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Effects of land use change on the spatiotemporal variability of soil organic carbon in an urban-rural ecotone of Beijing,China

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Journal of Integrative Agriculture 2016年第4期15卷 918-928页

作者： YE Hui-chun huang Yuan-fang CHEN Peng-fei huang wen-jiang ZHANG Shi-wen huangShan-yu HOU Sen Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100094P.R.China Hainan Key Laboratory of Earth Observation Sanya 572029P.R.China College of Resources and Environment China Agricultural UniversityBeijing 100193P.R.China State Key Laboratory of Resources and Environment Information System Institute of Geographic Science and Natural Resources ResearchChinese Academy of SciencesBeijing 100101P.R.China College of Earth and Environment Anhui University of Science and TechnologyHuainan 232001P.R.China Institute of Geography University of CologneKoln 50923Germany

Understanding the effects of land use changes on the spatiotemporal variation of soil organic carbon （SOC） can provide guidance for low carbon and sustainable agriculture. In this paper, based on the large-scale datasets of soil surveys in 1982 and 2009 for Pinggu District -- an urban-rural ecotone of Beijing, China, the effects of land use and land use changes on both temporal variation and spatial variation of SOC were analyzed. Results showed that from 1982 to 2009 in Pinggu District, the following land use change mainly occurred： Grain cropland converted to orchard or vegetable land, and grassland converted to forestland. The SOC content decreased in region where the land use type changed to grain cropland （e.g., vegetable land to grain cropland decreased by 0.7 g kg-1; orchard to grain cropland decreased by 0.2 g kg-l）. In contrast, the SOC content increased in region where the land use type changed to either orchard （excluding forestland） or forestland （e.g., grain cropland to orchard and forestland increased by 2.7 and 2.4 g kg-1, respectively; grassland to orchard and forestland increased by 4.8 and 4.9 g kg-1, respectively）. The organic carbon accumulation capacity per unit mass of the soil increased in the following order： grain cropland soil〈vegetable land/grassland soil〈orchard soil〈forestland soil. Therefore, to both secure supply of agricultural products and develop low carbon agriculture in a modern city, orchard has proven to be a good choice for land using.

关键词： land use change soil organic carbon spatiotemporal variability urban-rural ecotone

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Relationship of 2 100-2 300 nm Spectral Characteristics of Wheat Canopy to Leaf Area Index and Leaf N as Affected by Leaf Water Content

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Pedosphere 2006年第3期16卷 333-338页

作者： ZHAO Chun-jiang WANG Ji-Hua LIU Liang-Yun huang wen-jiang ZHOU Qi-Fa National Engineering Research Center for Information Technology in Agriculture Beijing 100089 （China） The State Key Laboratory of Plant Physiology and Biochemistry College of Life Sciences Zhejiang University Hangzhou 310012 （China）

The effects of leaf water status in a wheat canopy on the accuracy of estimating leaf area index (LAI) and N were determined in this study using extracted spectral characteristics in the 2 000-2 300 nm region of the short wave infrared (SWI) band. A newly defined spectral index, relative adsorptive index in the 2000-2300 nm region (RAI2000-2300), which can be calculated by RAI2000-2300 = (R2224 - R2054) (R2224 + R2054)-1 with R being the reflectance at 2224 or 2054 nm, was utilized. This spectral index, RAI2000-2300, was significantly correlated (P < 0.01) with green LAI and leaf N concentration and proved to be potentially valuable for monitoring plant green LAI and leaf N at the field canopy scale. Moreover, plant LAI could be monitored more easily and more successfully than plant leaf N. The study also showed that leaf water had a strong masking effect on the 2 000-2 300 nm spectral characteristics and both the coefficient between RAI2000-2300 and green LAI and that between RAI2000-2300 and leaf N content decreased as leaf water content increased.

关键词： leaf area index nitrogen plant water status reflectance Triticum aestivum L.

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Detection of Internal Leaf Structure Deterioration Using a New Spectral Ratio Index in the Near-Infrared Shoulder Region

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Journal of Integrative Agriculture 2014年第4期13卷 760-769页

作者： LIU Liang-yun huang wen-jiang PU Rui-liang WANG Ji-hua Key Laboratory of Digital Earth Science Center for Earth Observation and Digital EarthChinese Academy of Sciences Department of Geography Environmentand PlanningUniversity of South Florida National Engineering Research Center for Information Technology in Agriculture

