Metabolomics as an Emerging Technology for Molecular Authentication of Organic Food Products
Main Article Content
Abstract
Nowadays, the popularity of organic agricultural and food products has increased towards trends in healthy food consumption and environmental concerns. At present, organic products are generally sold for much higher values than conventional products and are an attractive target for food fraud malpractices. Therefore, analytical methods for verifying the quality and authenticity of organic products are widely in demand. Metabolomics is recognized as an effective tool for investigating the overall metabolite profile or metabolome of complex biological systems including food matrices. Current studies attempting to assess differences in the metabolite profile of organic and conventional agricultural and food products using various high-throughput analytical platforms in combination with chemometric analysis have been progressively documented. Therefore, this review aims to provide an overview of the studies in which metabolomics approach has been applied for molecular authentication and discrimination between organic and conventional products. The organic food metabolome databases should be further extended and validated in order to apply for organic food authentication and traceability in the future.
Article Details
Copyrights of all articles in the Journal of Food Technology available in print or online are owned by Siam University and protected by law.
References
Commission on Thai Organic Agriculture. (2017). The strategies for development of Thai organic agriculture (2017-2021). Office of Agricultural Economics, Ministry of Agriculture and Cooperatives. [Online] Avaliable from http://planning.dld.go.th/th/images/stories/section-5/2560/strategy11.pdf [Accessed August 12, 2020] (in Thai).
National Bureau of Agricultural Commodity and Food Standards. (2009). TAS 9000 PART 1-2009, Organic agriculture part 1: The production, processing, labelling and marketing of produce and products from organic agriculture. Ministry of Agriculture and Cooperatives. [Online] Available from https://www.acfs.go.th/files/files/commodity-standard/20190607104352_589820.pdf [Accessed August 12, 2020] (in Thai).
Vallverdú-Queralt, A. and Lamuela-Raventós, R.M. (2016). Foodomics: A new tool to differentiate between organic and conventional foods. Electrophoresis. 37(13): 1784-1794.
Wishart, D.S. (2008). Metabolomics: applications to food science and nutrition research. Trends in Food Science & Technology. 19(9): 482-493.
Settachaimogkon, S. and Luangwilai, M. (2017). Application of metabolomics technology for investigation of biomolecular profile of milk and dairy products. Journal of Food Technology, Siam University. 12(1): 1-16. (in Thai).
IFOAM. (2008). Principles of organic agriculture. nternational Federation of Organic Agriculture Movements. [Online] Available from https://www.ifoam.bio/why-organic/organic-landmarks/definition-organic [Accessed August 12, 2020].
National Bureau of Agricultural Commodity and Food Standards. (2020). Voluntary organic agriculture standards. [Online] Available from https://www.acfs.go.th/#/standard-commodity/general [Accessed August 12, 2020] (in Thai).
Office of Agricultural Economics. (2019). Annual report of the office of agricultural economics 2019. Ministry of Agriculture and Cooperatives. [Online] Available from http://www.oae.go.th/view/1/เอกสารเผยแพร่/TH-TH [Accessed August 12, 2020] (in Thai).
Paoletti, F. (2015). Chemical composition of organic food products. In: P.C.K. Cheung and B.M. Mehta, (eds.), Handbook of Food Chemistry. Springer, Berlin. 555-584.
Popa, M.E., Mitelut, A.C., Popa, E.E., Stan, A., and Popa, V.I. (2019). Organic foods contribution to nutritional quality and value. Trends in Food Science and Technology. 84: 15-18.
Capuano, E., Boerrigter-Eenling, R., van der Veer, G., and van Ruth, S.M. (2013). Analytical authentication of organic products: An overview of markers. Journal of the Science of Food and Agriculture. 93(1): 12-28.
Zheng, Y., Yu, X., Yang, H., and Wang, S. (2019). From a perspective of nutrition: Importance of organic foods over conventional counterparts. In: D. Biswas and S.A. Micallef, (eds.), Safety and Practice for Organic Food. Elsevier Academic Press, London. 75-134.
