اصالت‌سنجی و تشخیص تقلب مواد غذایی بر اساس تکنیک‌های انگشت‌نگاری و ابزارهای شیمی‌سنجی (مقاله مروری)

بهداشت مواد غذایی

مقاله 8، دوره 9، 3 (35) پاییز، آذر 1398، صفحه 89-112   

نوع مقاله: مقاله مروری

شناسه دیجیتال (DOI): 10.30495/jfh.2019.669289

نویسندگان

احسان سرلکی¹؛ محمد ابونجمی^{* 2}

¹دانشجوی دکتری مهندسی مکانیک بیوسیستم، گروه مهندسی فنی کشاورزی، پردیس ابوریحان، دانشگاه تهران

²دانشیار، گروه مهندسی فنی کشاورزی، پردیس ابوریحان، دانشگاه تهران

چکیده

اصالت‌سنجی یک مسئله مهم در کنترل کیفیت، بهداشت و ایمنی مواد غذایی است. شناسایی و تعیین تقلب‌ در مواد غذایی به‌منظور بررسی اجزای آن‌ها، کیفیت و صحت و اطمینان از ایمنی ماده غذایی و رضایت مصرف‌کنندگان نیاز به توسعه روش‌های تحلیلی نوین و مؤثر دارد. فنون انگشت‌نگاری شامل انگشت‌نگاری کروماتوگرافی، انگشت‌نگاری الکتروفورز، انگشت‌نگاری طیف‌سنجی و انگشت‌نگاری حسگرهای الکترونیکی هستند. در حال حاضر از میان این فنون، روش‌های کروماتوگرافی مایع (LC)، کروماتوگرافی گازی (GC)، طیف‌سنجی‌های مادون قرمز نزدیک (NIR) و مادون قرمز متوسط (MIR)، رامان (Raman)، تصویربرداری ابر طیفی (HSI) و رزونانس مغناطیسی هسته (NMR) به‌عنوان ابزارهای تحلیلی مرسوم موجود هستند و برای جلوگیری از تقلب مواد غذایی به‌کار گرفته می‌شوند. فنون NIR، MIR و Raman و هم‌چنین فنون انگشت‌نگاری حسگر-مبنا (بینی الکترونیکی (E-Nose)، زبان الکترونیکی (E-Tongue) و چشم الکترونیکی (E-Eye))، دارای مزایای بسیار مهمی از قبیل آنالیز سریع، پیشرفته و غیر-مخرب با هزینه‌های پایین هستند. انگشت‌نگاری مواد غذایی در ترکیب با ابزارهای شیمی‌سنجی یک تکنیک ارزشمند برای تشخیص تقلب و کنترل مواد غذایی به‌شمار می‌آید. در این مقاله مروری، انواع فنون انگشت‌نگاری مورداستفاده در شناسایی و تشخیص تقلب برای آنالیز اثرانگشت مواد غذایی موردبررسی قرار گرفته است و بر مزایا و معایب هر یک از فنون پرداخته شده و یافته‌های مقالات اخیر برای این فنون در حوزه اصالت‌سنجی مواد غذایی مورد بحث قرار گرفته است.

