|
|
|
|
|
|
| Efficient Saponification and Separation of Unsaponifiables for Authentication of Sesame Oil Using FT-IR Spectroscopy and Chemometrics |
| HE Wen-xuan*, LIN Qi |
| Department of Materials and Engineering, Engineering and Reaearch Center of New Chinese Lacquer Materials，Minjiang University, Fuzhou 350108, China |
|
|
|
|
Abstract Sesame oil is one of the essential cooking oil, and it has been consumed in daily life. The intake of adulterated sesame oil leads to severe health problems. Thus the method to identify adulteration is significant research. Saponification is one of the simple and inexpensive processes have been used to identify the adulteration in edible oil. The saponification takes a long time, higher temperature and the isolation of unsaponifiable from saponifiable is tedious. In the present research, the enriched saponification process has been developed using ultrasonication technique instead of a common conventional method. The process has been significantly reduced to ten minutes. The special solid phase extraction (SPE) cartridge has been designed and prepared to separate the unsaponifiable. The combined FT-IR with chemometrics based on the isolated unsaponifiable was first used to authenticate sesame oil. The partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) was employed to establish the models to identify the adulteration detection and authentication of sesame oil. The results indicated that the OPLS-DA is better than PLS-DA, which was chosen for the authentication of sesame oil. The prediction of samples was accurate by the constructed model. The results suggested that the combined FT-IR spectroscopy with chemometrics based on isolated unsaponifiable could be used for authentication of sesame oil.
|
|
Received: 2019-12-14
Accepted: 2020-04-26
|
|
|
|
Corresponding Authors:
HE Wen-xuan
E-mail: 706828346@qq.com
|
|
[1] Bedigian D. Econ. Bo., 2004, 58: 329.
[2] Anilakumar K R, Pal A, Khanum F, et al. Agric. Conspec. Sci.，2010, 75：159.
[3] Faostat, 2017, Crops/World Regions/Production Quantity from Pick Lists. UN Food and Agriculture Organization Corporate Statistical Database Retrieved 9 September 2018.
[4] Ruslan K, Happyniar S, Fidrianny I. J. Taibah. Univ. Sci., 2018, 13: 211.
[5] Lin X, Zhou L, Li T, et al. RSC. Adv., 2017, 7: 5751.
[6] Nigam D, Singh C, Tiwari U. J. Pharmacogn. Phytochem., 2015, 3: 88.
[7] Zhao X, Dong D, Zheng W, et al. Food Anal. Method, 2015, 8: 2308.
[8] Rizki H, Terouzi W, Kzaiber F, et al. J. Environ. Sci. Toxicol. Food Technol., 2016, 10: 138.
[9] Fadzlillah N A, Che Man Y B, Rohman A. Int. J. Food Prop., 2014, 17: 1275.
[10] Chen H, Lin Z, Tan C. Vib. Spectrosc., 2018, 99: 178.
[11] Zhang Q, Zhang L, Huang X, et al. Chemometr Intell Lab，2017, 161：147.
[12] Peng D, Bi Y, Ren X, et al. Food Chem.，2015, 188：415.
[13] Yadav S. Int. J. Chem. Stud.，2018, 6：1393.
[14] Hong E, Lee S Y, Jeong J Y, et al. J. Sci. Food Agric.，2017, 97：3877.
[15] Zhu W, Wang X, Chen L. Food Chem., 2017, 216: 268.
[16] Jabeur H, Zribi A, Bouaziz M. Food. Anal. Method, 2016, 9: 712.
[17] Zhang L, Li P, Sun X, et al. J. Agr. Food Chem.，2014, 62：8745.
[18] García M J L. Springer Heidelberg, New York Dordrecht London, 2012.
[19] Huang R, Li Y, He X, et al. Spectroscopy and Spectral Analysis，2020, 40(6)：1852.
[20] Medina V S, Capote P F, Castro M D L. Eur. J. Lipid. Sci. Technol., 2013, 115: 1325.
[21] Obana H, Okihashi M, Akutsu K, et al. Shokuhin Eiseigaku Zasshi，2001, 42：148.