Spectral reflectance in the near-infrared （NIR） shoulder （750-900 nm） region is affected by internal leaf structure, but it has rarely been investigated. In this study, a dehydration treatment and three paraquat herbicide applications were conducted to explore how spectral reflectance and shape in the NIR shoulder region responded to various stresses. A new spectral ratio index in the NIR shoulder region （NSRI）, defined by a simple ratio of reflectance at 890 nm to reflectance at 780 nm, was proposed for assessing leaf structure deterioration. Firstly, a wavelength-independent increase in spectral reflectance in the NIR shoulder region was observed from the mature leaves with slight dehydration. An increase in spectral slope in the NIR shoulder would be expected only when water stress developed sufficiently to cause severe leaf dehydration resulting in an alteration in cell structure. Secondly, the alteration of leaf cell structure caused by Paraquat herbicide applications resulted in a wavelength-dependent variation of spectral reflectance in the NIR shoulder region. The NSRI in the NIR shoulder region increased significantly under an herbicide application. Although the dehydration process also occurred with the herbicide injury, NSRI is more sensitive to herbicide injury than the water-related indices （water index and normalized difference water index） and normalized difference vegetation index. Finally, the sensitivity of NSRI to stripe rust in winter wheat was examined, yielding a determination coefficient of 0.61, which is more significant than normalized difference vegetation index （NDVI）, water index （WI） and normalized difference water index （NDWI）, with a determination coefficient of 0.45, 0.36 and 0.13, respectively. In this study, all experimental results demonstrated that NSRI will increase with internal leaf structure deterioration, and it is also a sensitive spectral index for herbicide injury or stripe rust in winter wheat.

关键词： spectral ratio index spectral reflectance vegetation index dehydration paraquat herbicide stripe rust

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Controlling underestimation bias in reinforcement learning via minmax operation

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Chinese Journal of Aeronautics 2024年第7期37卷 406-417页

作者： Fanghui huang Yixin HE Yu ZHANG Xinyang DENG wen jiang School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China College of Information Science and Engineering Jiaxing UniversityJiaxing 314001China

Obtaining the accurate value estimation and reducing the estimation bias are the key issues in reinforcement ***,current methods that address the overestimation problem tend to introduce underestimation,which face a challenge of precise decision-making in many *** address this issue,we conduct a theoretical analysis of the underestimation bias and propose the minmax operation,which allow for flexible control of the estimation ***,we select the maximum value of each action from multiple parallel state-action networks to create a new state-action value ***,a minimum value is selected to obtain more accurate value ***,based on the minmax operation,we propose two novel algorithms by combining Deep Q-Network(DQN)and Double DQN(DDQN),named minmax-DQN and ***,we conduct theoretical analyses of the estimation bias and variance caused by our proposed minmax operation,which show that this operation significantly improves both underestimation and overestimation biases and leads to the unbiased ***,the variance is also reduced,which is helpful to improve the network training ***,we conduct numerous comparative experiments in various environments,which empirically demonstrate the superiority of our method.

关键词： Reinforcement learning Minmax operation Estimation bias Underestimation bias Variance

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Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

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Chinese Journal of Aeronautics 2024年第1期37卷 287-299页

作者： Yu ZHANG Fanghui huang Xinyang DENG Mingda LI wen jiang School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China

Recognizing target intent is crucial for making decisions on the ***,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition *** with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)*** target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain ***,the HIR model is utilized to recognize intent for a tested sample from uncertain ***,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested *** retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample *** simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

关键词： Causal effect analysis Hybrid intention recognition Intervention retrieval Target intention Uncertainty reasoning

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Spectroscopic Leaf Level Detection of Powdery Mildew for Winter Wheat Using Continuous Wavelet Analysis

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Journal of Integrative Agriculture 2012年第9期11卷 1474-1484页

作者： ZHANG Jing-cheng YUAN Lin WANG Ji-hua huang wen-jiang CHEN Li-ping ZHANGDong-yan Beijing Research Center for Information Technology in Agriculture Beijing 100097 R.P.China Institute of Agriculture Remote Sensing and Information System Application Zhejiang University Hangzhou 310029 R.P.China Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing 100094 R.P.China