کلیدواژه‌ها

اثرانگشت مواد غذایی؛ اصالت‌سنجی؛ تقلب؛ روش‌های تحلیلی؛ شیمی‌سنجی

مراجع

• · Aboonajmi, M., Jahangiri, M. and Hassan‐Beygi, S.R. (2015). A Review on Application of Acoustic Analysis in Quality Evaluation of Agro‐food Products. Journal of food processing and preservation, 39 (6): 3175-3188.
• · Aboonajmi, M. and Najafabadi, T.A. (2014). Prediction of poultry egg freshness using Vis-NIR spectroscopy with maximum likelihood method, International journal of food properties, 17(10): 2166-2176.
• · Aboonajmi, M., Saberi, A., Najafabadi, T.A. and Kondo, N. (2016). Quality assessment of poultry egg based on visible–near infrared spectroscopy and radial basis function networks, International journal of food properties, 19(5): 1163-1172.
• · Aprea, E., Gika, H., Carlin, S., Theodoridis, G., Vrhovsek, U. and Mattivi, F. (2011). Metabolite profiling on apple volatile content based on solid phase microextraction and gas chromatography time of flight mass spectrometry. Journal of Chromatography A, 1218: 4517-4524.
• · Bahmani, L., Aboonajmi, M. and Arabhosseini, A. (2018). ANN modeling of extraction kinetics of essential oil from tarragon using ultrasound pre-treatment. Engineering in Agriculture, Environment and Food, 11(1): 25-29.
• · Bansal, S., Singh A., Mangal, M., Mangal, AK. and Kumar, S. (2015). Food adulteration: Sources, health risks, and detection methods. Critical Reviews in Food Science and Nutrition, 57(6):1174-1189.
• · Bing, Y., Luo, Y.B. and Huang, K.L. (2005). Application of near-infrared diffuse reflectance spectroscopy to the detection and identification of transgenic corn. Spectroscopy and Spectral Analysis, 25(10): 1580–1583.
• · Bosque-Sendra, J.M., Cuadros-Rodriguez, L., Ruiz-Samblas, C. and Mata, A.P. (2012). Combining chromatography and chemometrics for the characterization and authentication of fats and oils from triacylglycerol compositional data-a review. Analytica Chimica Acta, 724:1-11.
• · Bothwell, J.H. and Grifin, J.L. (2011). An introduction to biological nuclear magnetic resonance spectroscopy. Biological reviews of the Cambridge Philosophical Society, 86(2): 493–510.
• · Buratti, S., Malegori, C., Benedetti, S., Oliveri, P. and Giovanelli, G. (2018). E-nose, e-tongue and e-eye for edible olive oil characterization and shelf life assessment: A powerful data fusion approach. Talanta, 182: 131-141.
• · Chen, J., Lu, Y.H., Wei, D.Z. and Zhou, X.L. (2009). Establishment of a fingerprint of raspberries by LC. Chromatographia, 70: 981–985.
• · Chen, P., Harnly, J.M. and Lester, G.E. (2010). Flow injection mass spectral fingerprints demonstrate chemical differences in Rio red grapefruit with respect to year, harvest time, and conventional versus organic farming. Journal of Agricultural and Food Chemistry, 58(8): 4545–4553.
• · Chen, W., Zhang, D. and Zhang, B. (2006). Determination of lecithin in functional food by UV spectrophotometry. Journal of the Chinese Cereals and Oils Association, 21(3): 189–191.
• · Consonni, R., Cagliani, L.R., Stocchero, M. and Porretta, S. (2009). Triple concentrated tomato paste: Discrimination between Italian and Chinese products. Journal of Agricultural and Food Chemistry, 57(11): 4506–4513.
• · Cubero-Leon, E., Penalver, R. and Maquet, A. (2014). Review on metabolomics for food authentication. Food Research International, 60: 95–107.
• · Danezis, G.P., Tsagkaris, A. S., Camin, F., Brusic, V. and Georgiou, C.A. (2016). Food authentication: Techniques, trends & emerging approaches. TrAC Trends in Analytical Chemistry, 85: 123–132.
• · Dobson, G., Shepherd, T., Verrall, S.R., Conner, S., McNicol, J.W. and Ramsay, G. (2008). Phytochemical diversity in tubers of potato cultivars and landraces using a GC–MS metabolomics approach. Journal of Agricultural and Food Chemistry, 56(21): 10280–10291.
