Title: Combining Isotopic Signatures of n(87Sr)/n(86Sr) and Light Stable Elements (C, N, O, S) with Multi-Elemental Profiling for the Authentication of Provenance of European Cereal Samples
Authors: GOITOM ASFAHA DanielQUETEL ChristopheTHOMAS FreddyHORACEK MichaWIMMER BernhardHEISS GerhardDEKANT ChristianDETERS-ITZELSBERGER PeterHOELZL StefanRUMMEL SusanneBRACH-PAPA ChristopheVAN BOCXSTAELE MarleenJAMIN EricBAXTER MalcomHEINRICH KatharinaKELLY SimonBERTOLDI DanielaBONTEMPO LuanaCAMIN FedericaLARCHER RobertoPERINI MatteoROSSMAN AndreasSCHELLENBERG AntjeSCHLICHT ClausFROESCHL HeinzHOOGEWERFF JurianUECKERMANN Henriette
Citation: JOURNAL OF CEREAL SCIENCE vol. 53 no. 2 p. 170-177
Publisher: ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
Publication Year: 2011
JRC N°: JRC59105
ISSN: 0733-5210
URI: http://www.elsevier.com/locate/jcs
http://publications.jrc.ec.europa.eu/repository/handle/JRC59105
DOI: 10.1016/j.jcs.2010.11.004
Type: Articles in Journals
Abstract: The aim of this work (from the FP6 project TRACE) was to develop methods based on the use of geochemical markers for the authentication of the geographical origin of cereal samples in Europe (cf. EC regulations 2081/92 and 1898/06). For the first time, the potential usefulness of combining n(87Sr)/n(86Sr) and delta13C, delta15N, delta18O and delta34S isotopic signatures, alone or with key element concentrations ([Na], [K], [Ca], [Cu] and [Rb], progressively identified out of 31 sets of results), was investigated through multiple step multivariate statistics for more than 500 cereal samples collected over 2 years from 17 sampling sites across Europe representing an extensive range of geographical and environmental characteristics. From the classification categories compared (north/south; proximity to the Atlantic Ocean/to the Mediterranean Sea/to else; bed rock geologies) the first two were the most efficient (particularly with the ten variables selected together). In some instances element concentrations made a greater impact than the isotopic tracers. Validation of models included external prediction tests on 20% of the data randomly selected and, rarely done, a study on the robustness of these multivariate data treatments to uncertainties on measurement results. With the models tested it was possible to individualise 15 of the sampling sites.
JRC Institute:Institute for Reference Materials and Measurements

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