Background: Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. In addition, performing nondestructive high-throughput phenotyping to extract the structural and morphological features of roots remains challenging. Results: We developed the MultipleXLab: a modular, mobile, and cost-effective setup to tackle these limitations. The system can continuously monitor thousands of seeds from germination to root development based on a conventional camera attached to a motorized multiaxis-rotational stage and custom-built 3D-printed plate holder with integrated light-emitting diode lighting. We also developed an image segmentation model based on deep learning that allows the users to analyze the data automatically. We tested the MultipleXLab to monitor seed germination and root growth of Arabidopsis developmental, cell cycle, and auxin transport mutants non-invasively at high-throughput and showed that the system provides robust data and allows precise evaluation of germination index and hourly growth rate between mutants. Conclusion: MultipleXLab provides a flexible and user-friendly root phenotyping platform that is an attractive mobile alternative to high-end imaging platforms and stationary growth chambers. It can be used in numerous applications by plant biologists, the seed industry, crop scientists, and breeding companies.
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Plants are sessile organisms that deal with their -sometimes adverse- environment in well-regulated ways. Chromatin remodeling involving SWI/SNF2-type ATPases is thought to be an important epigenetic mechanism for the regulation of gene expression in different developmental programs and for integrating these programs with the response to environmental signals. In this study, we report on the role of chromatin remodeling in Arabidopsis with respect to the variability of growth and gene expression in relationship to environmental conditions.
Particle image velocimetry has been widely used in various sectors from the automotive to aviation, research, and development, energy, medical, turbines, reactors, electronics, education, refrigeration for flow characterization and investigation. In this study, articles examined in open literature containing the particle image velocimetry techniques are reviewed in terms of components, lasers, cameras, lenses, tracers, computers, synchronizers, and seeders. The results of the evaluation are categorized and explained within the tables and figures. It is anticipated that this paper will be a starting point for researchers willing to study in this area and industrial companies willing to include PIV experimenting in their portfolios. In addition, the study shows in detail the advantages and disadvantages of past and current technologies, which technologies in existing PIV laboratories can be renewed, and which components are used in the PIV laboratories to be installed.
