The vast datasets generated by modern plant-science technologies require clever data-mining methods to extract useful information. Now, KAUST researchers have developed MVApp—an open-source, online statistics platform for conducting multivariate analyses of these intricate data.
The recent development of high-throughput phenotyping techniques has rapidly produced huge datasets on the characteristics of plants. These multivariate data hold crucial details about plant physiology: how a plant responds to different environments and how a plant’s growth patterns and potential yields change—all of which are valuable in developing sustainable agriculture and ensuring food security.
Image: The Arabidobsis thaliana plants shown here are growing on a conveyor belt that is part of plant-screening phenotyping system.
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