There is a growing interest in agriculture productions combining safety and quality attributes with clear regional identity. In the last few years several methods have been employed for food authentication and traceability. In this study we tested geochemical data for elemental concentrations of Mn, Cu, Zn, Rb, Stand Cd and strontium isotope ratio in combination with biological data of 11 secondary metabolites and DNA as markers for the authentication of the origin of early potatoes at small geographical scale levels in Italy. DNA fingerprints through 12 SSR (simple sequence repeat) primer pairs allowed cultivar identification, confirming the discrimination power of molecular markers. Element concentrations, strontium isotope ratio and secondary metabolite data, through multivariate statistics (partial least squares discriminant analysis. PLS-DA), made it possible to clearly assign all the potato samples to the respective administrative regions of cultivation. The validation of the models was successful. It included external prediction tests on 20% of the data randomly selected from each administrative province and a study on the robustness of these multivariate data treatments to uncertainties on measurement results.
Biological and geochemical markers of the geographical origin and genetic identity of potatoes
DAL PIAZ, FABRIZIO;DE TOMMASI, Nunziatina;LEPORE, LAURA;
2012-01-01
Abstract
There is a growing interest in agriculture productions combining safety and quality attributes with clear regional identity. In the last few years several methods have been employed for food authentication and traceability. In this study we tested geochemical data for elemental concentrations of Mn, Cu, Zn, Rb, Stand Cd and strontium isotope ratio in combination with biological data of 11 secondary metabolites and DNA as markers for the authentication of the origin of early potatoes at small geographical scale levels in Italy. DNA fingerprints through 12 SSR (simple sequence repeat) primer pairs allowed cultivar identification, confirming the discrimination power of molecular markers. Element concentrations, strontium isotope ratio and secondary metabolite data, through multivariate statistics (partial least squares discriminant analysis. PLS-DA), made it possible to clearly assign all the potato samples to the respective administrative regions of cultivation. The validation of the models was successful. It included external prediction tests on 20% of the data randomly selected from each administrative province and a study on the robustness of these multivariate data treatments to uncertainties on measurement results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
