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| 1 | The rice OsV4 encoding a novel pentatricopeptide repeat protein is required for chloroplast development during the early leaf stage under cold stress显示文摘Pentatricopeptide repeat(PPR)proteins,characterized by tandem arrays of a 35 amino acid motif,have been suggested to play central and broad roles in modulating the expression of organelle genes in plants.However,the molecular mechanisms of most rice PPR genes remains unclear.In this paper,we isolated and characterized a temperature-conditional virescent mutant,OsV4,in rice(Oryza sativa cultivar Jiahua1(WT,japonica rice variety)).The mutant displays albino phenotype and abnormal chloroplasts at the three leaf stage,which gradually turns green after the four leaf stage at a low temperature(20°C).But the mutant always develops green leaves and well-developed chloroplasts at a high temperature(32°C).Genetic and molecular analyses uncovered that OsV4 encodes a novel chloroplast-targeted PPR protein including four PPR motifs.Further investigations show that the mutant phenotype is associated with changes in chlorophyll content and chloroplast development.The OsV4transcripts only accumulate to high levels in young leaves,indicating that its expression is tissue-specific.In addition,transcript levels of some ribosomal components and plastid-encoded polymerase-dependent genes are dramatically reduced in the albino mutants grown at 20°C.These findings suggest that OsV4 plays an important role during early chloroplast development under cold stress in rice. | Xiaodi Gong Qianqian Su Dongzhi Lin Quan Jiang Jianlong Xu Jianhui Zhang Sheng Teng Yanjun Dong | 2014 | Journal of Integrative Plant Biology2014，56，4： | 19 |
| 2 | The CAMS Climate System Model and a Basic Evaluation of Its Climatology and Climate Variability Simulation显示文摘A new coupled climate system model(CSM) has been developed at the Chinese Academy of Meteorological Sciences(CAMS) by employing several state-of-the-art component models. The coupled CAMS-CSM consists of the modified atmospheric model [ECmwf-HAMburg(ECHAM5)], ocean model [Modular Ocean Model(MOM4)], sea ice model [Sea Ice Simulator(SIS)], and land surface model [Common Land Model(CoLM)]. A detailed model description is presented and both the pre-industrial and 'historical' simulations are preliminarily evaluated in this study.The model can reproduce the climatological mean states and seasonal cycles of the major climate system quantities,including the sea surface temperature, precipitation, sea ice extent, and the equatorial thermocline. The major climate variability modes are also reasonably captured by the CAMS-CSM, such as the Madden–Julian Oscillation(MJO), El Ni?o–Southern Oscillation(ENSO), East Asian Summer Monsoon(EASM), and Pacific Decadal Oscillation(PDO).The model shows a promising ability to simulate the EASM variability and the ENSO–EASM relationship. Some biases still exist, such as the false double-intertropical convergence zone(ITCZ) in the annual mean precipitation field,the overestimated ENSO amplitude, and the weakened Bjerknes feedback associated with ENSO; and thus the CAMS-CSM needs further improvements. | Xinyao RONG Jian LI Haoming CHEN Yufei XIN Jingzhi SU Lijuan HUA Tianjun ZHOU Yanjun QI Zhengqiu ZHANG Guo ZHANG Jianduo LI | 2018 | Journal of Meteorological Research2018，32，6： | 15 |
