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Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perspectivity 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 categorized 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.

To investigate the deformation and failure behavior of a tunnel excavated in mixed strata, transparent soft rock test and numerical simulations were performed. The distribution features of displacement and failure and the evolution laws were analyzed. In this study, a transparent material for simulating mixed strata was developed. The visualization of the spatial deformation inside rock masses will improve the understanding of this process. The tests suggest that the mechanical properties of transparent soft rock are similar to those of natural rock. Experiments on the isotropic and mixed strata conditions were carried out to study the deformation rules during tunnel boring machine (TBM) excavation. The test results show that the dominant deformation position and direction exist in isotropic and mixed strata. A shear slip band occurs in both mixed and isotropic strata but with different distributions. Finally, numerical simulations were conducted to study the failure process, and the damage pattern of the transparent soft rock experiment was similar to that of the numerical simulation. The interface of the softness and hardness layers controls the extension of rock damage.

A series of modified polysaccharide microparticles have been fabricated and their potential application for scavenging reactive oxygen species (ROS) and their derivatives to achieve osteoarthritis (OA) treatment has been explored. These microparticles were cross-linked dextran (Sephadex) with different carbazate substitution ratios determined by the TNBS assay and elemental analysis. It has been demonstrated that they could effectively scavenge carbonylated proteins and ROS including hydroxyl radicals (˙OH), superoxide anions (˙O2-) and H2O2 and their derivatives with high efficiency, improve the viability of H2O2-treated chondrocytes by reducing their ROS levels, as well as lower their inflammatory factors. The above ability of antioxidation and inflammation resistance improved with the increase of carbazate substitution ratio. Significantly, this work provided the proof that modified Sephadex successfully alleviated the deterioration of cartilage and the progression of OA in vivo. The proposed microparticles showed a very promising capability for reducing ROS levels and further treating OA.

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.

To select elite germplasms, 112 mutants derived from japonica rice cultivar Wuyujing 3 were evaluated. The yield components such as panicle number per square meter, grain number per panicle, and grain weight were measured. The quality traits such as percentage of chalky grains (PCG), brown rice yield (BRY), milled rice yield (MRY), degree of milling (DM), amylose content (AC), protein content (PC), and relationships among traits were inverstigated. Results showed that grain yield ranged from 2.15 to 12.49 t/hm2 with a mean of 6.4 t/hm2 and number of grains per square meter contributed for 94.64% in grain yield variation. For quality traits, all rice mutants had short size (grain length ≤ 5.5 mm) and bold shape (grain length to width ratio = 1.10–2.00). Most of rice mutants (87.5%) had PCG values below 20%. All mutants had MRY values above 50%, AC values below 20%, and PC values below 10%. Percentage of chalky grains was significantly negatively correlated with MRY and positively correlated with DM. BRY and MRY were significantly negatively correlated with DM. PC was significantly and positively correlated with MRY and negatively correlated with DM, while AC had no significant correlation with these quality traits. It was concluded that there were 25 rice mutants which fulfilled the major requirements of Jiangsu standard japonica rice such as low percentage of chalky grains, low amylose content, optimal protein content, and which could be used as elite germplasms. Thus the mutants identified may lead to significant progress in improvement of rice quality.

With the development of remote sensing, robotics, computer vision and artificial intelligence, plant phenomics research has been developing rapidly in recent years. Here, we first introduced a concise history of this research domain, including the theoretical foundation, research methods, biological applications, and the latest progress. Then, we introduced some important indoor and outdoor phenotyping approaches such as handheld devices, ground-based manual and automated vehicles, robotic systems, Internet of Things(IoT)based distributed platforms, automatic deep phenotyping systems, and large-scale aerial phenotyping, together with their advantages and disadvantages during the applications. In order to extract meaningful information from big image-and sensor-based datasets generated by the phenotyping process, we also specified key phenotypic analysis methods and related development procedures. Finally, we discussed the future perspective of plant phenomics, with recommendations of how to apply this research field to breeding, cultivation and agricultural practices in China.

The paper proposes a coupling probe which can effectively expand the coupling adjustment range, and optimally designs a 64-element array antenna’s rectangular radial line feed network at the center frequency of 2.1 GHz. Simulation results show that the feed network whose caliber is 744 mm×744 mm can achieve approximately 64-road equiamplitude feed. The reflection coefficient is less than 0.1 at the center frequency, and less than 0.2 in the frequency band ranging from 2.06 GHz to 2.15 GHz.