BackgroundFusarium head blight (FHB), a scab principally caused by Fusarium graminearum Schw., is a serious disease of wheat. The purpose of this study is to evaluate the potential of combining synchrotron based phase contrast X-ray imaging (PCI) with Fourier Transform mid infrared (FTIR) spectroscopy to understand the mechanisms of resistance to FHB by resistant wheat cultivars. Our hypothesis is that structural and biochemical differences between resistant and susceptible cultivars play a significant role in developing resistance to FHB.ResultsSynchrotron based PCI images and FTIR absorption spectra (4000–800 cm−1) of the floret and rachis from Fusarium-damaged and undamaged spikes of the resistant cultivar ‘Sumai3’, tolerant cultivar ‘FL62R1’, and susceptible cultivar ‘Muchmore’ were collected and analyzed. The PCI images show significant differences between infected and non-infected florets and rachises of different wheat cultivars. However, no pronounced difference between non-inoculated resistant and susceptible cultivar in terms of floret structures could be determined due to the complexity of the internal structures. The FTIR spectra showed significant variability between infected and non-infected floret and rachis of the wheat cultivars. The changes in absorption wavenumbers following pathogenic infection were mostly in the spectral range from 1800–800 cm−1. The Principal Component Analysis (PCA) was also used to determine the significant chemical changes inside floret and rachis when exposed to the FHB disease stress to understand the plant response mechanism. In the floret and rachis samples, PCA of FTIR spectra revealed differences in cell wall related polysaccharides. In the florets, absorption peaks for Amide I, cellulose, hemicellulose and pectin were affected by the pathogenic fungus. In the rachis of the wheat cultivars, PCA underlines significant changes in pectin, cellulose, and hemicellulose characteristic absorption spectra. Amide II and lignin absorption peaks, persistent in the rachis of Sumai3, together with increased peak shift at 1245 cm−1 after infection with FHB may be a marker for stress response in which the cell wall compounds related to pathways for lignification are increased.ConclusionsSynchrotron based PCI combined with FTIR spectroscopy show promising results related to FHB in wheat. The combined technique is a powerful new tool for internal visualisation and biomolecular monitoring before and during plant-microbe interactions to understand both the differences between cultivars and their different responses to disease stress.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-014-0357-5) contains supplementary material, which is available to authorized users.

Minimally invasive investigation of plant parts (root, stem, leaves, and flower) has good potential to elucidate the dynamics of plant growth, morphology, physiology, and root-rhizosphere interactions. Laboratory based absorption X-ray imaging and computed tomography (CT) systems are extensively used for in situ feasibility studies of plants grown in natural and artificial soil. These techniques have challenges such as low contrast between soil pore space and roots, long X-ray imaging time, and low spatial resolution. In this study, the use of synchrotron (SR) based phase contrast X-ray imaging (PCI) has been demonstrated as a minimally invasive technique for imaging plants. Above ground plant parts and roots of 10 day old canola and wheat seedlings grown in sandy clay loam soil were successfully scanned and reconstructed. Results confirmed that SR-PCI can deliver good quality images to study dynamic and real time processes such as cavitation and water-refilling in plants. The advantages of SR-PCI, effect of X-ray energy, and effective pixel size to study plant samples have been demonstrated. The use of contrast agents to monitor physiological processes in plants was also investigated and discussed.

Quantum control for error correction is critical for the practical use of quantum computers. We address quantum optimal control for single-shot multi-qubit gates by framing it as a feasibility problem for the Hamiltonian model that is then solved with standard global optimization software. Our approach yields faster high-fidelity (>99.99%) single-shot three-qubit-gate control than obtained previously, and it has also enabled us to solve the quantum-control problem for a fast high-fidelity four-qubit gate.

Fluids confined to quasi-one-dimensional channels exhibit a dynamic crossover from single file diffusion to normal diffusion as the channel becomes wide enough for particles to hop past each other. In the crossover regime, where hopping events are rare, the diffusion coefficient in the long time limit can be related to a hopping time that measures the average time it takes a particle to escape the local cage formed by its neighbours. In this work, we show that a transition state theory that calculates the free energy barrier for two particles attempting to pass each other in the small system isobaric ensemble is able to quantitatively predict the hopping time in a system of two-dimensional soft repulsive discs [U (r ij ) = (σ/r ij ) α ] confined to a hard walled channel over a range of channel radii and degrees of particle softness measured in terms of 1/α. The free energy barrier exhibits a maximum at intermediate values of α that moves to smaller values of 1/α (harder particles) as the channel becomes narrower. However, the presence of the maximum is only observed in the hopping times for wide channels because the interaction potential dependence of the kinetic prefactor plays an increasingly important role for narrower channels. We also begin to explore how our transition state theory approach can be used to optimize and control dynamics in confined quasi-one-dimensional fluids.arXiv:1904.09304v1 [cond-mat.soft]

The Super Dual Auroral Radar Network (SuperDARN) is an international network of high frequency coherent scatter radars that are used for monitoring the electrodynamics of the Earth’s upper atmosphere at middle, high, and polar latitudes in both hemispheres. pyDARN is an open-source Python-based library developed specifically for visualizing SuperDARN radar data products. It provides various plotting functions of different types of SuperDARN data, including time series plot, range-time parameter plot, fields of view, full scan, and global convection map plots. In this paper, we review the different types of SuperDARN data products, pyDARN’s development history and goals, the current implementation of pyDARN, and various plotting and analysis functionalities. We also discuss applications of pyDARN, how it can be combined with other existing Python software for scientific analysis, challenges for pyDARN development and future plans. Examples showing how to read, visualize, and interpret different SuperDARN data products using pyDARN are provided as a Jupyter notebook.