| 3 | Application of deep learning in ecological resource research:Theories, methods, and challenges显示文摘Ecological resources are an important material foundation for the survival,development,and self-realization of human beings.In-depth and comprehensive research and understanding of ecological resources are beneficial for the sustainable development of human society.Advances in observation technology have improved the ability to acquire long-term,cross-scale,massive,heterogeneous,and multi-source data.Ecological resource research is entering a new era driven by big data.Traditional statistical learning and machine learning algorithms have problems with saturation in dealing with big data.Deep learning is a method for automatically extracting complex high-dimensional nonlinear features,which is increasingly used for scientific and industrial data processing because of its ability to avoid saturation with big data.To promote the application of deep learning in the field of ecological resource research,here,we first introduce the relationship between deep learning theory and research on ecological resources,common tools,and datasets.Second,applications of deep learning in classification and recognition,detection and localization,semantic segmentation,instance segmentation,and graph neural network in typical spatial discrete data are presented through three cases:species classification,crop breeding,and vegetation mapping.Finally,challenges and opportunities for the application of deep learning in ecological resource research in the era of big data are summarized by considering the characteristics of ecological resource data and the development status of deep learning.It is anticipated that the cooperation and training of cross-disciplinary talents may promote the standardization and sharing of ecological resource data,improve the universality and interpretability of algorithms,and enrich applications with the development of hardware. | Qinghua GUO Shichao JIN Min LI Qiuli YANG Kexin XU Yuanzhen JU Jing ZHANG Jing XUAN Jin LIU Yanjun SU Qiang XU Yu LIU | 2020 | Science China Earth Sciences2020，63，10： | 7 |
| 4 | The geo-pattern of course shifts of the Lower Yellow River显示文摘从传统的研究获得的更低的黄河(LYR ) 的变化模式,它主要基于与 LYR 有关的历史的文件做了字面的分析直觉太宏观、不在。这份报纸集成在与路线有关的历史的文件的记录最后 3000 年转移,泛滥并且溢出的所有并且在一个 GIS 数据库存储他们。然后,所有数据将在地图形式被设想,它是有用的显示出并且理解那些事件更直觉地并且精确地遵守的规则。作为基础拿这些数据,这学习总结 LYR 功课和影响范围的特征,并且两个都分类他们进三种类型;把 LYR 功课的流动方向划分成二个时期,并且建议它的变化模式;断定转向的特征削尖 of courses 移动事件;计算速度 of courses 移动,坡度和蜿蜒,并且分析他们的变化模式。最后,这研究分类可以影响功课移动的出现进二种类型的因素:内部因素例如河,和外部因素的沉积率,坡度和蜿蜒,例如降水和人的活动。 | WANG Yingjie SU Yanjun | 2011 | Journal of Geographical Sciences2011，21，6： | 6 |
| 5 | Phenformin alone or combined with gefitinib inhibits bladder cancer via AMPK and EGFR pathways显示文摘Background:In previous studies,we have shown that the combination of metformin and gefitinib inhibits the growth of bladder cancer cells.Here we examined whether the metformin analogue phenformin,either used alone or in combination with gefitinib,could inhibit growth of bladder cancer cells.Methods:The growth-inhibitory effects of phenformin and gefitinib were tested in one murine and two human bladder cancer cell lines using MTT and clonogenic assays.Effects on cell migration were assessed in a wound healing assay.Synergistic action between the two drugs was assessed using CompuSyn software.The potential involvement of AMPK and EGFR pathways in the effects of phenformin and gefitinib was explored using Western blotting.Results:In MTT and clonogenic assays,phenformin was>10-fold more potent than metformin in inhibiting bladder cancer cell growth.Phenformin also potently inhibited cell migration in wound healing assays,and promoted apop-tosis.AMPK signaling was activated;EGFR signaling was inhibited.Phenformin was synergistic with gefitinib,with the combination of drugs showing much stronger anticancer activity and apoptotic activation than phenformin alone.Conclusions:Phenformin shows potential as an effective drug against bladder cancer,either alone or in combination with gefitinib. | Yanjun Huang Sichun Zhou Caimei He Jun Deng Ting Tao Qiongli Su Kwame Oteng Darko Mei Peng Xiaoping Yang | 2018 | Cancer Communications2018，38，1： | 5 |
