| 光谱学与光谱分析 |
|
|
|
|
|
| Study on Temperature Correctional Models of Quantitative Analysis with Near Infrared Spectroscopy |
| ZHANG Jun1, CHEN Hua-cai1, 2, CHEN Xing-dan1 |
1. State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130022, China
2. China Institute of Metrology, Hangzhou 310018, China |
|
|
|
|
Abstract Effect of enviroment temperature on near infrared spectroscopic quantitative analysis was studied. The temperature correction model was calibrated with 45 wheat samples at different environment temperaturs and with the temperature as an external variable. The constant temperature model was calibated with 45 wheat samples at the same temperature. The predicted results of two models for the protein contents of wheat samples at different temperatures were compared. The results showed that the mean standard error of prediction (SEP) of the temperature correction model was 0.333, but the SEP of constant temperature (22 ℃) model increased as the temperature difference enlarged, and the SEP is up to 0.602 when using this model at 4 ℃. It was suggested that the temperature correctiona model improves the analysis precision.
|
|
Received: 2004-03-01
Accepted: 2004-07-16
|
|
|
|
Corresponding Authors:
ZHANG Jun
|
|
| Cite this article: |
|
ZHANG Jun,CHEN Hua-cai,CHEN Xing-dan. Study on Temperature Correctional Models of Quantitative Analysis with Near Infrared Spectroscopy [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(06): 890-893.
|
|
|
|
| URL: |
|
https://www.gpxygpfx.com/EN/Y2005/V25/I06/890 |
[1] Fornés V, Chaussidon J. J. Chem. Phys., 1978, 68: 4667.
[2] Delwiche S R, Norris K H, Pitt R E. Appl. Spectr., 1992, 46: 782.
[3] Hazen Kevin H, Arnold Mark A, Small Gary W. Appl. Spectr., 1994, 48: 477.
[4] Hideyuki Abe, Toyoko Kusama, Sumio Kawano, Mutsuo Iwamoto. Japanese Spectrum Research(分光研究), 1995, 44(5): 247.
[5] Noda L, Liu Y, Ozaki Y, Czarnecki M A. J. Phys. Chem., 1995, 99: 3068.
[6] Florian Wulfert, Wim Th Kok, Age K Smilde. Anal. Chem., 1998, 70: 1761.
[7] BAI Sheng-yuan, GU Pei-fu, LIU Xu, TANG Jin-fa(白胜元，顾培夫，刘 旭，唐晋发). Acta Photonica Sinica(光子学报), 2001, 30(5): 576.
[8] ZHU Er-yi, YANG Peng-yuan(朱尔一，杨芃原). Application and Technique of Chemertric(化学计量学技术及应用). Beijing: Science Press(北京: 科学出版社), 2001. 186.
[9] ZHENG Yong-mei, ZHANG Jun, LI Rong-fu, et al(郑咏梅，张 军，李荣福，等). Laser and Infrared(激光与红外), 2003, 33(2): 125.
[10] ZHENG Yong-mei, ZHANG Jun, CHEN Xing-dan, SHEN Xuan-guo, ZHANG Tie-qiang(郑咏梅，张 军，陈星旦，申铉国，张铁强). Spectroscopy and Spectral Analysis(光谱学与光谱分析). 2004，24(6)：675.
[11] LI Ning, MIN Shun-geng, QIN Fang-li, ZHANG Ming-xiang, YE Sheng-feng(李 宁，闵顺耕，覃方丽，张明祥，叶升锋). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2004，24(1)：45.
[12] WANG Duo-jia, ZHOU Xiang-yang, JIN Tong-ming, HU Xiang-na, ZHONG Jiao-e, et al(王多加，周向阳，金同铭，胡祥娜，钟娇娥, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2004，24(4)：447.
|
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [3] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [4] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [5] |
LIU Hao-dong1, 2, JIANG Xi-quan1, 2, NIU Hao1, 2, LIU Yu-bo1, LI Hui2, LIU Yuan2, Wei Zhang2, LI Lu-yan1, CHEN Ting1，ZHAO Yan-jie1*，NI Jia-sheng2*. Quantitative Analysis of Ethanol Based on Laser Raman Spectroscopy Normalization Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3820-3825. |
| [6] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [7] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [8] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [9] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [10] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [11] |
LIN Hong-jian1, ZHAI Juan1*, LAI Wan-chang1, ZENG Chen-hao1, 2, ZHAO Zi-qi1, SHI Jie1, ZHOU Jin-ge1. Determination of Mn, Co, Ni in Ternary Cathode Materials With
Homologous Correction EDXRF Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3436-3444. |
| [12] |
HUANG Li, MA Rui-jun*, CHEN Yu*, CAI Xiang, YAN Zhen-feng, TANG Hao, LI Yan-fen. Experimental Study on Rapid Detection of Various Organophosphorus Pesticides in Water by UV-Vis Spectroscopy and Parallel Factor Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3452-3460. |
| [13] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [14] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [15] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
|
|
|
|
