Feligini M.,Instituto Sperimentale Italiano Lazzaro Spallanzani |
Panelli S.,Instituto Sperimentale Italiano Lazzaro Spallanzani |
Sacchi R.,Universita` Degli Studi Of Pavia |
Ghitti M.,Universita` Degli Studi Of Pavia |
Capelli E.,Universita` Degli Studi Of Pavia
Food Control | Year: 2015
The aim of the study was to distinguish the raw milk from different farms in relation to their geographical sites within a narrowed territorial district. The goal was achieved by applying a molecular-based system for traceability that uses microbial DNA barcodes present in milk. Microbiota of milk were fingerprinted by PCR of the 16S-23S intergenic transcribed spacer using the Automated Ribosomal Intergenic Spacer Analysis (ARISA). A total of 64 markers within the range 279-756 bp were detected on the thirty-eight bulk milk samples, none of which was common to all the patterns. Overall samples did not show relevant differences across the two years of sampling. In fact, every farm maintained a specific core profile over time, thus demonstrating that the interaction between site and year of sampling is not significant and that the variability between years does not affect the distinction between grouping of farms. The system was able to trace the geographical origin of raw milk with a resolution of less than 5 km. According to the European regulations for the protection of the geographical names of foodstuffs which have a tangible link to the territory, the ARISA system described here may represent a suitable analytical tool for tracing the origin of milk integrating and reinforcing traceability processes of the dairy chain. © 2014 2014 Published by Elsevier Ltd.
Kottegoda N.T.,Universita` Degli Studi Of Pavia |
Natale L.,Universita` Degli Studi Of Pavia |
Raiteri E.,Universita` Degli Studi Of Pavia
Journal of Hydrology | Year: 2014
Observations of high intensity rainfalls have been recorded at gauging stations in many parts of the world. In some instances the resulting data sets may not be sufficient in their scope and variability for purposes of analysis or design. By directly incorporating statistical properties of hyetographs with respect to the number of events per year, storm duration, peak intensity, cumulative rainfall and rising and falling limbs we develop a fundamentally basic procedure for Monte Carlo Simulation. Rainfall from Pavia and Milano in Lombardia region and from five gauging stations in the Piemonte region of northern Italy are used in this study. Firstly, we compare the hydrologic output from our model with that from other design storm methods for validation. Secondly, depth-duration-frequency curves are obtained from historical data and corresponding functions from simulated data are compared for further validation of the procedure. By adopting this original procedure one can simulate an unlimited range of realistic hydrographs that can be used in risk assessment. The potential for extension to ungauged catchments is shown. © 2014.