Review on the Application of Spectroscopy Technology in Food Detection
LI Xin-xing1, 2, ZHANG Ying-gang1, MA Dian-kun1, TIAN Jian-jun3, ZHANG Bao-jun3, CHEN Jing4*
1. Beijing Laboratory of Food Quality and Safety, College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. Energy and Environment Engineering Institute, Nanchang Institute of Technology, Nanchang 330044, China
3. College of Food Science and Engineering, Inner Mongolia Agricultural University, Huhhot 010018, China
4. School of Logistics, Beijing Wuzi University, Beijing 101149, China
Abstract：With the progress of society, people's dietary requirements are constantly improving, which is gradually changed from the previous “eat full” to today's “eat well”. People are paying more attention to food safety. Therefore, fast and non-destructive food detection technology is needed to meet the imminent demand for food safety. Spectral technology can calculate the material characteristics and composition of food samples according to their physical structure and chemical composition. It has a broad application prospect in adulteration detection, freshness detection, and residue detection of harmful substances. Compared with the traditional detection technology in food detection, spectral technology has the advantages of rapid, high precision, no sample loss, and good repeatability, and it has become an important development direction in food detection. In this paper, related domestic and international literature on spectral techniques applied to food detection in the last five years is discussed, focusing on data pretreatment method, characteristic band selection algorithm and data modeling method to systematically review the application and progress of spectral technology in food detection. In this paper, the application of spectral technology in food detection is discussed, including the preprocessing of spectral data by multiplicative scatter correction (MSC), standard normal variate transform (SNV), and Savitzky-Golay smoothing (SG) algorithm; successive projections algorithm (SPA), principal component analysis (PCA), and competitive adaptive reweighted sampling (CARS) were used to select characteristic bands; partial least squares (PLS), support vector machine (SVM), and artificial neural network (ANN) were used to analyze collected data. Simultaneously, this paper summarizes the prospects for the application of spectral technology in food detection: the integration of spectral detection technology and a variety of food detection technology will become a new development direction in the future; combining spectral detection technology with on-line detection technology to realize on-line and real-time detection of food samples will obtain more valuable detection results; the development of portable spectral detection equipment will be more convenient for on-site food detection, and this equipment will significantly improve the efficiency of food detection and has excellent market potential.
Key words：Spectroscopy; Food detection; Spectral data processing; Prediction model
[1] Nicola M, Alsafi Z, Sohrabi C, et al. International Journal of Surgery, 2020, 78: 185.
[2] HU Guang-hui, LIU Wei-li, QIAN Chong, et al(胡光辉，刘伟丽，钱 冲，等). Food Safety and Quality Detection Technology(食品安全质量检测学报), 2016, 7(11): 4312.
[3] LI Hao-lin, LIU Jing, YANG Jue-ping, et al(李浩林，刘 箐，杨珏萍，等). Food and Fermentation Industries(食品与发酵工业), 2013, 39(6): 163.
[4] XIE Gui-fang, SU Ben-chao, XIE Xiao-xia, et al(谢桂芳，苏本超，谢晓霞，等). Journal of Instrumental Analysis(分析测试学报), 2021, 40(5): 648.
[5] SUN Da-wen, WU Di, HE Hong-ju, et al(孙大文，吴 迪，何鸿举，等). Journal of South China University of Technology(Natural Science Edition)[华南理工大学学报（自然科学版）], 2012, 40(10): 59.
[6] Geladi P, MacDougall D, Martens H. Applied Spectroscopy, 1985, 39(3): 491.
[7] FANG Yao, XIE Tian-hua, GUO Wei, et al(方 瑶，谢天铧，郭 渭，等). Jiangsu Journal of Agricultural Sciences(江苏农业学报), 2021, 37(1): 213.
[8] Luna A S, Da Silva A P, Da Silva C S, et al. Journal of Food Composition and Analysis, 2019, 76: 44.
[9] ZHAO Qiang, ZHANG Gong-li, CHEN Xing-dan(赵 强，张工力，陈星旦). Optics and Precision Engineering(光学精密工程), 2005，13(1): 53.
[10] Barnes R J, Dhanoa M S, Lister S J. Applied Spectroscopy, 1989, 43(5): 772.
[11] Fearn T, Riccioli C, Garrido-Varo A, et al. Chemometrics and Intelligent Laboratory Systems, 2009, 96(1): 22.
[12] Santos I A, Conceição D G, Viana M B, et al. Food Chemistry, 2021, 349: 129095.
[13] TIAN Xiao-yu, HUANG Xing-yi, BAI Jun-wen, et al(田潇瑜，黄星奕，白竣文，等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2019, 50(2): 350.
