Pokorny, Alexandria A

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ISU ReD: Research and eData

Color Space Standardization and Image Analysis forHigh-throughput Phenotyping of Sorghum bicolorAlexandria A. Pokornyaapokor@ilstu.eduIn plant science, high-throughput phenotyping is an important tool for gene discovery and analysis andimproved crop breeding. For the process to be high-throughput, thousands of images must be collected perday. Advances in computational technics have made automated image analysis the most efficient way toprocess these image sets. Image analysis for high-throughput phenotyping starts with image segmentation,the process of classifying pixels containing plant from pixels representing background. Highly specializedsystems for collecting images for phenotyping have been developed, and powerful and flexible tools for analysisof these images for phenotype data exist, such as PlantCV. The biggest challenge to this segmentationprocess, however, lies in persistent variation between images in a data set. A method for standardizing thecolor spaces of images was developed and shown to reduce variation in images for easier and more accuratesegmentation. This tool is also implemented in PlantCV as a new module, and a new and robust pipeline isdeveloped for segmenting and extracting data from images in a large image set of sorghum collected in theBellwether Phenotyping Facility at the Donald Danforth Plant Science Center.

Color Space Standardization and Image Analysis for High-throughput Phenotyping of Sorghum bicolor

https://ir.library.illinoisstate.edu/cgi/viewcontent.cgi?article=1294&amp;context=beer

Color Space Standardization and Image Analysis for High-throughput Phenotyping of Sorghum bicolor

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