Alternative pressurized liquid extraction using a hard cap espresso machine for determination of polycyclic aromatic hydrocarbons in smoked bacon

Extraction and analytical approaches for the determination of post-food processing major carcinogens: A comprehensive review towards healthier processed food

Different food processing methods, e.g. fermentation, grilling, frying, etc., to improve food sensory attributes or shelf-stability are typically employed in different cuisines worldwide. These methods may illicit in-situ health-hazardous chemicals via thermal or enzymatic-mediated processes or chemical interactions with food preservatives. This review provides a comparative overview of the occurrence, extraction, and determination of the major food carcinogens such as nitrosamines (NAs), biogenic amines (BAs), heterocyclic aromatic amines (HAAs), polycyclic aromatic hydrocarbons (PAHs), ethyl carbamate (EC), and malondialdehyde (MDA). Their carcinogenicity levels vary from group 1 (carcinogenic to humans) e.g. benzo[a]pyrene, group 2A (probably carcinogenic to humans) e.g. N-nitrosodiethylamine, group 2B (possibly carcinogenic to humans) e.g. chrysene or group 3 (non-classifiable as carcinogenic to humans) e.g. MDA. Chromatography-based methods are the most predominant techniques used for their analysis. LC-MS is widely used for both volatile/non-volatile NAs, HAAs, BAs, and EC, whereas GC-MS is applied more for volatile NAs, PAHs and MDA.

Pressurized Liquid Extraction: A Powerful Tool to Implement Extraction and Purification of Food Contaminants

Pressurized liquid extraction (PLE) is considered an advanced extraction technique developed in the mid-1990s with the aim of saving time and reducing solvent with respect to traditional extraction processes. It is commonly used with solid and semi-solid samples and employs solvent extraction at elevated temperatures and pressures, always below the respective critical points, to maintain the solvent in a liquid state throughout the extraction procedure. The use of these particular pressure and temperature conditions changes the physicochemical properties of the extraction solvent, allowing easier and deeper penetration into the matrix to be extracted. Furthermore, the possibility to combine the extraction and clean-up steps by including a layer of an adsorbent retaining interfering compounds directly in the PLE extraction cells makes this technique extremely versatile and selective. After providing a background on the PLE technique and parameters to be optimized, the present review focuses on recent applications (published in the past 10 years) in the field of food contaminants. In particular, applications related to the extraction of environmental and processing contaminants, pesticides, residues of veterinary drugs, mycotoxins, parabens, ethyl carbamate, and fatty acid esters of 3-monochloro-1,2-propanediol and 2-monochloro-1,3-propanediol from different food matrices were considered.

Research Progress of Polycyclic Aromatic Hydrocarbons Pretreatment Methods and Application of Computer Simulation Technology for Prediction and Degradation of Electrochemical Concentration Detection

Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds that are composed of aromatic rings containing only carbon and hydrogen atoms. They are one of the widespread environmental pollutants in the world. In recent years, many scholars have focused on the inhibition, formation mechanism, content of active components, and biodegradation effect of polycyclic aromatic hydrocarbons. They summarized the research progress of pretreatment methods for detection, but rarely discussed the experimental dataset for comprehensive analysis of pollution sources and the impact of different pretreatment technologies on the extraction of different substrates. What is more, computer simulation has not been mentioned. In this study, the pollution sources of polycyclic aromatic hydrocarbons (PAHs) are reviewed, and the related applications of various pretreatment methods such as gel permeation chromatography (GPC) are summarized. Finally, the computer simulation of the response surface method is introduced. The concentration of polycyclic aromatic hydrocarbons is tested or predicted by combining the neural network with the alternating trilinear decomposition (ATLD) algorithm, artificial population algorithm (ABC), and hierarchical genetic algorithm (HGA). Its future development trend is discussed and prospected, which provides a reference for solving the pollution problem. We look forward to providing help for the follow-up research of scholars in this field.