[14] ZHANG Zhe, WANG Xiao-xia, CHEN Jia-nan, et al(张 哲，王晓霞，陈佳楠，等). Food Research and Development(食品研究与开发), 2021, 42(23): 137.
[15] Yang J, Wang J, Lu G, et al. Computers and Electronics in Agriculture, 2021, 190: 106431.
[16] Nallan Chakravartula S S, Moscetti R, Bedini G, et al. Food Control, 2022, 135: 108816.
[17] Saad A, Azam M M, Amer B M A. Food Analytical Methods, 2022, 15(3): 689.
[18] Savitzky A, Golay M J E. Analytical Chemistry (Washington), 1964, 36(8): 1627.
[19] Li C, Zong B, Guo H, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2020, 227: 117697.
[20] Guo W, Li W, Yang B, et al. Journal of Food Engineering, 2019, 257: 109955.
[21] Cui L, Wang X, Xu Y, et al. Journal of Consumer Protection and Food Safety, 2022, 17(1): 51.
[22] BAI Jing, LI Jia-peng, ZOU Hao, et al(白 京，李家鹏，邹 昊，等). Food Science(食品科学), 2019, 40(2): 287.
[23] Araújo M C U, Saldanha T C B, Galvão R K H, et al. Chemometrics and Intelligent Laboratory Systems, 2001, 57(2): 65.
[24] Wang Q, He Y. Applied Sciences, 2019, 9(5): 822.
[25] Gao Q, Wang M, Guo Y, et al. IEEE Access, 2019, 7: 128064.
[26] Yang B, Gao Y, Li H, et al. PLOS ONE, 2019, 14(2): e210084.
[27] Sun X, Liu J, Sun J, et al. Journal of Food Process Engineering, 2021, 44(11): e13864.
[28] Pearson K. Philosophical Magazine, 1901, 2(11): 559.
[29] Teklemariam T A, Moisey J, Gotera J. Food Chemistry, 2021, 355: 129616.
[30] Amirvaresi A, Nikounezhad N, Amirahmadi M, et al. Food Chemistry, 2021, 344: 128647.
[31] Feng L, Zhu S, Zhang C, et al. Molecules, 2018, 23(11): 2907.
[32] Tang N, Sun J, Yao K, et al. Journal of Food Process Engineering, 2021, 44(1): e13603.
[33] Xing Z, Du C, Shen Y, et al. Computers and Electronics in Agriculture, 2021, 191: 106549.
[34] Guo Z, Wang M, Agyekum A A, et al. Journal of Food Engineering, 2020, 279: 109955.
[35] Ren G, Liu Y, Ning J, et al. Journal of Food Composition and Analysis, 2021, 98: 103810.
[36] Li Y, Yin Y, Yu H, et al. Journal of Food Measurement and Characterization, 2022, 16(1): 76.
[37] Liu Y, Wang Q, Xu Q, et al. Journal of Food Measurement and Characterization, 2018, 12(4): 2809.
[38] Yang L, Wu T, Liu Y, et al. Journal of Spectroscopy, 2018, 2018: 1.
[39] Khamsopha D, Woranitta S, Teerachaichayut S. Food Control, 2021, 123: 107781.
[40] Taylan O, Cebi N, Tahsin Yilmaz M, et al. Food Chemistry, 2020, 332: 127344.
[41] Zheng X, Li Y, Wei W, et al. Meat Science, 2019, 149: 55.
[42] Leng T, Li F, Chen Y, et al. Meat Science, 2021, 180: 108559.
[43] Liu Y, Li Y, Peng Y, et al. Journal of Food Science, 2020, 85(9): 2773.
[44] Shi J, Wang Y, Liu C, et al. Food Chemistry: X, 2021, 11: 100128.
[45] Dai Q, Cheng J, Sun D, et al. Food Chemistry, 2016, 197: 257.
[46] Yang X, Li G, Song J, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018, 205: 457.
[47] Dashti A, Muller-Maatsch J, Weesepoel Y, et al. Foods, 2021, 11(1): 71.
[48] Amsaraj R, Ambade N D, Mutturi S. International Dairy Journal, 2021, 123: 105172.
[49] Zhao H, Feng Y, Chen W, et al. Meat Science, 2019, 151: 75.
[50] Zareef M, Chen Q, Hassan M M, et al. Food Engineering Reviews, 2020, 12(2): 173.
[51] SHAO Yuan-yuan, WANG Yong-xian, XUAN Guan-tao, et al(邵园园，王永贤，玄冠涛，等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2020, 51(8): 344.
[52] Puertas G, Vázquez M. Journal of Food Composition and Analysis, 2020, 86: 103350.
[53] Wang H, Wang K, Wang B, et al. Journal of Food Quality, 2018, 2018: 1.
[54] Yan H, Li P, Zhou G, et al. Food Chemistry, 2021, 341: 128241.