| 6 | Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series显示文摘Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment.Terrestrial laser scanning(TLS)is a well-suited tool to study structural rhythm under field conditions.Recent studies have used TLS to describe the structural rhythm of trees,but no consistent patterns have been drawn.Meanwhile,whether TLS can capture structural rhythm in crops is unclear.Here,we aim to explore the seasonal and circadian rhythms in maize structural traits at both the plant and leaf levels from time-series TLS.The seasonal rhythm was studied using TLS data collected at four key growth periods,including jointing,bell-mouthed,heading,and maturity periods.Circadian rhythms were explored by using TLS data acquired around every 2 hours in a whole day under standard and cold stress conditions.Results showed that TLS can quantify the seasonal and circadian rhythm in structural traits at both plant and leaf levels.(1)Leaf inclination angle decreased significantly between the jointing stage and bell-mouthed stage.Leaf azimuth was stable after the jointing stage.(2)Some individual-level structural rhythms(e.g.,azimuth and projected leaf area/PLA)were consistent with leaf-level structural rhythms.(3)The circadian rhythms of some traits(e.g.,PLA)were not consistent under standard and cold stress conditions.(4)Environmental factors showed better correlations with leaf traits under cold stress than standard conditions.Temperature was the most important factor that significantly correlated with all leaf traits except leaf azimuth.This study highlights the potential of time-series TLS in studying outdoor agricultural chronobiology. | Shichao Jin Yanjun Su Yongguang Zhang Shilin Song Qing Li Zhonghua Liu Qin Ma Yan Ge LingLi Liu Yanfeng Ding Frédéric Baret Qinghua Guo | 2021 | Plant Phenomics2021，3，1： | 5 |
| 7 | Simulation and projection of climate change using CMIP6 Muti-models in the Belt and Road Region显示文摘Climate condition over a region is mostly determined by the changes in precipitation,temperature and evaporation as the key climate variables.The countries belong to the Belt and Road region are subjected to face strong changes in future climate.In this paper,we used five global climate models from the latest Sixth Phase of Coupled Model Intercomparison Project(CMIP6)to evaluate future climate changes under seven combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5)across the Belt and Road region.This study focuses on undertaking a climate change assessment in terms of future changes in precipitation,air temperature and actual evaporation for the three distinct periods as near-term period(2021−2040),mid-term period(2041−2060)and long-term period(2081−2100).To discern spatial structure,Köppen−Geiger Climate Classification method has been used in this study.In relative terms,the results indicate an evidence of increasing tendency in all the studied variables,where significant changes are anticipated mostly in the long-term period.In addition to,though it is projected to increase under all the SSP-RCP scenarios,greater increases will be happened under higher emission scenarios(SSP5-8.5 and SSP3-7.0).For temperature,robust increases in annual mean temperature is found to be 5.2°C under SSP3-7.0,and highest 7.0°C under SSP5-8.5 scenario relative to present day.The northern part especially Cold and Polar region will be even more warmer(+6.1°C)in the long-term(2081−2100)period under SSP5-8.5.Similarly,at the end of the twenty-first century,annual mean precipitation is inclined to increase largely with a rate of 2.1%and 2.8%per decade under SSP3-7.0 and SSP5-8.5 respectively.Spatial distribution demonstrates that the largest precipitation increases are to be pronounced in the Polar and Arid regions.Precipitation is projected to increase with response to increasing warming most of the regions.Finally,the actual evaporation is projected to increase significantly with rate of 20.3%under SSP3-7.0 and greatest 27.0%for SSP5-8.5 by the end of the century.It is important to note that the changes in evaporation respond to global mean temperature rise consistently in terms of similar spatial pattern for all the scenarios where stronger increase found in the Cold and Polar regions.The increase in precipitation is overruled by enhanced evaporation over the region.However,this study reveals that the CMIP6 models can simulate temperature better than precipitation over the Belt and Road region.Findings of this study could be the reliable basis for initiating policies against further climate induced impacts in the regional scale. | YanRan Lü Tong Jiang YanJun Wang BuDa Su JinLong Huang Hui Tao | 2020 | Research in Cold and Arid Regions2020，12，6： | 4 |
