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Compound-specific isotope analysis to improve food traceability

Authors: Bontempo, L.; Paolini, M.; Camin, F.;

Compound-specific isotope analysis to improve food traceability

Abstract

The scandals of recent years have left their mark on consumer confidence in food products. For this reason there is increasing demand for analytical techniques able to provide data on issues such as the traceability, authenticity and origin of foods and beverages. Stable isotope ratios have been used for food authentication for thirty years, and in the last few years emerging methods aimed at individual chemical compounds have provided a means of obtaining a more in-depth understanding. In particular, a technique that shows enormous promise in this area is gas chromatography combustion/pyrolysis - isotope ratio mass spectrometry (GC-C/Py-IRMS). This technique can be applied to a wide array of foods and beverages, generating data on key food components such as amino acids, fatty acids, aroma compounds and carbon dioxide (in carbonated beverages). This data can be used to verify the geographical origin of foods and food ingredients and the use of synthetic or organic fertilisers, as well as to determine the synthetic or natural origin of food ingredients. GC-C/Py-IRMS is thus one of the most powerful techniques available at the moment to detect fraudulent, illegal, or unsafe practices in the food and beverage industry

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green