Gomiero, T. (2018). Food quality assessment in organic vs. conventional agricultural produce: Findings and issues. Applied Soil Ecology. 123: 714-728.
Mditshwa, A., Magwaza, L.S., Tesfay, S.Z., and Mbili, N. (2017). Postharvest quality and composition of organically and conventionally produced fruits: A review. Scientia Horticulturae. 216: 148-159.
Li, S., Tian, Y., Jiang, P., Lin, Y., Liu, X., and Yang, H. (2020). Recent advances in the application of metabolomics for food safety control and food quality analyses. Critical Reviews in Food Science and Nutrition. in press.
Castro-Puyana, M., Pérez-Míguez, R., Montero, L., and Herrero, M. (2017). Application of mass spectrometry-based metabolomics approaches for food safety, quality and traceability. TrAC - Trends in Analytical Chemistry. 93: 102-118.
Kim, S., Kim, J., Yun, E.J., and Kim, K.H. (2016). Food metabolomics: From farm to human. Current Opinion in Biotechnology. 37: 16-23.
Marcum, J.A. (2020). Nutrigenetics/nutrigenomics, personalized nutrition, and precision healthcare. Current Nutrition Reports. in press.
Medina-Franco, J.L., Naveja, J.J., and Rico-Hidalgo, M.P. (2018). Analysis of a large food chemical database: Chemical space, diversity, and complexity. F1000Research. 7: Article No. 993.
Goldansaz, S.A., Guo, A.C., Sajed, T., Steele, M.A., Plastow, G.S., and Wishart, D.S. (2017). Livestock metabolomics and the livestock metabolome: A systematic review. PLoS ONE. 12(5): Article No. e0177675.
Foroutan, A., Guo, A.C., Vazquez-Fresno, R., Lipfert, M., Zhang, L., Zheng, J., Badran, H., Budinski, Z., Mandal, R., Ametaj, B.N., and Wishart, D.S. (2019). Chemical composition of commercial cow's milk. Journal of Agricultural and Food Chemistry. 67(17): 4897-4914.
Settachaimongkon, S. and Kuntaveesuk, A. (2018). Kefir: Biotechnology from “~omics” perspectives. Journal of Food Technology, Siam University. 13(1): 1-18. (in Thai).
Kongboonkird, M. (2019). Comparison of biomolecular profiles between organic and conventional bovine milk using metabolomics technology. Master’s thesis, Chulalongkorn University. Thailand, (in Thai). [Online] Available from http://cuir.car.chula.ac.th/handle/123456789/65002. [Accessed August 12, 2020]
Karlund, A., Hanhineva, K., Lehtonen, M., Karjalainen, R.O., and Sandell, M. (2015). Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally. Journal of Agricultural and Food Chemistry. 63(3): 1010-1019.
Bonte, A., Neuweger, H., Goesmann, A., Thonar, C., Mäder, P., Langenkämper, G., and Niehaus, K. (2014). Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems. Journal of the Science of Food and Agriculture. 94(13): 2605-2612.
Rohlig, R.M. and Engel, K.H. (2010). Influence of the input system (conventional vs. organic farming) on metabolite profiles of maize (Zea mays) kernels. Journal of Agricultural and Food Chemistry. 58(5): 3022-3030.
Zörb, C., Langenkämper, G., Betsche, T., Niehaus, K., and Barsch, A. (2006). Metabolite profiling of wheat grains (Triticum aestivum L.) from organic and conventional agriculture. Journal of Agricultural and Food Chemistry. 54(21): 8301-8306.
Kessler, N., Bonte, A., Albaum, S.P., Mäder, P., Messmer, M., Goesmann, A., Niehaus, K., Langenkämper, G., and Nattkemper, T.W. (2015). Learning to classify organic and conventional wheat - A machine learning driven approach using the MeltDB 2.0 metabolomics analysis platform. Frontiers in Bioengineering and Biotechnology. 3: Article No. 35.
