique dataset around crop health and nutrition, Gardin’s long term vision is to become the go-to data marketplace in the global food supply chain.
The company plans to use this injection of capital to fuel their growth in Europe and North America, as well as scale its penetration in greenhouses and vertical farms.
Gardin also plans to improve their sensors and to release new advanced analytics features such as crop forecasting and nutritional density mapping.Fabrizio explains: “The immediate goal is to give farmers direct insight into what they should do next to improve yields. “The long-term vision is to deliver a low-cost high-throughput phenotyping platform for all growers, breeders and the food processing industry.”