Powdery mildew （Blumeria graminis） is one of the most destructive crop diseases infecting winter wheat plants, and has devastated millions of hectares of farmlands in China. The objective of this study is to detect the disease damage of powdery mildew on leaf level by means of the hyperspectral measurements, particularly using the continuous wavelet analysis. In May 2010, the reflectance spectra and the biochemical properties were measured for 114 leaf samples with various disease severity degrees. A hyperspectral imaging system was also employed for obtaining detailed hyperspectral information of the normal and the pustule areas within one diseased leaf. Based on these spectra data, a continuous wavelet analysis （CWA） was carried out in conjunction with a correlation analysis, which generated a so-called correlation scalogram that summarizes the correlations between disease severity and the wavelet power at different wavelengths and decomposition scales. By using a thresholding approach, seven wavelet features were isolated for developing models in determining disease severity. In addition, 22 conventional spectral features （SFs） were also tested and compared with wavelet features for their efficiency in estimating disease severity. The multivariate linear regression （MLR） analysis and the partial least square regression （PLSR） analysis were adopted as training methods in model mildew on leaf level were found to be closely related with the development. The spectral characteristics of the powdery spectral characteristics of the pustule area and the content of chlorophyll. The wavelet features performed better than the conventional SFs in capturing this spectral change. Moreover, the regression model composed by seven wavelet features outperformed （R2=0.77, relative root mean square error RRMSE=0.28） the model composed by 14 optimal conventional SFs （R2---0.69, RRMSE--0.32） in estimating the disease severity. The PLSR method yielded a higher accuracy than the MLR met

关键词： powdery mildew disease severity continuous wavelet analysis partial least square regression

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Leaf chlorophyll content retrieval of wheat by simulated RapidEye, Sentinel-2 and EnMAP data

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Journal of Integrative Agriculture 2019年第6期18卷 1230-1245页

作者： CUI Bei ZHAO Qian-jun huang wen-jiang SONG Xiao-yu YE Hui-chun ZHOU Xian-feng Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijing 100094P.R.China University of Chinese Academy of Sciences Beijing 100094P.R.China Key Laboratory of Earth Observation Hainan ProvinceSanya 572029P.R.China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry SciencesBeijing 100097P.R.China College of Life Information Science and Instrument Engineering Hangzhou Dianzi UniversityHangzhou 310018P.R.China

Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual *** accurate estimation of LCC can therefore provide valuable information for precision field ***-edge information from hyperspectral data has been widely used to estimate crop ***,after the advent of red-edge bands in satellite imagery,no systematic evaluation of the performance of satellite data has been *** this end,we analyze herein the performance of winter wheat LCC retrieval of currant and forthcoming satellites(RapidEye,Sentinel-2 and EnMAP)and their new red-edge bands by using partial least squares regression(PLSR)and a vegetation-indexbased *** satellite spectral data were obtained by resampling ground-measured hyperspectral data under various field conditions and according to specific spectral response functions and spectral *** results showed:1)This study confirmed that RapidEye,Sentinel-2 and EnMAP data are suitable for winter wheat LCC *** the PLSR approach,Sentinel-2 data provided more accurate estimates of LCC(R2=0.755,0.844,0.805 for 2002,2010,and 2002+2010)than do RapidEye data(R2=0.689,0.710,0.707 for 2002,2010,and 2002+2010)and EnMAP data(R2=0.735,0.867,0.771 for 2002,2010,and 2002+2010).For index-based approaches,the MERIS terrestrial chlorophyll index,which is a vegetation index with two red-edge bands,was the most sensitive and robust index for LCC for both the Sentinel-2 and EnMAP data(R2≥0.628),and the indices(NDRE1,SRRE1 and CIRE1)with a single red-edge band were the most sensitive and robust indices for the RapidEye data(R2≥0.420);2)According to the analysis of the effect of the wavelength and number of used red-edge spectral bands on LCC retrieval,the short-wavelength red-edge bands(from 699 to 734 nm)provided more accurate predictions when using the PLSR approach,whereas the long-wavelength red-edge bands(740 to 783 nm)gave more accurate predictions when using

关键词： leaf chlorophyll content RapidEye Sentinel-2 EnMAP red-edge band

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Photoacoustic/ultrasound dual-modal imaging of human nails: A pilot study

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Journal of Innovative Optical Health Sciences 2024年第6期17卷 15-28页

作者： Yanting wen Yijie huang Lin huang Dan Wu Renbin Zhong Shixie jiang Yudi Zhang Ting Liu Xiaotian Liu Huabei jiang Department of Ultrasound Chengdu Fifth People's Hospital Chengdu 611137P.R.China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 P.R.China School of Electronic Science and Engineering University of Electronic Science and Technology Chengdu 611731 P.R.China Department of Psychiatry University of Florida College of Medicine GainesvilleFL 32610USA Department of Medical Engineering University of South Florida Tampa 33620USA

