Journal
PLANT METHODS
Volume 14, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s13007-018-0316-5
Keywords
Root growth; Root architecture; Automatic imaging; Image processing; Root phenotyping; High throughput
Categories
Funding
- '948' Program [2011-G19]
- China Postdoctoral Science Foundation [2015M571167, 2017M620960]
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Background: In order to efficiently determine genotypic differences in rooting patterns of crops, novel hardware and software are needed simultaneously to characterize dynamics of root development. Results: We describe a prototype robotic monitoring platform-the RhizoChamber-Monitor for analyzing growth patterns of plant roots automatically. The RhizoChamber-Monitor comprises an automatic imaging system for acquiring sequential images of roots which grow on a cloth substrate in custom rhizoboxes, an automatic irrigation system and a flexible shading arrangement. A customized image processing software was developed to analyze the spatiotemporal dynamics of root growth from time-course images of multiple plants. This software can quantify overall growth of roots and extract detailed growth traits (e.g. dynamics of length and diameter) of primary roots and of individual lateral roots automatically. It can also identify local growth traits of lateral roots (pseudo-mean-length and pseudo-maximum-length) semi-automatically. Two cotton genotypes were used to test both the physical platform and the analysis software. Conclusions: The combination of hardware and software is expected to facilitate quantification of root geometry and its spatio-temporal growth patterns, and therefore to provide opportunities for high-throughput root phenotyping in support of crop breeding to optimize root architecture.
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