Xiao, R., Ma, Y., Zhang, D., and Qian, L. (2018). Discrimination of conventional and organic rice using untargeted LC-MS-based metabolomics. Journal of Cereal Science. 82: 73-81.
Xiao, R., Li, L., and Ma, Y. (2019). A label-free proteomic approach differentiates between conventional and organic rice. Journal of Food Composition and Analysis. 80: 51-61.
Cubero-Leon, E., De Rudder, O., and Maquet, A. (2018). Metabolomics for organic food authentication: Results from a long-term field study in carrots. Food Chemistry. 239: 760-770.
Cuevas, F.J., Pereira-Caro, G., Moreno-Rojas, J.M., Muñoz-Redondo, J.M., and Ruiz-Moreno, M.J. (2017). Assessment of premium organic orange juices authenticity using HPLC-HR-MS and HS-SPME-GC-MS combining data fusion and chemometrics. Food Control. 82: 203-211.
Cuevas, F.J., Moreno-Rojas, J.M., Arroyo, F., Daza, A., and Ruiz-Moreno, M.J. (2016). Effect of management (organic vs conventional) on volatile profiles of six plum cultivars (Prunus salicina Lindl.). A chemometric approach for varietal classification and determination of potential markers. Food Chemistry. 199: 479-484.
Consonni, R., Polla, D., and Cagliani, L.R. (2018). Organic and conventional coffee differentiation by NMR spectroscopy. Food Control. 94: 284-288.
Consonni, R., Bernareggi, F., and Cagliani, L.R. (2019). NMR-based metabolomic approach to differentiate organic and conventional Italian honey. Food Control. 98: 133-140.
National Bureau of Agricultural Commodity and Food Standards. (2018). TAS 9000 PART 2-2018, Organic agriculture part 2 : Organic livestock. Ministry of Agriculture and Cooperatives. [Online] Available from https://www.acfs.go.th/files/files/commodity-standard/20190625122638_657298.pdf [Accessed August 12, 2020] (in Thai).
Tomazin, U., Batorek-Lukac, N., Skrlep, M., Prevolnik-Povse, M., and Candek-Potokar, M. (2019). Meat and fat quality of krškopolje pigs reared in conventional and organic production systems. Animal. 13(5): 1103-1110.
Skrlep, M., Candek-Potokar, M., Atorek-Lukac, N.B., Tomazin, U., and Flores, M. (2019). Aromatic profile, physicochemical and sensory traits of dry-fermented sausages produced without nitrites using pork from krškopolje pig reared in organic and conventional husbandry. Animals. 9: Article No. 55.
Zhao, Y., Tu, T., Tang, X., Zhao, S., Qie, M., Chen, A., and Yang, S. (2020). Authentication of organic pork and identification of geographical origins of pork in four regions of China by combined analysis of stable isotopes and multi-elements. Meat Science. 165: Article No. 108129.
Ostermeyer, U., Molkentin, J., Lehmann, I., Rehbein, H., and Walte, H.G. (2014). Suitability of instrumental analysis for the discrimination between wild-caught and conventionally and organically farmed shrimps. European Food Research and Technology. 239(6): 1015-1029.
Molkentin, J., Lehmann, I., Ostermeyer, U., and Rehbein, H. (2015). Traceability of organic fish - Authenticating the production origin of salmonids by chemical and isotopic analyses. Food Control. 53: 55-66.
Ackermann, S.M., Lachenmeier, D.W., Kuballa, T., Schütz, B., Spraul, M., and Bunzel, M. (2019). NMR-based differentiation of conventionally from organically produced chicken eggs in Germany. Magnetic Resonance in Chemistry. 57(9): 579-588.
Mierlita, D. (2020). Fatty acid profile and oxidative stability of egg yolks from hens under different production systems. South African Journal of Animal Sciences. 50(2): 196-206.
