Abstract
Analysis of time series of images can quantify plant growth and development, including the effects of genetic mutations (phenotypes) that give information about gene function. Here is demonstrated a software application named HYPOTrace that automatically extracts growth and shape information from electronic gray-scale images of Arabidopsis (Arabidopsis thaliana) seedlings. Key to the method is the iterative application of adaptive local principal components analysis to extract a set of ordered midline points (medial axis) from images of the seedling hypocotyl. Pixel intensity is weighted to avoid the medial axis being diverted by the cotyledons in areas where the two come in contact. An intensity feature useful for terminating the midline at the hypocotyl apex was isolated in each image by subtracting the baseline with a robust local regression algorithm. Applying the algorithm to time series of images of Arabidopsis seedlings responding to light resulted in automatic quantification of hypocotyl growth rate, apical hook opening, and phototropic bending with high spatiotemporal resolution. These functions are demonstrated here on wild-type, cryptochrome1, and phototropin1 seedlings for the purpose of showing that HYPOTrace generated expected results and to show how much richer the machine-vision description is compared to methods more typical in plant biology. HYPOTrace is expected to benefit seedling development research, particularly in the photomorphogenesis field, by replacing many tedious, error-prone manual measurements with a precise, largely automated computational tool.
Highlights
Analysis of time series of images can quantify plant growth and development, including the effects of genetic mutations that give information about gene function
The seedling hypocotyl has been the subject of much important plant biology research because its growth and development are profoundly modified by many environmental and endogenous factors
Another major challenge posed by typical images of Arabidopsis (Arabidopsis thaliana) seedlings is locating the apical end of the hypocotyl to terminate the midline at the anatomically correct spot
Summary
HYPOTrace: Image Analysis Software for Measuring Hypocotyl Growth and Shape Demonstrated on Arabidopsis Seedlings Undergoing Photomorphogenesis1[OA]. Applying the algorithm to time series of images of Arabidopsis seedlings responding to light resulted in automatic quantification of hypocotyl growth rate, apical hook opening, and phototropic bending with high spatiotemporal resolution. These functions are demonstrated here on wild-type, cryptochrome, and phototropin seedlings for the purpose of showing that HYPOTrace generated expected results and to show how much richer the machine-vision description is compared to methods more typical in plant biology. The midline-based method of Miller et al (2007), while capable of high-resolution quantification of hypocotyl growth rate and apical hook opening in response to light, required manual image editing to separate the cotyledons from the hypocotyl in cases where they were appressed. The program called HYPOTrace is described and shown to measure light-induced hypocotyl inhibition, apical hook opening, phototropism, and nutation with a high degree of automation and resolution
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