• · Dunn, W.B., Broadhurst, D.I., Atherton, H.J., Goodacre, R. and Griffin, J.L. (2011). Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chemical Society Reviews, 40(1): 387–426.
• · Ellis, D.I., Dunn, W.B., Griffin, J.L., Allwood, J.W. and Goodacre, R. (2007). Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics, 8: 1243–1266.
• · Ellis, D.I., Victoria, L.B., Warwick, B.D., Allwood, J.D., Alexander, P.G. and Goodacre, R. (2012). Fingerprinting food: Current technologies for the detection of food adulteration and contamination. Chemical Society Reviews, 41: 5706–5727.
• · Esslinger, S., Riedl, J. and Fauhl-Hassek, C. (2014). Potential and limitations of nontargeted fingerprinting for authentication of food in official control. Food Research International, 60: 189–204.
• · Esteki, M., Shahsavari, Z. and Simal-Gandara, J. (2018). Use of spectroscopic methods in combination with linear discriminant analysis for authentication of food products. Food Control, 91: 100-112.
• · Fei, D. and Mei, L. (2008). Determination of paraquat in vegetable by ion chromatography with UV detection. Environmental Pollution and Control, 30(6): 31–33.
• · Fu, X., Ying, Y. and Liu, Y. (2006). Detection of pear firmness using near infrared diffuse reflectance spectroscopy. Spectroscopy and Spectral Analysis, 26(6): 1038–1041.
• · Gallo, M. and Ferranti, P. (2016). The evolution of analytical chemistry methods in food omics. Journal of Chromatography A, 14(28): 3–15.
• · Gan, Z., Yang, Y., Li, J., Wen, X., Zhu, M., Jiang, Y. and Ni, Y. (2016). Using sensor and spectral analysis to classify botanical origin and determine adulteration of raw honey. Journal of Food Engineering, 178: 151-158.
• · Gil, M., Le Duarte, I.F., Godejohann, M., Braumann, U., Maraschin, M. and Spraul, M. (2003). Characterization of the aromatic composition of some liquid foods by nuclear magnetic resonance spectrometry and liquid chromatography with nuclear magnetic resonance and mass spectrometric detection. Analytica Chimica Acta, 488: 35–51.
• · Gomez-Ariza, J.L., Arias-Borrego, A. and Garcıa-Barrera, T. (2006). Multi-elemental fractionation in pine nuts (pinus pinea) from different geographic origins by size-exclusion chromatography with UV and inductively coupled mass spectrometry detection. Journal of Chromatography A, 1121: 191–199.
• · Guo, J., Yue, T. and Yuan, Y. (2012). Feature selection and recognition from nonspecific volatile profiles for discrimination of apple juices according to variety and geographical origin. Journal of Food Science, 77: 1090–1096.
• · Han, B., Jin, J. and Wu, Q.Y. (2009). High order derivative spectrophotograph determination of Sudan red in the samples containing lycopene. Chinese Journal of Pharmaceutical Analysis, 29(5): 710–713.
• · Hao, X., Hu, J.Z. and Zhong, H. (2007). Detection of Benzo Pyrene in meat food by high pressure liquid chromatography (HPLC). Food Science and Technology, 7: 219–221.
• · He, X.Q., Xu, D. and Luo, M. (2005). A microwave-assisted derivatization and GC-MS method coupled with calibration transformation matrix for determination of fatty acid in edible oils. Journal of Instrumental Analysis, 24(1): 25–28.
• · Herrero, A.M. (2008). Raman spectroscopy a promising technique for quality assessment of meat and fish: A review. Food Chemistry, 107(4): 1642–51.
• · Hu, Y.F. (2005). Study on the photometry of nitrites in meat products. Physical Testing and Chemical Analysis Part B: Chemical Analysis, 41(3): 188–189.
• · Huang, H., Yu, H., Xu, H. and Ying, Y. (2008). Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review. Journal of Food Engineering, 87(3): 303–13.
