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Chinese Academy of Sciences Institutional Repositories Grid
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Temporal and spatial variations in the terrestrial water storage across Central Asia based on multiple satellite datasets and global hydrological models 期刊论文  OAI收割
JOURNAL OF HYDROLOGY, 2021, 卷号: 596, 页码: 16
作者:  
Hu, Zengyun;  Zhang, Zizhan;  Sang, Yan-Fang;  Qian, Jing;  Feng, Wei
  |  收藏  |  浏览/下载:48/0  |  提交时间:2021/08/19
The powdery mildew disease of rubber (Oidium heveae) is jointly controlled by the winter temperature and host phenology 期刊论文  OAI收割
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY, 2021, 卷号: 65, 期号: 10, 页码: 1707-1718
作者:  
Zhai,De-Li;  Thaler,Philippe;  Luo,Yiqi;  Xu,Jianchu
  |  收藏  |  浏览/下载:42/0  |  提交时间:2022/04/02
Measurement of moisture content in lubricating oils of high-speed rail gearbox by Vis-NIR spectroscopy 期刊论文  OAI收割
Optik, 2020, 卷号: 224
作者:  
Liu, Chenyang;  Tang, Xingjia;  Yu, Tao;  Wang, Taisheng;  Lu, Zhenwu
  |  收藏  |  浏览/下载:83/0  |  提交时间:2020/11/03
Phytoplankton community, structure and succession delineated by partial least square regression in Daya Bay, South China Sea 期刊论文  OAI收割
ECOTOXICOLOGY, 2020, 卷号: 29, 期号: 6, 页码: 751, 761
作者:  
Wu, Mei-Lin;  Wang, Yu-Tu;  Cheng, Hao;  Sun, Fu-lin;  Fei, Jiao
  |  收藏  |  浏览/下载:31/0  |  提交时间:2020/09/22
Learning Instance Correlation Functions for Multilabel Classification 期刊论文  OAI收割
ieee transactions on cybernetics, 2017, 卷号: 47, 期号: 2, 页码: 499-510
作者:  
Liu, Huawen;  Li, Xuelong;  Zhang, Shichao
收藏  |  浏览/下载:25/0  |  提交时间:2017/04/06
Evaluation of MLSR and PLSR for estimating soil element contents using visible/near-infrared spectroscopy in apple orchards on the Jiaodong peninsula 期刊论文  OAI收割
CATENA, 2016, 卷号: 137, 页码: 340-349
作者:  
Yu, X;  Liu, Q;  Wang, YB;  Liu, XY;  Liu, X
收藏  |  浏览/下载:40/0  |  提交时间:2016/04/24
An experimental study on paddy soil moisture inversion based on emissive hyperspectra 会议论文  OAI收割
2012 First International Conference on Agro-Geoinformatics, New York
Huang Qi-ting; Luo Jian-cheng; Shi Zhou; Li Jun-li
收藏  |  浏览/下载:30/0  |  提交时间:2014/12/07
Band Selection Method for Retrieving Soil Lead Content with Hyperspectral Remote Sensing Data 会议论文  OAI收割
Earth Resources and Environmental Remote Sensing-Gis Applications, Bellingham
Zhang, Xia; Wen, Jianting; Zhao, Dong
收藏  |  浏览/下载:24/0  |  提交时间:2014/12/07
The study on the near infrared spectrum technology of sauce component analysis (EI CONFERENCE) 会议论文  OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:  
Li S.;  Wang C.;  Chen X.;  Chen X.;  Chen X.
收藏  |  浏览/下载:32/0  |  提交时间:2013/03/25
The author  Shangyu Li  engages in supervising and inspecting the quality of products. In soy sauce manufacturing  quality control of intermediate and final products by many components such as total nitrogen  saltless soluble solids  nitrogen of amino acids and total acid is demanded. Wet chemistry analytical methods need much labor and time for these analyses. In order to compensate for this problem  we used near infrared spectroscopy technology to measure the chemical-composition of soy sauce. In the course of the work  a certain amount of soy sauce was collected and was analyzed by wet chemistry analytical methods. The soy sauce was scanned by two kinds of the spectrometer  the Fourier Transform near infrared spectrometer (FT-NIR spectrometer) and the filter near infrared spectroscopy analyzer. The near infrared spectroscopy of soy sauce was calibrated with the components of wet chemistry methods by partial least squares regression and stepwise multiple linear regression. The contents of saltless soluble solids  total nitrogen  total acid and nitrogen of amino acids were predicted by cross validation. The results are compared with the wet chemistry analytical methods. The correlation coefficient and root-mean-square error of prediction (RMSEP) in the better prediction run were found to be 0.961 and 0.206 for total nitrogen  0.913 and 1.215 for saltless soluble solids  0.855 and 0.199 nitrogen of amino acids  0.966 and 0.231 for total acid  respectively. The results presented here demonstrate that the NIR spectroscopy technology is promising for fast and reliable determination of major components of soy sauce.  
Fast determination of total ginsenosides content in Ginseng powder by near infrared reflectance spectroscopy (EI CONFERENCE) 会议论文  OAI收割
ICO20: Biomedical Optics, August 21, 2005 - August 26, 2005, Changchun, China
作者:  
Chen X.-D.;  Chen X.-D.
收藏  |  浏览/下载:23/0  |  提交时间:2013/03/25
Near infrared (NIR) reflectance spectroscopy was used to develop a fast determination method for total ginsenosides in Ginseng (Panax Ginseng) powder. The spectra were analyzed with multiplicative signal correction (MSC) correlation method. The best correlative spectra region with the total ginsenosides content was 1660 nm1880 nm and 2230nm-2380 nm. The NIR calibration models of ginsenosides were built with multiple linear regression (MLR)  principle component regression (PCR) and partial least squares (PLS) regression respectively. The results showed that the calibration model built with PLS combined with MSC and the optimal spectrum region was the best one. The correlation coefficient and the root mean square error of correction validation (RMSEC) of the best calibration model were 0.98 and 0.15% respectively. The optimal spectrum region for calibration was 1204nm-2014nm. The result suggested that using NIR to rapidly determinate the total ginsenosides content in ginseng powder were feasible.