[22] Al-asheh S, Banat F, Al-lagtah N. Chem. Eng. Res. Des., 2004, 82：855. |
| [1] |
ZHAO Wen-hua1, 2, HAN Xiang-na1*, YE Lin2, BAI Jiu-jiang2. Accurate Identification of Common Soluble Salts in Cultural Relics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3826-3831. |
| [2] |
WU Shan, ZHANG Ming-zhe, YU Hui-zhen, CHEN Zhe, YIN Wen-xiu, ZHANG Quan, SHEN Xu-fang, SUN Chao, QIU Hui, SHUAI Jiang-bing, ZHANG Xiao-feng*. Ivory Identification Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2397-2406. |
| [3] |
DENG Xiao-jun1, 2, MA Jin-ge1, YANG Qiao-ling3, SHI Yi-yin1, HUO Yi-hui1, GU Shu-qing1, GUO De-hua1, DING Tao4, YU Yong-ai5, ZHANG Feng6. Visualized Fast Identification Method of Imported Olive Oil Quality Grade Based on Raman-UV-Visible Fusion Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1117-1125. |
| [4] |
LIU Xin-yu1, SHAO Wen-wu2*, ZHOU Shi-rui3. Spectral Pattern Recognition of Cardiac Tissue in Electric Shock Death and Post-Mortem Electric Shock[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1126-1133. |
| [5] |
ZHANG Li-qian1, 2, LIU Yang-jie2, 3, LIN Bing-lan2, DUAN Jun1. Comparative Study on Mineralogical Identification and Spectral
Characteristics of Halloysitum Album, a Commercial Mineral
Medicine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 897-902. |
| [6] |
LIU Feng-xiang, HE Shuai, ZHANG Li-hao, HUANG Xia, SONG Yi-zhi*. Application of Raman Spectroscopy in Detection of Pathogenic Microorganisms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3653-3658. |
| [7] |
OUYANG Ai-guo, YU Bin, HU Jun, LIN Tong-zheng, LIU Yan-de. Grade Evaluation of Grain Size in High-Speed Railway Wheel Steel Based on Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3428-3434. |
| [8] |
ZHU Gui-jun, WANG Gan-zhen, PENG Jun*, TIAN Zong-ping, HOU Zhi-hua. The Mineralogical and Spectroscopic Characteristics of Phosphohedyphane From Chenzhou of Hunan Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3017-3023. |
| [9] |
ZHANG Li-qian1, 2, LIU Yang-jie2, 3. Comparative Study on Mineralogical Identification and Spectral
Characteristics of Four Iron-Containing Mineral Medicines[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2884-2889. |
| [10] |
ZHANG Fu1, 2, 3, CUI Xia-hua1, DING Ke4*, ZHANG Ya-kun1, WANG Yong-xian1, PAN Xiao-qing5. Study on the Influence of Different Pretreatment Methods on Gender Determination of Multiposition[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 434-439. |
| [11] |
RUAN Zhen1, ZHU Peng-fei3, ZHANG Lei3, CHEN Rong-ze3, LI Xun-rong3, FU Xiao-ting3, HUANG Zheng-gu4, ZHOU Gang4, JI Yue-tong5, LIAO Pu1, 2*. Study on Identification of Non-Tuberculosis Mycobacteria Based on Single-Cell Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(11): 3468-3473. |
| [12] |
YUAN Rui-rui, LIU Gui-shan*, HE Jian-guo, KANG Ning-bo, BAN Jing-jing, MA Li-min. Quantitative Damage Identification of Lingwu Long Jujube Based on Visible Near-Infrared Hyperspectral Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(04): 1182-1187. |
| [13] |
CUI Yao-yao1, KONG De-ming2, 3*, KONG Ling-fu1, WANG Shu-tao2, SHI Hui-chao4. An Oil Identification Method Based on Reconstructed 3D Fluorescence Spectra Combined With Partial Least Squares Discriminant Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3789-3794. |
| [14] |
LU Xian-yong1, HE Wen-xuan2, 3*, CHEN Hao-cong2, HUANG Rui2, ZHANG Yan-jie2. Identification Model of Camellia Oil Based on 3D Fluorescence Spectra of Vegetable Oils[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3854-3859. |
| [15] |
JIA Fu-dong1, 2, ZHANG Chang-qing1*, HUA Zhi-xin3, LOU De-bo1, LI Bao-long1, SUN Jia1. Identification Characteristics, Composition and Genesis of Euclase in Mahuaping Tungsten-Beryllium Polymetallic Deposit in Yunnan Province, Southwest China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(10): 3185-3192. |
|
|
|
|
