室内植物表型平台及性状鉴定研究进展和展望

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perceptivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorised according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future

4,4′-Dibromo-7,7′-dimeth­oxy-1,1′-spiro­biindane

In the title compound, C19H18Br2O2, the dihedral angle between the two benzene rings of the spiro­biindane molecule is 70.44 (8)°. In the crystal, mol­ecules are inter­connected along the c axis by C—H⋯O hydrogen bonds and π–π stacking [centroid–centroid distance = 3.893 (2) Å] inter­actions, forming an infinite chain structure. The chains are further inter­connected through another set of C—H⋯O hydrogen bonds, forming layers approximately parallel to the bc plane

基于Scopus的植物表型组学研究进展分析

Bibliometric analyses are capable of demonstrating the history and the tendency of scientific and technological development. This article aims to use big scientific data to explore the present status of plant phenomics, based on which sound recommendations could be provided for the development of this emerging research domain. [Methods] Based on academic outputs such as research publications, citations, collaborations, research areas, academic organizations, and authors retrieved from the Scopus database between 2013 and September 2018, statistical analysis tools such as SciVal and CiteSpace 5.0 were applied to quantitatively visualize the development and tendency of plant phenotyping, plant phenomics, and related research areas. [Results] This Scopus-based research has retrieved 20 953 articles that are related to plant phenotyping, plant phenomics, and related applications in plant research, with a total citation of 217 105 and 2.0% of them are TOP1% highly cited papers. According to total citations, the TOP10 countries are the United States, China, Germany, the United Kingdom, France, Japan, Australia, Spain, Canada, and the Netherlands. The TOP10 research organizations based on total citations are Chinese Academy of Sciences (CAS), Institut National de la Recherche Agronomique (INRA), the US Department of Agriculture, Centre National de la Recherche Scientifique (CNRS), Chinese Academy of Agricultural Sciences, Cornell University, Spanish National Research Council, University of California at Davis, Universite Paris-Sacly, and Wageningen University & Research. The scholar with the most academic outputs is Alisdair Robert Fernie at the Koch Planck Institute of Molecular Plant Physiology, Germany. He has published 58 papers using plant cellular phenotypes and was cited 1 246 times. At present, plant phenomics research has focused on a number of plant species, including Arabidopsis, rice, wheat, corn, tomato and soybean. [Conclusion] As an emerging research domain, plant phenomics requires interdisciplinary efforts to integrate agriculture, cultivation, breeding, and other plant biological research with computing sciences. In particular, high-throughput image analysis and related data analysis has become an important research theme at the present stage, with the topical saliency index reaches 98.8%, a very high relevance score

Plant–plant interactions vary greatly along a flooding gradient in a dam-induced riparian habitat

Plant–plant interactions under extreme environmental stress are still controversial. The stress gradient hypothesis (SGH) proposes that facilitation prevails under extreme environmental stresses, while an alternative view states that facilitation collapses or even switches back to competition at the extreme end of stress gradients. However, how the relationship between plant–plant interaction and periodic extreme flooding stress varies and its underlying mechanism are still unclear in a dam-regulated riparian ecosystem. We established a controlled experiment using two dominant species pairs (Cynodon dactylon–Cyperus rotundus and C. dactylon–Xanthium sibiricum) in the water level fluctuating zone of the Three Gorges Dam to examine their growth responses to the periodic extreme flooding stress. The results showed that as flooding stress increased, the competitive effect of C. dactylon on X. sibiricum shifted to facilitation, whereas the effect of X. sibiricum on C. dactylon maintained a strong inhibition. The plant height of X. sibiricum was the most important driver of the interaction between X. sibiricum and C. dactylon along the flooding gradient. The net effect of C. dactylon on C. rotundus shifted from neutral to negative, and the inhibitory effect of C. rotundus on C. dactylon became stronger at the extreme end of flooding stress. The root biomass of the two species was the key trait regulating their interaction with increasing flooding stress. Overall, the SGH was partially supported along our periodic extreme flooding stress gradient. Aboveground resource (light) might be the dominant factor driving the response of the interaction between annual plants and perennial clonal plants to periodic flooding stress, whereas belowground resource (water and nutrients) was probably the dominant factor for perennial clonal plants. Our study will help to further understand the environmental responses of plant–plant relationships and their regulatory mechanism, and the succession of riparian plant communities under extreme environmental changes, providing a basic theoretical basis and data support for the ecological restoration and management of riparian wetland vegetation

Simulation of future global warming scenarios in rice paddies with an open-field warming facility

To simulate expected future global warming, hexagonal arrays of infrared heaters have previously been used to warm open-field canopies of upland crops such as wheat. Through the use of concrete-anchored posts, improved software, overhead wires, extensive grounding, and monitoring with a thermal camera, the technology was safely and reliably extended to paddy rice fields. The system maintained canopy temperature increases within 0.5°C of daytime and nighttime set-point differences of 1.3 and 2.7°C 67% of the time

Human Urinary Epithelial Cells as a Source of Engraftable Hepatocyte-Like Cells Using Stem Cell Technology

K