| 8 | Development characteristics of the fault system and its control on basin structure, Bodong Sag, East China显示文摘The Bodong Sag,located in the Bohai Sea,offshore China,is one of the most petroliferous basins in China.Based on three dimensional seismic reflection data and time slice data,we analyze the fault system of the Bodong area in detail,establish the fault structure pattern of different types and summarize the distribution of the fault system.It is concluded that the development characteristics of the Cenozoic fault system are in accordance with the dextral stress field of the Tanlu Fault,which displayed a brush structure with NNE strike-slip faults as its principal faults,NE-trending extensional faults as secondary faults and EW-trending faults as minor faults.Faults can be divided into (1) strike-slip type,(2) extensional type,(3) strike-slip extensional type and (4) extensional strike-slip type.The spatial structures of different faults have obvious differences because of the fault properties and activity intensity.The fault system at different stages shows tremendous differences because of the transition of the Tanlu Fault from sinistral strike-slip to dextral strike-slip,the transition between extension and strike-slip,and the transition from mantle upwelling to thermal subsidence.According to the controlling effect of faults on basin structure,the Cenozoic basin experienced four evolutionary stages,(a) transition stage from sinistral strike-slip to dextral strike-slip,(b) strike-slip extensional faulted stage,(c) extensional strike-slip faulted stage and (d) strike-slip depression stage.The identification of temporal and spatial differences of faults could be used as a significant guideline for oil and gas exploration in the Bodong area. | Wu Zhiping Cheng Yanjun Yan Shiyong Su Wen Wang Xin Xu Changgui Zhou Xinhuai | 2013 | Petroleum Science2013，10，4： | 4 |
| 9 | Single-Step Organization of Plasmonic Gold Metamaterials with Self-Assembled DNA Nanostructures显示文摘Self-assembled DNA nanostructures hold great promise as nanoscale templates for organizing nanoparticles(NPs)with nearatomistic resolution.However,large-scale organization of NPs with high yield is highly desirable for nanoelectronics and nanophotonic applications.Here,we design fve-strand DNA tiles that can readily self-assemble into well-organized micrometerscale DNA nanostructures.By organizing gold nanoparticles(AuNPs)on these self-assembled DNA nanostructures,we realize the fabrication of one-and two-dimensional Au nanostructures in single steps.We further demonstrate the one-pot synthesis of Au metamaterials for highly amplifed surface-enhanced Raman Scattering(SERS).Tis single-step and high-yield strategy thus holds great potential for fabricating plasmonic metamaterials. | Shaokang Ren Jun Wang Chunyuan Song Qian Li Yanjun Yang Nan Teng Shao Su Dan Zhu Wei Huang Jie Chao Lianhui Wang Chunhai Fan | 2019 | Research2019，，1： | 4 |
| 10 | Cisplatin resistance in lung cancer is mediated by MACC1 expression through PI3K/AKT signaling pathway activation显示文摘 | Qiang Zhang Bin Zhang Leina Sun Qingna Yan Yu Zhang Zhenfa Zhang Yanjun Su Changli Wang | 2018 | Acta Biochimica et Biophysica Sinica2018，50，8： | 3 |
