Title of article :
Use of X-ray diffraction technique and chemometrics to aid soil sampling strategies in traceability studies
Author/Authors :
Bertacchini، نويسنده , , Lucia and Durante، نويسنده , , Caterina and Marchetti، نويسنده , , Andrea and Sighinolfi، نويسنده , , Simona and Silvestri، نويسنده , , Michele and Cocchi، نويسنده , , Marina، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2012
Abstract :
Aim of this work is to assess the potentialities of the X-ray powder diffraction technique as fingerprinting technique, i.e. as a preliminary tool to assess soil samples variability, in terms of geochemical features, in the context of food geographical traceability. A correct approach to sampling procedure is always a critical issue in scientific investigation. In particular, in food geographical traceability studies, where the cause–effect relations between the soil of origin and the final foodstuff is sought, a representative sampling of the territory under investigation is certainly an imperative. This research concerns a pilot study to investigate the field homogeneity with respect to both field extension and sampling depth, taking also into account the seasonal variability. Four Lambrusco production sites of the Modena district were considered. The X-Ray diffraction spectra, collected on the powder of each soil sample, were treated as fingerprint profiles to be deciphered by multivariate and multi-way data analysis, namely PCA and PARAFAC. The differentiation pattern observed in soil samples, as obtained by this fast and non-destructive analytical approach, well matches with the results obtained by characterization with other costly analytical techniques, such as ICP/MS, GFAAS, FAAS, etc. Thus, the proposed approach furnishes a rational basis to reduce the number of soil samples to be collected for further analytical characterization, i.e. metals content, isotopic ratio of radiogenic element, etc., while maintaining an exhaustive description of the investigated production areas.
Keywords :
Food geographical traceability , PCA , Multivariate data analysis , PARAFAC , powder X-ray diffraction , soil