Scientists are using artificial intelligence software to analyze plant root systems, laying out a protocol that can be applied to gather data on crop and model plant phenotypes (physical characteristics) more efficiently and with equal or greater accuracy than existing methods.
Scientists are using artificial intelligence software to analyze plant root systems, laying out a protocol that can be applied to gather data on crop and model plant phenotypes more efficiently and with equal or greater accuracy than existing methods.
What's more, tracking these physical root system characteristics helps scientists find genes affiliated with those characteristics, as well as whether multiple root characteristics are determined by the same genes or independently. This allows the Salk team to determine what genes are most beneficial to their plant designs.
What sets SLEAP apart is its unique use of both computer vision and deep learning . This combination allows researchers to process images without moving pixel-by-pixel, instead skipping this intermediate labor-intensive step to jump straight from image input to defined plant features. This step -- connecting phenotype and genotype -- is crucial in Salk's mission to create plants that hold on to more carbon and for longer, as those plants will need root systems designed to be deeper and more robust. Implementing this accurate and efficient software will allow the Harnessing Plants Initiative to connect desirable phenotypes to targetable genes with groundbreaking ease and speed.
Other authors include Lin Wang, Hannah Carrillo, Kimberly Echegoyen, Mikayla Kappes, Jorge Torres, Angel Ai-Perreira, Erica McCoy, Emily Shane, Charles Copeland, Lauren Ragel, Charidimos Georgousakis, Sanghwa Lee, Dawn Reynolds, Avery Talgo, Juan Gonzalez, Ling Zhang, Ashish Rajurkar, Michel Ruiz, Erin Daniels, Liezl Maree, and Shree Pariyar of Salk.
Nature Botany Climate Global Warming Environmental Awareness Computer Modeling Software Artificial Intelligence
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