Abstract
BackgroundRoot phenotyping aims to characterize root system architecture because of its functional role in resource acquisition. RGB imaging and analysis procedures measure root system traits via colour contrasts between roots and growth media or artificial backgrounds. In the case of plants grown in soil-filled rhizoboxes, where the colour contrast can be poor, it is hypothesized that root imaging based on spectral signatures improves segmentation and provides additional knowledge on physico-chemical root properties.ResultsRoot systems of Triticum durum grown in soil-filled rhizoboxes were scanned in a spectral range of 1000–1700 nm with 222 narrow bands and a spatial resolution of 0.1 mm. A data processing pipeline was developed for automatic root segmentation and analysis of spectral root signatures. Spectral- and RGB-based root segmentation did not significantly differ in accuracy even for a bright soil background. Best spectral segmentation was obtained from log-linearized and asymptotic least squares corrected images via fuzzy clustering and multilevel thresholding. Root axes revealed major spectral distinction between center and border regions. Root decay was captured by an exponential function of the difference spectra between water and structural carbon absorption regions.ConclusionsFundamentals for root phenotyping using hyperspectral imaging have been established by means of an image processing pipeline for automated segmentation of soil-grown plant roots at a high spatial resolution and for the exploration of spectral signatures encoding physico-chemical root zone properties.
Highlights
Root phenotyping aims to characterize root system architecture because of its functional role in resource acquisition
Using a representative image section of 320 × 3000 pixels near the plant base, file size was decreased to 9.4 GB for deriving an adequate image processing strategy, while reducing computational time sufficiently to test several possible combinations of processing steps on a standard PC
Hyperspectral imaging is a novel approach for root phenotyping of soil grown plants
Summary
Root phenotyping aims to characterize root system architecture because of its functional role in resource acquisition. RGB imaging and analysis procedures measure root system traits via colour contrasts between roots and growth media or artificial backgrounds. In the case of plants grown in soil-filled rhizoboxes, where the colour contrast can be poor, it is hypothesized that root imaging based on spectral signatures improves segmentation and provides additional knowledge on physico-chemical root properties. Better understanding of root and rhizosphere processes can essentially contribute to enhance resource efficiency in crop production and sustainable soil management [26, 38, 63, 68]. Advances in root system and rhizosphere management critically depend on appropriate measurement methods, making the plants’ “hidden half ” [5] accessible to visualization and quantification. Bodner et al Plant Methods (2018) 14:84 living, senescent and dead roots, leaf debris and soil. Pandey et al [51] showed that using an extended hyperspectral range from 550 to 1700 nm enables an accurate prediction of leaf water content and nutritional status
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