• · Huanga, L.F., Wu, M.J., Zhongb, K.J., Sunb, X.J., Liang, Y.Z., Dai, Y.H., et al. (2007). Fingerprint developing of coffee flavor by gas chromatography mass spectrometry and combined chemometrics methods. Analytica Chimica Acta, 588: 216–223.
• · Jiang, J.S., Zhao, B. and Zhou, L. (2009). Simultaneous determination of 36 pesticide residues in tea by GC-MS. Food Science, 30(14): 276-330.
• · Jin, Z.Q., Zhang, J.S. and Lin, X.Y. (2007). Study on water loss rate and decay of strawberry by NMR and MRI. Food Science, 28(8): 108-111.
• · Kim, H.J. and Jang, Y.P. (2009). Direct analysis of curcumin in turmeric by DART-MS. Phytochemical Analysis, 20: 372-377.
• · Kim, J., Jung, Y., Song, B., Bong, Y.S., Ryu, D.H. and Lee, K.S. (2013). Discrimination of cabbage (Brassica rapa ssp. pekinensis) cultivars grown in different geographical areas using 1H NMR-based metabolomics. Food Chemistry, 137(137): 68–75.
• · Kvasnicka, F. (2005). Capillary electrophoresis in food authenticity. Journal of Separation Science, 28: 813–825.
• · Leme, G.M., Coutinho, I.D., Creste, S., Hojo, O., Carneiro, R.L. and Bolzani, V. (2014). HPLC-DAD method to metabolic fingerprinting to the phenotyping of sugarcane genotypes. Analytical Methods, 6: 7781–7788.
• · Li, H.B., Wang, S. and Wang, H. (2008). Application of AFLP marker technology in the identification of greengrocery variety “Youdonger”. Journal of Anhui Agricultural Sciences, 36(1): 72–73.
• · Li, J., He, X., Li, M., Zhao, W., Liu, L. and Kong, X. (2015). Chemical fingerprint and quantitative analysis for quality control of polyphenols extracted from pomegranate peel by HPLC. Food Chemistry, 176: 7–11.
• · Lohumi, S., Lee, S., Lee, H. et al. (2015). A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends in Food Science and Technology, 46: 85–98.
• · Malheiro, R., Guedes de Pinho, P., Soares, S., Cesar da Silva Ferreira, A. and Baptista, P. (2013). Volatile biomarkers for wild mushrooms species discrimination. Food Research International, 54: 186–194.
• · Medina, S., Perestrelo, R., Silva, P., Pereira, J.A.M. and Camara, J.S. (2019). Current trends and recent advances on food authenticity technologies and chemometric approaches, Trends in Food Science & Technology, 85: 163-176.
• · Moore, J.C., Spink, J. and Lipp, M. (2012). Development and application of a database of food ingredient fraud and economically motivated adulteration from 1980 to 2010. Journal of Food Science, 77: 118–126.
• · Nicolaou, N., Xu, Y. and Goodacre, R. (2011). MALDI-MS and multivariate analysis for the detection and quantification of different milk species. Analytical and Bioanalytical Chemistry, 399(10): 3491–502.
• · Parastar, H., Jalali, H.M., Sereshti, H. and Varnosfaderani, A.M. (2012). Chromatographic fingerprint analysis of secondary metabolites in citrus fruits peels using gas chromatography-mass spectrometry combined with advanced chemometric methods. Journal of Chromatography A, 1251: 176–187.
• · Peng, Y., Liu, F. and Ye, J. (2006). Quantitative and qualitative analysis of flavonoid markers in Frucus aurantii of different geographical origin by capillary electrophoresis with electrochemical detection. Journal of Chromatography B, 830: 224–230.
• · Qin, J., Chao, K. and Kim, M.S. (2010). Raman chemical imaging system for food safety and quality inspection. Trans ASABE, 53(6): 1873–1882.
• · Reid, L.M., O’Donnell, C.P. and Downey, G. (2006). Recent technological advances for the determination of food authenticity. Trends Food Science Technology, 17: 344–53.
• · Salvatore, E., Bevilacqua, M., Bro, R., Marini, F. and Cocchi, M. (2013). Classification methods of multiway arrays as a basic tool for food PDO authentication. In Food Protected Designation of Origin: Methodologies and Applications. M. de la Guardia and A. Gonzalvez (Eds.). Elsevier, Amsterdam, pp: 339–382.