| 11 | Projection of temperature and precipitation under SSPs-RCPs Scenarios over northwest China显示文摘Climate change significantly affects the environmental and socioeconomic conditions in northwest China.Here we evaluate the ability of five general circulation models(GCMs)from 6th phase of the Coupled Model Inter-comparison Project(CMIP6)to reproduce regional temperature and precipitation over northwest China from 1961 to 2014,and project the future temperature and precipitation during 2021 to 2100 under SSPs-RCPs(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5).The results show that the CMIP6 models can simulate temperature better than precipitation.Projections show that the annual mean temperature will further increase under different SSPs-RCPs scenarios in the 21st century.Future climate changes in the near-term(2021-2040),mid-term(2041-2060)and long-term(2081-2100)are analyzed relative to the reference period(1995-2014).In the long term,warming will be significantly higher than the near and mid-terms.In the long term,annual mean temperature will increase by 1.4℃,1.9℃,3.3℃,5.5℃,2.7℃,3.8℃ and 6.0℃ under SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5,respectively.Spatially,warming in the Junggar Basin will be higher than those in the Tarim Basin.Seasonally,the maximum warming zone will be in the mountainous areas of Tarim Basin during spring and autumn,in the southern basin during winter,and in the east during summer.Precipitation shows an increasing trend under different SSPs-RCPs in the 21st century.In the long term,increase in precipitation will be significantly higher than in the near and mid-terms.Increase in annual precipitation in the long term will be 4.1% under SSP1-1.9,13.9% under SSP1-2.6,28.4% under SSP2-4.5, 35.2% under SSP3-7.0, 6.9% under SSP4-3.4, 8.9% under SSP4-6.0, and 27.3% under SSP5-8.5 relative to the reference period of 1995-2014. Spatially, precipitation increase will be higher in the south than the north, especially higher in mountainous regions than the basin under SSP2-4.5, SSP3-7.0, and SSP5-8.5. Seasonally, highest increase can be expected for winter, followed by spring, with significant increase in mountainous regions of southern Tarim Basin. Summer precipitation will reduce in Tian Shan and basins but will significantly increase in the northern margin of the Kunlun Mountain. | Jiancheng QIN Buda SU Hui TAO Yanjun WANG Jinlong HUANG Tong JIANG | 2021 | Frontiers of Earth Science2021，15，1： | 3 |
| 12 | Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing显示文摘Accurate, efficient, and timely yield estimation is critical for crop variety breeding and management optimization. However, the contributions of proximal sensing data characteristics(spectral, temporal, and spatial) to yield estimation have not been systematically evaluated. We collected long-term, hypertemporal, and large-volume light detection and ranging(Li DAR) and multispectral data to(i) identify the best machine learning method and prediction stage for wheat yield estimation,(ii) characterize the contribution of multisource data fusion and the dynamic importance of structural and spectral traits to yield estimation, and(iii) elucidate the contribution of time-series data fusion and 3 D spatial information to yield estimation. Wheat yield could be accurately(R^(2)= 0.891) and timely(approximately-two months before harvest) estimated from fused Li DAR and multispectral data. The artificial neural network model and the flowering stage were always the best method and prediction stage, respectively. Spectral traits(such as CIgreen) dominated yield estimation, especially in the early stage, whereas the contribution of structural traits(such as height) was more stable in the late stage. Fusing spectral and structural traits increased estimation accuracy at all growth stages. Better yield estimation was realized from traits derived from complete 3 D points than from canopy surface points and from integrated multi-stage(especially from jointing to heading and flowering stages) data than from single-stage data. We suggest that this study offers a novel perspective on deciphering the contributions of spectral, structural, and timeseries information to wheat yield estimation and can guide accurate, efficient, and timely estimation of wheat yield. | Qing Li Shichao Jin Jingrong Zang Xiao Wang Zhuangzhuang Sun Ziyu Li Shan Xu Qin Ma Yanjun Su Qinghua Guo Dong Jiang | 2022 | The Crop Journal2022，10，5： | 2 |
