Researchers at the University of Zurich have developed a method, PlantServation, which uses big data, machine learning and field observations to observe how plants respond to changes in the environment. PlantServation is a method that incorporates robust image-acquisition hardware and deep learning-based software to analyze field images, and it works in any kind of weather. Using PlantServation, the researchers collected images of Arabidopsis plants on the experimental plots of UZH’s Irchel Campus across three field seasons and then analyzed the more than four million images using machine learning. The data recorded the species-specific accumulation of a plant pigment called “anthocyanin” as a response to seasonal and annual fluctuations in the environment.
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