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浏览/检索结果: 共7条，第1-7条 帮助 限定条件 专题：长春光学精密机械与物理研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Establishment and evaluation of a quantitative analysis model for potentially toxic metals in wet soil samples by LIBS 期刊论文 European Journal of Soil Science, 2022, 卷号: 73, 期号: 2, 页码: 10 作者:  Y. X. Xu;  B. Han;  X. Tan;  Q. B. Jiao;  Z. Y. Ma 收藏  |  浏览/下载：3/0  |  提交时间：2023/06/14 Measurement of moisture content in lubricating oils of high-speed rail gearbox by Vis-NIR spectroscopy 期刊论文 Optik, 2020, 卷号: 224, 页码: 8 作者:  C. Y. Liu,X. J. Tang,T. Yu,T. S. Wang,Z. W. Lu and W. X. Yu 收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06 Baseline Fitting of Partial Least Squares for Oxygen A Absorption Band 期刊论文 Zhongguo Jiguang/Chinese Journal of Lasers, 2017, 卷号: 44, 期号: 8 作者:  Li, J.;  M. Zhang and D. Zhang 收藏  |  浏览/下载：10/0  |  提交时间：2018/06/13 多元散射校正预处理波段对近红外光谱定标模型的影响 期刊论文 光谱学与光谱分析, 2014, 期号: 9, 页码: 2387-2390 王动民; 纪俊敏; 高洪智 收藏  |  浏览/下载：25/0  |  提交时间：2015/04/17 多元散射校正  预处理波段  偏最小二乘回归  近红外光谱分析   The Effect of MSC Spectral Pretreatment Regions on Near Infrared Spectroscopy Calibration Results 期刊论文 Spectroscopy and Spectral Analysis, 2014, 卷号: 34, 期号: 9, 页码: 2387-2390 Wang D. M.; Ji J. M.; Gao H. Z. 收藏  |  浏览/下载：18/0  |  提交时间：2015/04/24 The study on the near infrared spectrum technology of sauce component analysis (EI CONFERENCE) 会议论文 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Li S.; Zhang J.; Chen X.; Liang J.; Wang C. 收藏  |  浏览/下载：19/0  |  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 ICO20: Biomedical Optics, August 21, 2005 - August 26, 2005, Changchun, China Chen H.-C.; Chen X.-D.; Lu Y.-J.; Cao Z.-Q. 收藏  |  浏览/下载：16/0  |  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.