| 光谱学与光谱分析 |
|
|
|
|
|
| A Point Raman Scanning Method for Rapidly Detection of Spinach Quality and Safety Parameters |
| XU Tian-feng, PENG Yan-kun, LI Yong-yu*, ZHAI Chen, ZHENG Xiao-chun, QIAO Lu，Adnan Abbas |
| College of Engineering, China Agricultural University, National Research and Development Center for Agro-processing Equipment, Beijing 100083, China |
|
|
|
|
Abstract According to actual market demand for nondestructive detection of vegetables quality and safety, combined with the heterogeneity of quality and safety parameters such as pesticide residues on leaf vegetables surface and to realize the automatic point scanning for the whole leaf vegetables samples, a suction device based on laboratory (self-designed) Raman spectroscopy hardware and a GUI application software based on the LabVIEW development platform were developed. This system can test the Raman spectroscopy of the whole spinach including the automatic collection, display and storage of the Raman signal of all the scanned points by set up different scan step. A new method to remove the Raman spectrum background was proposed based on data replacement with linear equation at the range of threshold spectrum on both sides of the effective peaks according to the characteristics of spinach original spectra. Its principle is to determine the starting position of linear fitting by judging whether there is trough on both sides of the crest, and then to generate and replace the original spectra data in peak position through the linear fitting equation. Spinach samples were used for the experiment showed that the chlorophyll content and distribution of chlorpyrifos pesticide residue on each scanning point can be obtained after scanning. Therefore, the point scanning Raman system could improve detection accuracy of the quality and safety parameters for the non-uniform samples effectively.
|
|
Received: 2015-04-13
Accepted: 2015-08-25
|
|
|
|
Corresponding Authors:
LI Yong-yu
E-mail: yyli@cau.edu.cn
|
|
[1] WU Jian-fan, WANG Yun-hua(吴建繁，王运华). Chinese Bulletin of Botany(植物学通报), 2000, 17(6)： 482.
[2] Hu J Y, Zheng Z H, et al. Deng, Bull Environ. Contam Toxicol., 2011, 86(1): 95.
[3] Lavagnini I, Urbani A, Magno F, et al, Talanta, 2011, 83: 1754.
[4] Ortelli D, Edder P, Corvi C, et al. Food Additives and Contaminants, 2005, 22(5): 423.
[5] ZHU He, JI Ming-shan(朱 赫，纪明山). Chinese Agricultural Science Bulletin(中国农学通报), 2014, 30(4): 242.
[6] LI Xiao-ting, WANG Ji-hua, ZHU Da-zhou, et al(李晓婷，王纪华，朱大洲，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2011, 27(Supp.)： 363.
[7] FAN Yu-xia, LAI Ke-qiang, HUANG Yi-qun(樊玉霞，赖克强，黄轶群). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2014, 34(7): 1859.
[8] Li Y, Dhakal S, Peng Y. Journal of Food Engineering, 2012, 109: 127.
[9] Moros J, Armenta S, Garrigues S, et al. Analytica Chimica Acta, 2005, 543: 124.
[10] Dhakal S, Li Y, Peng Y, et al. Journal of Food Engineering, 2014, 123: 94.
[11] Sagar Dhakal, Li Yongyu, Peng Yankun, et al. International Agricultural Engineering Journal, 2013, 22(3): 62.
[12] Zhang P X，Zhou X F，Cheng A Y S，et al. Journal of Physics: Conference Series，2006，28: 7.
[13] Xie Y，Mukamurezi G，Sun Y，et al. European Food Research and Technology，2012，234(6): 1 091.
[14] Jianwei Q, Kuanglin C, Moon S K. Proc SPIE, 2011.
[15] WANG De-kai, PEI Ke-mei, LIU He-qin(汪得凯, 裴克梅, 刘合芹). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2008, 25(1): 1. |
| [1] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [2] |
WANG Fang-yuan1, 2, HAN Sen1, 2, YE Song1, 2, YIN Shan1, 2, LI Shu1, 2, WANG Xin-qiang1, 2*. A DFT Method to Study the Structure and Raman Spectra of Lignin
Monomer and Dimer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 76-81. |
| [3] |
XING Hai-bo1, ZHENG Bo-wen1, LI Xin-yue1, HUANG Bo-tao2, XIANG Xiao2, HU Xiao-jun1*. Colorimetric and SERS Dual-Channel Sensing Detection of Pyrene in
Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 95-102. |
| [4] |
WANG Xin-qiang1, 3, CHU Pei-zhu1, 3, XIONG Wei2, 4, YE Song1, 3, GAN Yong-ying1, 3, ZHANG Wen-tao1, 3, LI Shu1, 3, WANG Fang-yuan1, 3*. Study on Monomer Simulation of Cellulose Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 164-168. |
| [5] |
WANG Lan-hua1, 2, CHEN Yi-lin1*, FU Xue-hai1, JIAN Kuo3, YANG Tian-yu1, 2, ZHANG Bo1, 4, HONG Yong1, WANG Wen-feng1. Comparative Study on Maceral Composition and Raman Spectroscopy of Jet From Fushun City, Liaoning Province and Jimsar County, Xinjiang Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 292-300. |
| [6] |
LI Wei1, TAN Feng2*, ZHANG Wei1, GAO Lu-si3, LI Jin-shan4. Application of Improved Random Frog Algorithm in Fast Identification of Soybean Varieties[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3763-3769. |
| [7] |
WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2*. Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3770-3774. |
| [8] |
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. |
| [9] |
LU Wen-jing, FANG Ya-ping, LIN Tai-feng, WANG Hui-qin, ZHENG Da-wei, ZHANG Ping*. Rapid Identification of the Raman Phenotypes of Breast Cancer Cell
Derived Exosomes and the Relationship With Maternal Cells[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3840-3846. |
| [10] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [11] |
GUO He-yuanxi1, LI Li-jun1*, FENG Jun1, 2*, LIN Xin1, LI Rui1. A SERS-Aptsensor for Detection of Chloramphenicol Based on DNA Hybridization Indicator and Silver Nanorod Array Chip[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3445-3451. |
| [12] |
ZHU Hua-dong1, 2, 3, ZHANG Si-qi1, 2, 3, TANG Chun-jie1, 2, 3. Research and Application of On-Line Analysis of CO2 and H2S in Natural Gas Feed Gas by Laser Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3551-3558. |
| [13] |
LIU Jia-ru1, SHEN Gui-yun2, HE Jian-bin2, GUO Hong1*. Research on Materials and Technology of Pingyuan Princess Tomb of Liao Dynasty[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3469-3474. |
| [14] |
LI Wen-wen1, 2, LONG Chang-jiang1, 2, 4*, LI Shan-jun1, 2, 3, 4, CHEN Hong1, 2, 4. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in
Citrus Epidermis by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058. |
| [15] |
ZHAO Ling-yi1, 2, YANG Xi3, WEI Yi4, YANG Rui-qin1, 2*, ZHAO Qian4, ZHANG Hong-wen4, CAI Wei-ping4. SERS Detection and Efficient Identification of Heroin and Its Metabolites Based on Au/SiO2 Composite Nanosphere Array[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3150-3157. |
|
|
|
|
