In situ root system architecture extraction from magnetic resonance imaging for water uptake modeling

An automated method for root system architecture reconstruction from three-dimensional volume data sets obtained from magnetic resonance imaging (MRI) was developed and validated with a three-dimensional semimanual reconstruction using virtual reality and a two-dimensional reconstruction using SmartRoot. It was tested on the basis of an MRI image of a 25-d-old lupin (Lupinus albus L.) grown in natural sand with a resolution of 0.39 by 0.39 by 1.1 mm. The automated reconstruction algorithm was inspired by methods for blood vessel detection in MRI images. It describes the root system by a hierarchical network of nodes, which are connected by segments of defined length and thickness, and also allows the calculation of root parameter profiles such as root length, surface, and apex density The obtained root system architecture (RSA) varied in number of branches, segments, and connectivity of the segments but did not vary in the average diameter of the segments (0.137 cm for semimanual and 0.143 cm for automatic RSA), total root surface (127 cm2 for semimanual and 124 cm² for automatic RSA), total root length (293 cm for semimanual and 282 cm for automatic RSA), and total root volume (4.7 cm³ for semimanual and 4.7 cm³ for automatic RSA). The difference in performance of the automated and semimanual reconstructions was checked by using the root system as input for water uptake modeling with the Doussan model. Both systems worked well and allowed for continuous water flow. Slight differences in the connectivity appeared to be leading to locally different water flow velocities, which were 30% smaller for the semimanual method,