• · Sarbu, C., Nacu-Briciu, R.D., Kot-Wasik, A., Gorinstein, S., Wasik, A. and Namiesnik, J. (2012). Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data. Food Chemistry, 130: 994–1002.
• · She, Y.X., Liu, J.J. and Wang, J. (2008). Determination of 24 sulfonamides in milk by ultra-performance liquid chromatography combined with Quadrupole mass spectrometry. Journal of Instrumental Analysis, 27(12): 1313–1317.
• · Shen, D., Wu, Q., Sciarappa, W.J. and Simon, J.E. (2012). Chromatographic fingerprints and quantitative analysis of isoflavones in Tofu-type soybeans. Food Chemistry, 130: 1003–1009.
• · Tian, H., Zhan, P. and Zhang, H. (2014). Development of a fatty acid fingerprint of white apricot almond oil by gas chromatography and gas chromatography-mass spectrometry. European Journal of Lipid Science and Technology, 116: 126–133.
• · Tian, H.X., Wang, Z. and Xu, S.Y. (2006). Separation and identification of volatile flavors of Jinhua Ham by gas chromatography-mass spectrometry coupled with head space solid phase microextraction. Chinese Journal of Chromatography, 24(2): 177-180.
• · Vardin, H., Tay, A., Ozen, B. and Mauer, L. (2008). Authentication of pomegranate concentrate using FTIR spectroscopy and chemometrics. Food Chemistry, 108(2): 742–748.
• · Wang, N., Lin, X.Y. and Yuan, R.S. (2007). Study on navel orange storage processing with NMR. Food Science, 28(7): 83–87.
• · Wolfendera, J.L., Martia, G., Thomas, A. and Bertrand, S. (2015). Current approaches and challenges for the metabolite profiling of complex natural extracts. Journal of Chromatography A, 1382: 136–164.
• · Wu, J.H., Peng, Y.K. and Jiang, F. (2009). Hyperspectral scattering profiles for prediction of beef tenderness. Transactions of the Chinese Society for Agricultural Machinery, 40(12): 135–138.
• · Xu, Y., Cheung, W., Winder, C.L. and Goodacre, R. (2010). VOC-based metabolic profiling for food spoilage detection with the application to detecting Salmonella typhimurium contaminated pork. Analytical and Bioanalytical Chemistry, 397(6): 2439–2449.
• · Xu, Y., Cheung, W., Winder, W.L., Dunn, W.B. and Goodacre, R. (2011). Metabolic profiling of meat: assessment of pork hygiene and contamination with Salmonella typhimurium. Analyst, 136: 508–514.
• · Yang, W., Tian, S. and Dong, W. (2007). Determination of total sugar in honey by ultraviolet spectrophotometry. Chinese Journal of Spectroscopy Laboratory, 24(4): 739–742.
• · Yuan, H., Fu, H. and Rao, P.F. (2005). Analysis of trans fatty acids by infrared spectroscopy and gas chromatography. Journal of Cereals & Oils, 24(1): 25–28.
• · Zhan, J., Yu, X.J. and Huang, W. (2008). A simple method for the simultaneous determination of 7 food additives in foods with complex matrices by GC/MS. Journal of Food and Drug Analysis, 24(6): 729–731.
• · Zhang, J., Zhang, X., Dediu, L. and Victor, C. (2011). Review of the current application of fingerprinting allowing detection of food adulteration and fraud in China. Food Control, 22: 1126–35.
• · Zhang, N., Zhang, D. and Li, S. (2008). Preliminary study on origin traceability of mutton by near infrared reflectance spectroscopy coupled with SIMCA method. Transactions of the Chinese Society of Agricultural Engineering, 24(12): 309–312.
• · Zhao, J., Zhai, J. and Liu, M. (2006). The determination of beef tenderness using near infrared spectroscopy. Spectroscopy and Spectral Analysis, 26(4): 640–642.
• · Zhong, W., Chen, D. and Yong, W. (2005). Determination of acrylamide in fried starchy foods by gas chromatography-mass spectrometry. Chinese Journal of Chromatography, 23(3): 312–314.
• · Zhou, M., McDonald, J.F. and Fernandez, F.M. (2010). Optimization of a direct analysis in real time/time-of-flight mass spectrometry method for rapid serum metabolomic fingerprinting. Journal of the American Society for Mass Spectrometry, 21: 68–75.