Traditional diagnostic techniques including visual examination,ultrasound(US),and magnetic resonance imaging(MRI)have limitations of in-depth information for the detection of nail disorders,resolution,and *** pilot study,for thefirst time,evaluates a dualmodality imaging system that combines photoacoustic tomography(PAT)with the US for the multiparametric quantitative assessment of human *** study involved a small cohort offive healthy volunteers who underwent PAT/US imaging for acquiring the nail unit *** PAT/US dual-modality imaging successfully revealed thefine anatomical structures and microvascular distribution within the nail and nail ***,this system utilized multispectral PAT to analyze functional tissue parameters,including oxygenated hemoglobin,deoxyhemoglobin,oxygen saturation,and collagen under tourniquet and cold stimulus tests to evaluate changes in the microcirculation of the nail *** quantitative analysis of multispectral PAT reconstructed images demonstrated heightened sensitivity in detecting alterations in blood oxygenation levels and collagen content within the nail bed,under simulated different physiological *** pilot study highlights the potential of PAT/US dual-modality imaging as a real-time,noninvasive diagnostic modality for evaluating human nail health and for early detection of nail bed pathologies.

关键词： Nail photoacoustic tomography ultrasound multi-modality quantitative parameter

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Exploring the Feasibility of Winter Wheat Freeze Injury by Integrating Grey System Model with RS and GIS

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Journal of Integrative Agriculture 2013年第7期12卷 1162-1172页

作者： WANG Hui-fang GUO wei WANG Ji-hua huang wen-jiang GU Xiao-he DONG Ying-ying XUXin-gang Beijing Research Centre for Information Technology in Agriculture Institute of Agriculture Remote Sensing and Information System Application Zhejiang University

Winter wheat freeze injury is one of the main agro-meteorological disasters affecting wheat production. In order to evaluate the severity of freeze injury on winter wheat systematically, we proposed a grey-system model （GSM） to monitor the degree and the distribution of the winter wheat freeze injury. The model combines remote sensing （RS） and geographic information system （GIS） technology. It gave examples of wheat freeze injury monitoring applications in Gaocheng and Jinzhou of Hebei Province, China. We carried out a quantitative evaluation method study on the severity of winter wheat freeze injury. First, a grey relational analysis （GRA） was conducted. At the same time, the weights of the stressful factors were determined. Then a wheat freezing injury stress multiple factor spatial matrix was constructed using spatial interpolation technology. Finally, a winter wheat freeze damage evaluation model was established through grey clustering algorithm （GCA）, and classifying the study area into three sub-areas, affected by severe, medium or light disasters. The evaluation model were verified by the Kappa model, the overall accuracy reached 78.82% and the Kappa coefficient was 0.6754. Therefore, through integration of GSM with RS images as well as GIS analysis, quantitative evaluation and study of winter wheat freeze disasters can be conducted objectively and accurately, making the evaluation model more scientific.

关键词： winter wheat freeze injury RS GIS GRA GCA

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Single‑cell sequencing reveals the reproductive variations between primiparous and multiparous Hu ewes

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Journal of Animal Science and Biotechnology 2024年第2期15卷 614-631页

作者： Ting Ge Yifan wen Bo Li Xiaoyu huang Shaohua jiang Enping Zhang Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China

Background In the modern sheep production systems,the reproductive performance of ewes determines the economic profitability of *** the genetic mechanisms underlying differences in the litter size is important for the selection and breeding of highly prolific *** sheep,a high-quality Chinese sheep breed,is known for its high fecundity and is often used as a model to study prolificacy *** the current study,animals were divided into two groups according to their delivery rates in three consecutive lambing seasons(namely,the high and low reproductive groups with≥3 lambs and one lamb per season,n=3,respectively).The ewes were slaughtered within 12 h of estrus,and unilateral ovarian tissues were collected and analyzed by 10×Genomics single-cell RNA *** A total of 5 types of somatic cells were identified and corresponding expression profiles were mapped in the ovaries of each ***,the differences in the ovary somatic cell expression profiles between the high and low reproductive groups were mainly clustered in the granulosa ***,four granulosa cell subtypes were *** analysis revealed that the abundance of JPH1 expression and the reduction of LOC101112291 expression could lead to different evolutionary directions of the granulosa ***,the expression levels of FTH1 and FTL in mural granulosa cells of the highly reproductive group were significantly *** genes inhibit necroptosis and ferroptosis of mural granulosa cells,which helps prevent follicular *** This study provides insights into the molecular mechanisms underlying the high fecundity of Hu *** differences in gene expression profiles,particularly in the granulosa cells,suggest that these cells play a critical role in female *** findings also highlight the importance of genes such as JPH1,LOC101112291,FTH1,and FTL in regulating granulosa cell function and follicular development.

关键词： Granulosa cells Hu sheep Lambing number Ovarian somatic cells Single-cell RNA sequencing

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