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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. [ABSTRACT FROM AUTHOR]

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: 10.1039/D0LC00227E. [ABSTRACT FROM AUTHOR]

To preserve the quality of fresh pear fruit after harvest and deliver quality fruit year-round a controlled supply chain and long-term storage are applied. During storage, however, internal disorders can develop due to suboptimal storage conditions that may not cause externally visible symptoms. This makes them impossible to be detected by current commercial quality grading systems in a reliable and non-destructive way. A combination of a Support Vector Machine coupled with a feature extraction algorithm and X-ray Computed Tomography is proposed to successfully detect internal disorders in 'Conference' and 'Cepuna' pear fruit nondestructively. Classifiers were able to distinguish defective from sound fruit with classification accuracies ranging between 90.2 and 95.1% depending on the cultivar and number of used features. Moreover, low false positive and negative rates were obtained, respectively ranging between 0.0 and 6.7%, and 5.7 and 13.3%. Classifiers trained on 'Conference' data were transferred effectively to the 'Cepuna' cultivar, suggesting generalizability to other cultivars as well. With continuing developments in both hardware and software to increase inspection speed and reduce equipment costs, the method can be implemented in industrial applications, e.g., inline translational X-ray CT. • Healthy and defect Conference and Cepuna pears resulted from storage experiments. • Fast X-ray CT scans were obtained of all fruit and relevant features were extracted. • SVMs achieved high accuracy in detecting defect fruit regardless of the cultivar. • Feature selection could limit the used features to two without a drop in performance. • Method can be implemented for postharvest fruit sorting using fast X-ray CT. [ABSTRACT FROM AUTHOR]

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. High-resolution X-ray computed tomography (CT) instruments are increasingly becoming available to plant research laboratories for structural phenotyping experiments at the macro-, micro-, and nanoscales. New developments in contrast agents, phase contrast, and soft X-ray imaging improve image contrast and allow the visualization of previously unresolved structural features Time-resolved X-ray CT techniques are emerging and permit dynamic imaging in real time owing to improvements in acquisition and image reconstruction. Automatic image-processing algorithms based on machine and deep learning are starting to appear and replace conventional image processing based on often cumbersome and manually operated segmentation procedures. X-ray CT-based mathematical models are being developed to compute the effect of plant tissue structure on relevant physiological processes such as respiration and photosynthesis. [ABSTRACT FROM AUTHOR]

During respiratory quotient based dynamic controlled atmosphere (RQ-DCA) storage, the oxygen concentration in the room is reduced until the RQ measured in the air of the room (R Q a i r ) increases above a predefined threshold. This increase in RQ indicates an increased extent of fermentation within the fruit. Because of internal gas gradients, the oxygen concentration inside the fruit is lower than that of the storage atmosphere and, hence, the RQ value in the fruit (R Q f r u i t , m a x ) is larger than R Q a i r . Moreover, due to biological variability and fluctuations in the storage conditions, both R Q f r u i t , m a x and R Q a i r vary. Currently, no information exists about how the RQ measured in the atmosphere correlates with the RQ value inside the fruit, and how representative this R Q a i r is for all fruit inside the room. In this article, we investigated how variability affects the critical R Q a i r threshold in RQ-DCA. Hereto we used a multiscale stochastic reaction-diffusion model to compute gas transport within pears of three different cultivars, 'Cepuna', 'Conference' and 'Queen's Forelle'. Biological variability in diffusion and respiration parameters and fluctuations in cool room conditions were taken into account by performing Monte-Carlo simulations. The results showed large variations in both R Q f r u i t , m a x and R Q a i r . The effect of cool room filling degree on both RQ values was negligible, while variations in fruit material properties (pear size, tissue gas diffusivity and respiration kinetics) showed to be of high importance. However, as R Q a i r increased before fermentation started to dominate, the underestimation and variability of R Q a i r did not inhibit a proper detection of hypoxia inside the fruit within the room. This finding indicates that R Q a i r is a proper parameter to control DCA storage of various cultivars. Due to differences in fruit properties, the RQ-response varied between the cultivars. 'Cepuna' requires the highest O 2 (0.61 kPa) to prevent fermentation, while 'Conference' and 'Queen's Forelle' can be stored at lower O 2 (0.33 and 0.22 kPa, respectively). The results obtained in this research can be used to optimize RQ-DCA storage of each cultivar. • Gas exchange properties of pear vary with cultivar. • Stochastic simulations quantified the variability in RQ during RQ-DCA storage. • Large variations in RQ were predicted during RQ-DCA storage. • Room RQ measurements allowed to properly detect fruit fermentation. [ABSTRACT FROM AUTHOR]