Mugnai, C., Sossidou, E.N., Dal Bosco, A., Ruggeri, S., Mattioli, S., and Castellini, C. (2014). The effects of husbandry system on the grass intake and egg nutritive characteristics of laying hens. Journal of the Science of Food and Agriculture. 94(3): 459-467.
Bergamaschi, M., Cipolat-Gotet, C., Cecchinato, A., Schiavon, S., and Bittante, G. (2020). Chemometric authentication of farming systems of origin of food (milk and ripened cheese) using infrared spectra, fatty acid profiles, flavor fingerprints, and sensory descriptions. Food Chemistry. 305: Artcle No. 125480.
Chung, I.M., Kim, J.K., Yarnes, C.T., An, Y.J., Kwon, C., Kim, S.Y., Yang, Y.J., Chi, H.Y., and Kim, S.H. (2019). Fatty acid- and amino acid-specific isotope analysis for accurate authentication and traceability in organic milk. Journal of Agricultural and Food Chemistry. 67(2): 711-722.
Capuano, E., Van Der Veer, G., Boerrigter-Eenling, R., Elgersma, A., Rademaker, J., Sterian, A., and Van Ruth, S.M. (2014). Verification of fresh grass feeding, pasture grazing and organic farming by cows farm milk fatty acid profile. Food Chemistry. 164: 234-241.
Liu, N., Pustjens, A.M., Erasmus, S.W., Yang, Y., Hettinga, K., and van Ruth, S.M. (2020). Dairy farming system markers: The correlation of forage and milk fatty acid profiles from organic, pasture and conventional systems in the Netherlands. Food Chemistry. 314: Article No. 126153.
Kongboonkird, M., Duangmal, K., Chantaprasan, N., and Settachaimongkon, S. (2018). Molecular authentication of pasteurized organic milk products in Thailand using 1H-NMR-based metabolomics approach. In Proceedings of the 30th Annual Meeting of the Thai Society for Biotechnology and International Conference (TSB2018), CSB-P-03-1-11. November 22-23, 2018. Bangkok, Thailand.
Mie, A., Laursen, K.H., Aberg, K.M., Forshed, J., Lindahl, A., Thorup-Kristensen, K., Olsson, M., Knuthsen, P., Larsen, E.H., and Husted, S. (2014). Discrimination of conventional and organic white cabbage from a long-term field trial study using untargeted LC-MS-based metabolomics. Analytical and Bioanalytical Chemistry. 406(12): 2885-2897.
Maione, C., De Paula, E.S., Gallimberti, M., Batista, B.L., Campiglia, A.D., Barbosa, F., Jr., and Barbosa, R.M. (2016). Comparative study of data mining techniques for the authentication of organic grape juice based on ICP-MS analysis. Expert Systems with Applications. 49: 60-73.
Pacifico, D., Casciani, L., Ritota, M., Mandolino, G., Onofri, C., Moschella, A., Parisi, B., Cafiero, C., and Valentini, M. (2013). NMR-based metabolomics for organic farming traceability of early potatoes. Journal of Agricultural and Food Chemistry. 61(46): 11201-11211.
Hohmann, M., Christoph, N., Wachter, H., and Holzgrabe, U. (2014). 1H NMR profiling as an approach to differentiate conventionally and organically grown tomatoes. Journal of Agricultural and Food Chemistry. 62(33): 8530-8540.
Martínez Bueno, M.J., Díaz-Galiano, F.J., Rajski, Ł., Cutillas, V., and Fernández-Alba, A.R. (2018). A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops. Journal of Chromatography A. 1546: 66-76.
Zhang, Y., Cao, S., Zhang, Z., Meng, X., Hsiaoping, C., Yin, C., Jiang, H., and Wang, S. (2020). Nutritional quality and health risks of wheat grains from organic and conventional cropping systems. Food Chemistry. 308: Article No. 125584.
Natrella, G., Gambacorta, G., De Palo, P., Maggiolino, A., and Faccia, M. (2020). Volatile organic compounds in milk and mozzarella: Comparison between two different farming systems. International Journal of Food Science and Technology. 5(11): 3403-3411.