Three main limitations:<\/p>\n
\u00b7 These analyses only cover 3 main aspects of the organic regulations: detection and quantification of residues of plant protection products<\/strong>, detection of residues of veterinary products<\/strong> in meat products and detection of GMOs<\/strong>. Other key specifications of organic farming (e.g. crop rotation, recycling of organic matter, animal welfare) cannot be analytically tested at present.<\/p>\n \u00b7 Secondly, the current technical approach is that of targeted analysis<\/strong>. We seek to detect the presence of previously known products. By definition, this approach can only detect what it is looking for. On the one hand, the spectrum of elements we are looking for is relatively limited (pesticides, GMOs, veterinary drugs, etc.). On the other hand, if other products are used, such as chemically modified pesticides, it is possible that the analyses do not detect the samples as non-compliant.<\/p>\n \u00b7 The third limitation observed is that the analyses carried out may give ambiguous results on compliance with the organic farming specifications.<\/strong> Indeed, it is possible that a food product which is positive for one of these analyses has nevertheless been produced according to the organic specifications (e.g. cross-contamination, etc.). On the contrary, if we limit ourselves to these methods, some conventional products can give a negative result on these analyses and thus be confused with authentically organic products.<\/p>\n <\/p>\n The aim of the TOFoo project is therefore to develop innovative analyses to ensure the authenticity of the “organic” character of food products throughout the supply chain.<\/p>\n These will include methods that collect the overall analytical footprint<\/strong> of products and verify their “organic” character (“non-targeted” approach), as well as methods for the identification of non-authorised food additives<\/strong> and the characterisation of manufactured nanoparticles<\/strong>. They will be applied to plant products (fruit, vegetables, cereals, oilseeds and protein crops) and dairy products.<\/strong><\/p>\n On-site analyses<\/strong>will complement these laboratory analyses, allowing rapid and frequent checks<\/strong> to be carried out directly on industrial or distribution sites. These analyses, carried out with portable testing devices<\/strong>, will be designed to provide pre-alerts on product integrity, to be confirmed by laboratory methods.<\/p>\n Finally, to enable the development of these new analyses, each partner will contribute to the emergence of new solutions: development of portable devices for rapid in situ analysis, improved performance of laboratory equipment<\/strong>with emerging technologies, constitution and exploitation of databases<\/strong> of several thousand samples thanks to innovative statistical processing at the crossroads of “big data” and artificial intelligence.<\/strong>.<\/p>\n The principle behind the non-targeted analyses we carry out is that there is a difference in chemical composition between organic and conventional products.<\/strong> This difference could be due to different agricultural practices between organic and conventional farming, which would have an influence on the metabolism of plants or animals, and therefore on the final composition of the food products. This assumption is supported by the scientific literature, summarised in two meta-studies, one on crops and the other on dairy products. [1,2].<\/p>\n The objective of the non-targeted methods is to identify these differences without prejudice by comparing the general analytical fingerprints<\/strong> of organic and non-organic products.<\/p>\n To do this, we are building analytical databases<\/strong> from several thousands of samples<\/strong>. We then seek to extract markers of “organic” character from the great variability of food products, linked to their variety, their geographical origin, the weather during the year of production, etc.<\/p>\n <\/p>\n 1. Bara\u0144ski M., \u015arednicka-Tober D., Volakakis N., Seal C., Sanderson R., Stewart G.B., Benbrook C., Biavati B., Markellou E., Giotis C., Gromadzka-Ostrowska J., Rembia\u0142kowska E., Skwar\u0142o-So\u0144ta K., Tahvonen R., Janovsk\u00e1 D., Niggli U., Nicot P. & Leifert C. (2014). \u2013 Higher antioxidant and lower cadmium concentrations and lower incidence of pesticide residues in organically grown crops: a systematic literature review and meta-analyses. British Journal of Nutrition, 112 (5), 794\u2013811. doi:10.1017\/S0007114514001366.<\/p>\n 2. Palupi E., Jayanegara A., Ploeger A. & Kahl J. (2012). \u2013 Comparison of nutritional quality between conventional and organic dairy products: a meta-analysis. J Sci Food Agric, 92 (14), 2774\u20132781. doi:10.1002\/jsfa.5639.<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":"Planned innovations<\/h2>\n
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Why non-targeted methods?<\/h2>\n