Development and Application of a Database of Food Ingredient Fraud and Economically Motivated Adulteration from 1980 to 2010

Abstract

Abstract: Food ingredient fraud and economically motivated adulteration are emerging risks, but a comprehensive compilation of information about known problematic ingredients and detection methods does not currently exist. The objectives of this research were to collect such information from publicly available articles in scholarly journals and general media, organize into a database, and review and analyze the data to identify trends. The results summarized are a database that will be published in the US Pharmacopeial Convention's Food Chemicals Codex , 8th edition, and includes 1305 records, including 1000 records with analytical methods collected from 677 references. Olive oil, milk, honey, and saffron were the most common targets for adulteration reported in scholarly journals, and potentially harmful issues identified include spices diluted with lead chromate and lead tetraoxide, substitution of Chinese star anise with toxic Japanese star anise, and melamine adulteration of high protein content foods. High‐performance liquid chromatography and infrared spectroscopy were the most common analytical detection procedures, and chemometrics data analysis was used in a large number of reports. Future expansion of this database will include additional publically available articles published before 1980 and in other languages, as well as data outside the public domain. The authors recommend in‐depth analyses of individual incidents. Practical Application: This report describes the development and application of a database of food ingredient fraud issues from publicly available references. The database provides baseline information and data useful to governments, agencies, and individual companies assessing the risks of specific products produced in specific regions as well as products distributed and sold in other regions. In addition, the report describes current analytical technologies for detecting food fraud and identifies trends and developments.

Ähnliche Arbeiten