247,198 research outputs found

    室内植物表型平台及性状鉴定研究进展和展望

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    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

    莱茵衣藻生长和光合作用对硝基苯的响应

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    初步研究了不同浓度硝基苯对莱茵衣藻(Chlamydomonas reinhardtii)生长和光合作用的影响.结果表明:不同浓度的硝基苯对莱茵衣藻的生长和光合生理有明显抑制作用,主要表现在其明显降低光合色素的含量、光能转换效率(Fv/Fm)、电子传递速率(ETR)、净光合速率(Pn)等方面;硝基苯对莱茵衣藻的影响主要是通过影响光合色素合成,降低光合作用电子传递,从而降低藻类的光合作用,引起生长的抑制

    近年来光合作用领域的前沿和热点研究——基于WOS高被引论文的科技术语分析

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    科技术语是科技论文的基本要素和重要特征,光合作用研究论文中存在大量的科技术语。基于数据驱动的科技术语分析能够对学科领域的动态发展和演变起到较好的揭示和印证作用。文章以VOSviewer软件为主要分析工具,对Web of Science数据库中光合作用领域近三年的高被引论文和热点论文中的科技术语进行计量分析和可视化呈现。分析比较的结果表明,近年来光合作用的研究热点集中在&quot;自然光合作用的机理探究&quot;&quot;光合作用与环境变化&quot;&quot;人工光合的应用和发展&quot;三个方向,&quot;光催化剂&quot;成为这几年光合作用领域研究的前沿。&nbsp; 引用:[1]蒋甜,许哲平,陈学娟,卢庆陶,杨辉霞,朱学军.近年来光合作用领域的前沿和热点研究&mdash;&mdash;基于WOS高被引论文的科技术语分析[J].中国科技术语,2021,23(01):60-70.</p

    一种Ag纳米粒子嵌入的复合材料制备与光催化性能研究

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    将Zn O纳米线阵列作为模板,采用射频和直流磁控溅射法,结合快速退火工艺制备了Zn O/Ti O2/Ag/Zn Se复合光催化材料。利用扫描电子显微镜、X射线衍射仪、透射电镜、紫外可见吸收光度计、拉曼谱仪等仪器分别考察了复合纳米线的形貌、结构、光学性质和催化性能。研究结果表明,在Zn Se半导体敏化和Ag纳米粒子诱导表面等离激元的共振作用下,复合材料在紫外光和可见光方面表现出了良好的光吸收性能和光催化性能
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