| 13 | Two Ultraviolet Radiation Datasets that Cover China显示文摘Ultraviolet(UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes. | Hui LIU Bo HU Yuesi WANG Guangren LIU Liqin TANG Dongsheng JI Yongfei BAI Weikai BAO Xin CHEN Yunming CHEN Weixin DING Xiaozeng HAN Fei HE Hui HUANG Zhenying HUANG Xinrong LI Yan LI Wenzhao LIU Luxiang LIN Zhu OUYANG Boqiang QIN Weijun SHEN Yanjun SHEN Hongxin SU Changchun SONG Bo SUN Song SUN Anzhi WANG Genxu WANG Huimin WANG Silong WANG Youshao WANG Wenxue WEI Ping XIE Zongqiang XIE Xiaoyuan YAN Fanjiang ZENG Fawei ZHANG Yangjian ZHANG Yiping ZHANG Chengyi ZHAO Wenzhi ZHAO Xueyong ZHAO Guoyi ZHOU Bo ZHU | 2017 | Advances in Atmospheric Sciences2017，34，7： | 2 |
| 14 | 苯乙双胍单药或联合吉非替尼通过AMPK和EGFR通路抑制膀胱癌显示文摘背景与目的在前期研究中,我们发现二甲双胍和吉非替尼联合使用可抑制膀胱癌细胞生长。本文旨在研究二甲双胍类似物——苯乙双胍单药或联合吉非替尼能否抑制膀胱癌细胞生长。方法在1种鼠源和2种人源膀胱癌细胞系中,采用MTT和克隆形成实验检测苯乙双胍和吉非替尼对细胞生长的抑制作用。采用伤口愈合实验检测细胞迁移情况。使用CompuSyn软件评估2种药物之间的协同作用。采用蛋白免疫印迹实验分析苯乙双胍和吉非替尼对AMPK和EGFR通路的潜在作用。结果 MTT和克隆形成实验结果显示,苯乙双胍抑制膀胱癌细胞生长的作用是二甲双胍的10倍以上。伤口愈合实验结果显示,苯乙双胍可有效抑制细胞迁移,并促进凋亡。AMPK信号被激活,EGFR信号被抑制。苯乙双胍与吉非替尼可协同作用,二者联合使用比苯乙双胍单药表现出更强的抑癌活性和促凋亡活性。结论苯乙双胍单药或联合吉非替尼均可能成为治疗膀胱癌的有效药物。 | Yanjun Huang Sichun Zhou Caimei He Jun Deng Ting Tao Qiongli Su Kwame Oteng Darko Mei Peng Xiaoping Yang | 2019 | 癌症2019，38，5： | 1 |
| 15 | Comparative QSAR modeling of antitumor activity of ARC-111 analogues using stepwise MLR, PLS, and ANN techniques显示文摘 | Yanjun Yu Rongxin Su Libing Wang Wei Qi Zhimin He | 2010 | Medicinal Chemistry Research2010，，9： | 1 |
| 16 | Triple-functional bone adhesive with enhanced internal fixation,bacteriostasis and osteoinductive properties for open fracture repair显示文摘At present,effective fixation and anti-infection implant materials represent the mainstay for the treatment of open fractures.However,external fixation can cause nail tract infections and is ineffective for fixing small fracture fragments.Moreover,closed reduction and internal fixation during the early stage of injury can lead to potential bone infection,conducive to bone nonunion and delayed healing.Herein,we designed a bone adhesive with anti-infection,osteogenic and bone adhesion fixation properties to promote reduction and fixation of open fractures and subsequent soft tissue repair.It was prepared by the reaction of gelatin(Gel)and oxidized starch(OS)with vancomycin(VAN)-loaded mesoporous bioactive glass nanoparticles(MBGNs)covalently cross-linked with Schiff bases.Characterization and adhesion experiments were conducted to validate the successful preparation of the Gel-OS/VAN@MBGNs(GOVM-gel)adhesive.Meanwhile,in vitro cell experiments demonstrated its good antibacterial effects with the ability to stimulate bone marrow mesenchymal stem cell(BMSCs)proliferation,upregulate the expression of alkaline phosphatase(ALP)and osteogenic proteins(RunX2 and OPN)and enhance the deposition of calcium nodules.Additionally,we established a rat skull fracture model and a subcutaneous infection model.The histological analysis showed that bone adhesive enhanced osteogenesis,and in vivo experiments demonstrated that the number of inflammatory cells and bacteria was significantly reduced.Overall,the adhesive could promote early reduction of fractures and antibacterial and osteogenic effects,providing the foothold for treatment of this patient population. | Yusheng Yang Shenghui Su Shencai Liu Weilu Liu Qinfeng Yang Liangjie Tian Zilin Tan Lei Fan Bin Yu Jian Wang Yanjun Hu | 2023 | Bioactive Materials2023，，7： | 1 |
