Researchers from Imperial College London (ICL) and Syngenta have developed a computational tool that uses machine learning to find complex patterns in data about the behavior of plants. The use of machine learning means agricultural researchers will be able to analyze plant biology in minutes, even if they lack certain information about the inner workings of plants. With previous mathematical modeling tools, finding nuggets of information could take months or even years. “We believe our computing tool will revolutionize agricultural research by making the process much faster than is currently possible using conventional techniques,” says ICL professor Stephen Muggleton. “We hope that our new technology will ultimately help farmers to produce hardier, longer lasting, and more nutritious crops.” The researchers are currently testing a prototype of the tool, which will help agricultural scientists predict how genes inside plants will react to different chemicals or environmental conditions. For one project, the tool will be used to analyze how different genes affect the way a tomato’s flesh hardens and tastes, and the findings could lead to new tomato strains that are tastier, or redden earlier and soften later to prevent them from spoiling when they are transported to market.
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