Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy

Abstract

Concerns about meat authenticity are increasing recently, due to great fraud scandals. This paper analysed real samples (43 adulterated and 12 controls) originated from criminal networks dismantled by the Brazilian Police. This fraud consisted of injecting solutions of non-meat ingredients (NaCl, phosphates, carrageenan, maltodextrin) in bovine meat, aiming to increase its water holding capacity. Five physico-chemical variables were determined, protein, ash, chloride, sodium, phosphate. Additionally, infrared spectra were recorded. Supervised classification PLS-DA models were built with each data set individually, but the best model was obtained with data fusion, correctly detecting 91% of the adulterated samples. From this model, a variable selection based on the highest VIPscores was performed and a new data fusion model was built with only one chemical variable, providing slightly lower predictions, but a good cost/performance ratio. Finally, some of the selected infrared bands were specifically associated to the presence of adulterants NaCl, tripolyphosphate and carrageenan.

Economically Motivated Food Fraud and Adulteration in Brazil: Incidents and Alternatives to Minimize Occurrence

“…Spectroscopic techniques are very promising tools to detect and/or quantify adulteration in food because they are rapid, nondestructive, effective, reliable, and do not use chemical reagents (Kamal & Karoui, ). The NIRS methodology was successfully applied to identify food fraud and adulteration in the following food production chains: milk and dairy products (Carvalho et al., ; Gondim, Junqueira, Souza, Ruisánchez, & Callao, ; Kamal & Karoui, ; Rodrigues et al., ), honey and botanical origin studies (Siddiqui, Musharraf, Choudhary, & Rahman, ), coffee (Reis, Franca, & Oliveira, ), bovine meat (Nunes et al., ), and extra virgin flaxseed oil (Souza, Santana, Gontijo, Mazivila, & Borges, ). Infrared spectroscopy combined with chemometrics has been used as a powerful tool for determining adulterants in milk, contributing to product quality assurance and serving as a method for cross‐checking results (Nascimento, Santos, Pereira‐Filho, & Rocha, ).…”

Overview on Untargeted Methods to Combat Food Frauds: A Focus on Fishery Products

“…In 2017, UV-VIS spectroscopy was used as a testing approach to distinguish pomegranate molasses from the date syrup [63]. In 2016, meat fraud characterized by nonmeat ingredient addition, including salts, carrageenan, maltodextrin, and collagen, was detected using ATR-FTIR spectroscopy and the purpose of this adulterant manipulation was to increase the water holding capacity in bovine meat [64]. In another paper, the same approach was used as a tool for unifloral honey authentication [65].…”

Water quality monitoring method based on data fusion technology

“…Pls A Pls A + (10) We assume that all types of water quality indexes are independent of each other, and the final water quality detection decisions can be made by the above process.…”

“…In this paper, we demonstrate the problem of data fusion in the water monitoring system. Data fusion has been successfully utilized in many areas, such as generating daily synthetic Landsat imagery [9], detection and characterisation of frauds in bovine meat [10], indoor localization under collinear ambiguity [11], prediction of olive oil sensory descriptors [12], olive oil sensory defects classification [13], in-process inspection of freeform shaped parts [14], vibration condition monitoring system for wind turbine bearings [15], exploring the cancer aberration landscape [16], enhancing information retrieval process [17], minimizing energy consumption by selecting sensors for sampling and relaying data [18], adaptive locality weighted multisource joint sparse representation classification [19].…”