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Fitness - OSTI GOV

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Last Updated: 04 August 2022

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High–throughput measurement of plant fitness traits with an object detection method using Faster R–CNN

Genetic contributions to plant phenotype are often discussed, because loss-of-function results can be subtle or obscured by varying degrees of genetic redundancy. Two Arabidopsis fitness characteristics were determined by an image segmentation-based method using the Faster Region-based Convolutional Neural Network algorithm, and an object detection-based method using the Faster Region-based Convolutional Neural Network algorithm. Fruit counts revealed the same results for two genes as well as wild-type and 12 mutant lines, showing fitness consequences for three genes.

Source link: https://www.osti.gov/biblio/1876374

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions