TY - JOUR
T1 - Global media as an early warning tool for food fraud; an assessment of MedISys-FF
AU - Marvin, Hans J.P.
AU - Hoenderdaal, Wouter
AU - Gavai, Anand K.
AU - Mu, Wenjuan
AU - van den Bulk, Leonieke M.
AU - Liu, Ningjing
AU - Frasso, Gianluca
AU - Ozen, Neris
AU - Elliott, Chris
AU - Manning, Louise
AU - Bouzembrak, Yamine
PY - 2022/7
Y1 - 2022/7
N2 - Food fraud is a serious problem that may compromise the safety of the food products being sold on the market. Previous studies have shown that food fraud is associated with a large variety of food products and the fraud type may vary from deliberate changing of the food product (i.e. substitution, tampering, dilution etc.) to the manipulation of documents. It is therefore important that all actors within the food supply chain (food producers, authorities), have methodologies and tools available to detect fraudulent products at an early stage so that preventative measures can be taken. Several of such systems exist (i.e. iRASFF, EMA, HorizonScan, AAC-FF, MedISys-FF), but currently only MedISys-FF is publicly online available. In this study, we analyzed food fraud cases collected by MedISys-FF over a 6-year period (2015–2020) and show global trends and developments in food fraud activities. In the period investigated, the system has collected 4375 articles on food fraud incidents from 164 countries in 41 different languages. Fraud with meat and meat products were most frequently reported (27.7%), followed by milk and milk products (10.5%), cereal and bakery products (8.3%), and fish and fish products (7.7%). Most of the fraud was related to expiration date (58.3%) followed by tampering (22.2%) and mislabeling of country of origin (11.4%). Network analysis showed that the focus of the articles was on food products being frauded. The validity of MedISys-FF as an early warning system was demonstrated with COVID-19. The system has collected articles discussing potential food fraud risks due to the COVID-19 crisis. We therefore conclude that MedISys-FF is a very useful tool to detect early trends in food fraud and may be used by all actors in the food system to ensure safe, healthy, and authentic food.
AB - Food fraud is a serious problem that may compromise the safety of the food products being sold on the market. Previous studies have shown that food fraud is associated with a large variety of food products and the fraud type may vary from deliberate changing of the food product (i.e. substitution, tampering, dilution etc.) to the manipulation of documents. It is therefore important that all actors within the food supply chain (food producers, authorities), have methodologies and tools available to detect fraudulent products at an early stage so that preventative measures can be taken. Several of such systems exist (i.e. iRASFF, EMA, HorizonScan, AAC-FF, MedISys-FF), but currently only MedISys-FF is publicly online available. In this study, we analyzed food fraud cases collected by MedISys-FF over a 6-year period (2015–2020) and show global trends and developments in food fraud activities. In the period investigated, the system has collected 4375 articles on food fraud incidents from 164 countries in 41 different languages. Fraud with meat and meat products were most frequently reported (27.7%), followed by milk and milk products (10.5%), cereal and bakery products (8.3%), and fish and fish products (7.7%). Most of the fraud was related to expiration date (58.3%) followed by tampering (22.2%) and mislabeling of country of origin (11.4%). Network analysis showed that the focus of the articles was on food products being frauded. The validity of MedISys-FF as an early warning system was demonstrated with COVID-19. The system has collected articles discussing potential food fraud risks due to the COVID-19 crisis. We therefore conclude that MedISys-FF is a very useful tool to detect early trends in food fraud and may be used by all actors in the food system to ensure safe, healthy, and authentic food.
KW - COVID-19
KW - Early warning system
KW - Food fraud
KW - MedISys-FF
KW - Trend analysis
U2 - 10.1016/j.foodcont.2022.108961
DO - 10.1016/j.foodcont.2022.108961
M3 - Article
AN - SCOPUS:85126368748
SN - 0956-7135
VL - 137
JO - Food Control
JF - Food Control
M1 - 108961
ER -