| 17 | Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery显示文摘Forests of the Sierra Nevada(SN)mountain range are valuable natural heritages for the region and the country,and tree height is an important forest structure parameter for understanding the SN forest ecosystem.There is still a need in the accurate estimation of wall-to-wall SN tree height distribution at fine spatial resolution.In this study,we presented a method to map wall-to-wall forest tree height(defined as Lorey’s height)across the SN at 70-m resolution by fusing multi-source datasets,including over 1600 in situ tree height measurements and over 1600 km^(2) airborne light detection and ranging(LiDAR)data.Accurate tree height estimates within these airborne LiDAR boundaries were first computed based on in situ measurements,and then these airborne LiDAR-derived tree heights were used as reference data to estimate tree heights at Geoscience Laser Altimeter System(GLAS)footprints.Finally,the random forest algorithm was used to model the SN tree height from these GLAS tree heights,optical imagery,topographic data,and climate data.The results show that our fine-resolution SN tree height product has a good correspondence with field measurements.The coefficient of determination between them is 0.60,and the root-mean-squared error is 5.45 m. | Yanjun Su Qin Ma Qinghua Guo | 2017 | International Journal of Digital Earth2017，10，3： | 1 |
| 18 | Study on the gel properties and secondary structure of soybean protein isolate/egg white composite gels显示文摘 | Yujie Su Yiting Dong Fuge Niu Chenying Wang Yuntao Liu Yanjun Yang | 2015 | European Food Research and Technology2015，，2： | 1 |
| 19 | CpG_MPs:identification of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data显示文摘 | SU Jianzhong YAN Haidan WEI Yanjun | 2012 | Nucleic Acids Res2012，41，： | 1 |
| 20 | Automatic segmentation of stem and leaf components and individual maize plants in field terrestrial LiDAR data using convolutional neural networks显示文摘High-throughput maize phenotyping at both organ and plant levels plays a key role in molecular breeding for increasing crop yields. Although the rapid development of light detection and ranging(Li DAR) provides a new way to characterize three-dimensional(3 D) plant structure, there is a need to develop robust algorithms for extracting 3 D phenotypic traits from Li DAR data to assist in gene identification and selection. Accurate 3 D phenotyping in field environments remains challenging, owing to difficulties in segmentation of organs and individual plants in field terrestrial Li DAR data. We describe a two-stage method that combines both convolutional neural networks(CNNs) and morphological characteristics to segment stems and leaves of individual maize plants in field environments. It initially extracts stem points using the Point CNN model and obtains stem instances by fitting 3 D cylinders to the points. It then segments the field Li DAR point cloud into individual plants using local point densities and 3 D morphological structures of maize plants. The method was tested using 40 samples from field observations and showed high accuracy in the segmentation of both organs(F-score =0.8207) and plants(Fscore =0.9909). The effectiveness of terrestrial Li DAR for phenotyping at organ(including leaf area and stem position) and individual plant(including individual height and crown width) levels in field environments was evaluated. The accuracies of derived stem position(position error =0.0141 m), plant height(R^(2)>0.99), crown width(R^(2)>0.90), and leaf area(R^(2)>0.85) allow investigating plant structural and functional phenotypes in a high-throughput way. This CNN-based solution overcomes the major challenges in organ-level phenotypic trait extraction associated with the organ segmentation, and potentially contributes to studies of plant phenomics and precision agriculture. | Zurui Ao Fangfang Wu Saihan Hu Ying Sun Yanjun Su Qinghua Guo Qinchuan Xin | 2022 | The Crop Journal2022，10，5： | 1 |
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