X-ray computed tomography for 3D plant imaging.

X-ray computed tomography (CT) is a valuable tool for 3D imaging of plant tissues and organs. Applications include the study of plant development and organ morphogenesis, as well as modeling of transport processes in plants. Some challenges remain, however, including attaining higher contrast for easier quantification, increasing the resolution for imaging subcellular features, and decreasing image acquisition and processing time for high-throughput phenotyping. In addition, phase contrast, multispectral, dark-field, soft X-ray, and time-resolved imaging are emerging. At the same time, a large amount of 3D image data are becoming available, posing challenges for data management. We review recent advances in the area of X-ray CT for plant imaging, and describe opportunities for using such images for studying transport processes in plants.

Correction: 4D synchrotron microtomography and pore-network modelling for direct in situ capillary flow visualization in 3D printed microfluidic channels.

Correction for '4D synchrotron microtomography and pore-network modelling for direct in situ capillary flow visualization in 3D printed microfluidic channels' by Agnese Piovesan et al., Lab Chip, 2020, 20, 2403-2411, DOI: .

4D synchrotron microtomography and pore-network modelling for direct in situ capillary flow visualization in 3D printed microfluidic channels.

Powder-based 3D printing was employed to produce porous, capillarity-based devices suitable for passive microfluidics. Capillary imbibition in such devices was visualized in situ through dynamic synchrotron X-ray microtomography performed at the European Synchrotron Radiation Facility (ESRF) with sub-second time resolution. The obtained reconstructed images were segmented to observe imbibition dynamics, as well as to compute the system effective contact angle and to generate a pore-network to model capillary imbibition. A contact angle gradient was observed resulting in a preferential wicking direction, with the central portion of the microfluidic channel filling faster than the edge areas. The contact angle analysis and the pore-network model results suggest that this is due to spatial variations in the material surface properties arising from both the 3D printing and the subsequent drying processes.