Virus-induced gene complementation reveals a transcription factor network in modulation of tomato fruit ripening

Plant virus technology, in particular virus-induced gene silencing, is a widely used reverse- and forward-genetics tool in plant functional genomics. However the potential of virus technology to express genes to induce phenotypes or to complement mutants in order to understand the function of plant genes is not well documented. Here we exploit Potato virus X as a tool for virus-induced gene complementation (VIGC). Using VIGC in tomato, we demonstrated that ectopic viral expression of LeMADS-RIN, which encodes a MADS-box transcription factor (TF), resulted in functional complementation of the non-ripening rin mutant phenotype and caused fruits to ripen. Comparative gene expression analysis indicated that LeMADS-RIN up-regulated expression of the SBP-box (SQUAMOSA promoter binding protein-like) gene LeSPL-CNR, but down-regulated the expression of LeHB-1, an HD-Zip homeobox TF gene. Our data support the hypothesis that a transcriptional network may exist among key TFs in the modulation of fruit ripening in tomato

Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images

Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information-based change detection methods have been proposed in past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. All the bi-temporal images are scanned pixel by pixel so the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by three land cover change cases with Landsat bi-temporal remote sensing images and aerial images with very high spatial resolution (0.5 m/pixel). In comparison to several widely used change detection methods, the proposed approach can produce a land cover change inventory map with a competitive accuracyThis work was supported by the National Science Foundation China (61701396), the Natural Science Foundation of Shaan Xi Province (2017JQ4006), Engineering Research Center of Geospatial Information and Digital Technology, NASG (SIDT20171003), The National Key Research and Development Program of China(018YFF0215006), Natural Science Foundation of Jiangsu Province, China (BK20150835), and Tibet Natural Science Foundation-The study of Tibet crop condition monitoring based on crop growth model and multi-source remote sensing data (2016-ZR-15-18).Peer Reviewe

Post-Processing Approach for Refining Raw Land Cover Change Detection of Very High-Resolution Remote Sensing Images

In recent decades, land cover change detection (LCCD) using very high-spatial resolution (VHR) remote sensing images has been a major research topic. However, VHR remote sensing images usually lead to a large amount of noises in spectra, thereby reducing the reliability of the detected results. To solve this problem, this study proposes an object-based expectation maximization (OBEM) post-processing approach for enhancing raw LCCD results. OBEM defines a refinement of the labeling in a detected map to enhance its raw detection accuracies. Current mainstream change detection (preprocessing) techniques concentrate on proposing a change magnitude measurement or considering image spatial features to obtain a change detection map. The proposed OBEM approach is a new solution to enhance change detection accuracy by refining the raw result. Post-processing approaches can achieve competitive accuracies to the preprocessing methods, but in a direct and succinct manner. The proposed OBEM post-processing method synthetically considers multi-scale segmentation and expectation maximum algorithms to refine the raw change detection result. Then, the influence of the scale of segmentation on the LCCD accuracy of the proposed OBEM is investigated. Four pairs of remote sensing images, one of two pairs (aerial image with 0.5 m/pixel resolution) which depict two landslide sites on Landtau Island, Hong Kong, China, are used in the experiments to evaluate the effectiveness of the proposed approach. In addition, the proposed approach is applied, and validated by two case studies, LCCD in Tianjin City China (SPOT-5 satellite image with 2.5 m/pixel resolution) and Mexico forest fire case (Landsat TM images with 30 m/pixel resolution), respectively. Quantitative evaluations show that the proposed OBEM post-processing approach can achieve better performance and higher accuracies than several commonly used preprocessing methods. To the best of the authors’ knowledge, this type of post-processing framework is first proposed here for the field of LCCD using VHR remote sensing images.This work was supported by the National Science Foundation China (61701396 and D010701), the Science Foundation of Hunan Province (Grant No. 2016JJ6100), the Natural Science Foundation of Shaan Xi Province (2017JQ4006), and the project from the China Postdoctoral Science Foundation (2015M572658XB).Peer Reviewe

Observation of Metallic Surface States in the Strongly Correlated Kitaev-Heisenberg Candidate Na\u3csub\u3e2\u3c/sub\u3eIrO\u3csub\u3e3\u3c/sub\u3e

We report high-resolution angle-resolved photoemission spectroscopy measurements on the honeycomb iridate Na2IrO3. Our measurements reveal the existence of a metallic surface band feature crossing the Fermi level with nearly linear dispersion and an estimated surface carrier density of 3.2 x 1013 cm-2, which has not been theoretically predicted or experimentally observed, and provides the first evidence for metallic behavior on the boundary of this material, whereas the bulk bands exhibit a robust insulating gap. We further show the lack of theoretically predicted Dirac cones at the M¯ points of the surface Brillouin zone, which confirms the absence of a stacked quantum spin Hall phase in this material. Our data indicates that the surface ground state of this material is exotic and metallic, unlike as predicted in theory, and establishes Na2IrO3 as a rare example of a strongly correlated spin-orbit insulator with surface metallicity

Changes in physiology and quality of Laiyang pear in long time storage

Physiological disorders easily occur in Laiyang pear (Pyrus bretschneideri cv. Laiyang) fruit after harvest and result in quality deterioration and short postharvest life. In this paper, we mainly investigated the effects of 1-methylcyclopropene (1-MCP) treatment and controlled atmosphere (CA) with 2% O-2 plus 2% CO2 on quality of Laiyang pear and storage time. The results indicated that 1-MCP treatment and CA were effective in maintaining quality and prolonging storage time of Laiyang pear fruit, because 1-MCP and CA could significantly delay fruit senescence via limiting ethylene production, reducing fruit respiration rate, regulating anti-oxidant enzymes and membrane permeability. We consider that the major action modes of 1-MCP and CA, that can maintain harvested quality of Laiyang pear fruit, may be greatly contributed to inhibiting ethylene biosynthesis and regulating anti-oxidant pathways. (C) 2012 Elsevier B.V. All rights reserved

Inner and outer particles searching method with its applying in SPH method

A two-dimensional hydrodynamic model is developed, on the basis of numerical approximation formulations of Smoothed Particle Hydrodynamics (SPH) to NS equation. In the model, Dirichlet conditions are applied to free surfaces, solid boundaries are modeled with fixed wall particles, no-slip boundary conditions are employed to mirror particles, and pressure can get through solving state equation. A new Nearest Neighboring Particles Searching (NNPS) technique is developed, which can improve the computation efficiency remarkably compared with the traditional DSM method and the Mihai s method. The case of the dam breaking is used to verify the present model