Soy sauce, a dark-colored seasoning, is added to enhance the sensory properties of foods. Soy sauce can be consumed as a condiment or added during the preparation of food. There are 3 types of soy sauce: fermented, acid-hydrolyzed vegetable protein (acid-HVP), and mixtures of these. 3-Chloropropane-1,2-diol (3-MCPD) is a heatproduced contaminants formed during the preparation of soy sauce and was found to be a by-product of acid-HVPproduced soy sauce in 1978. 3-MCPD has been reported to be carcinogenic, nephrotoxic, and reproductively toxic in laboratory animal testing and has been registered as a chemosterilant for rodent control. 3-MCPD is classified as a possible carcinogenic compound, and the maximum tolerated limit in food has been established at both national and international levels. The purpose of this review is to provide an overview on the detection of 3-MCPD in soy sauce, its toxic effects, and the potential methods to reduce its concentration, especially during the production of acid-HVP soy sauce. The methods of quantification are also critically reviewed with a focus on efficiency, suitability, and challenges encountered in analysis.

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This paper reports the application of hexamethyldisilazane-trimethylsilyl trifluoromethanesulfonate (HMDS-TMSOTf) for the simultaneous silylation of 3-monochloro-1,2-propanediol (3-MCPD) and 1,3-dicholoropropanol (1,3-DCP) in solid and liquid food samples. 3-MCPD and 1,3-DCP are chloropropanols that have been established as Group 2B carcinogens in clinical testing. They can be found in heat-processed food, especially when an extended high-temperature treatment is required. However, the current AOAC detection method is time-consuming and expensive. Thus, HMDS-TMSOTf was used in this study to provide a safer, and cost-effective alternative to the HFBI method. Three important steps are involved in the quantification of 3-MCPD and 1,3-DCP: extraction, derivatization and quantification. The optimization of the derivatization process, which involved focusing on the catalyst volume, derivatization temperature, and derivatization time was performed based on the findings obtained from both the Box-Behnken modeling and a real experimental set up. With the optimized conditions, the newly developed method was used for actual food sample quantification and the results were compared with those obtained via the standard AOAC method. The developed method required less samples and reagents but it could be used to achieve lower limits of quantification (0.0043mgL(-1) for 1,3-DCP and 0.0011mgL(-1) for 3-MCPD) and detection (0.0028mgL(-1) for 1,3-DCP and 0.0008mgL(-1) for 3-MCPD). All the detected concentrations are below the maximum tolerable limit of 0.02mgL(-1). The percentage of recovery obtained from food sample analysis was between 83% and 96%. The new procedure was validated with the AOAC method and showed a comparable performance. The HMDS-TMSOTf derivatization strategy is capable of simultaneously derivatizing 1,3-DCP and 3-MCPD at room temperature, and it also serves as a rapid, sensitive, and accurate analytical method for food samples analysis.

Microplastics (the term for plastics at sizes of <5 mm) might be introduced into the environment from domestic or agricultural activities or from the breakdown of plastic pieces, particles, and debris that are bigger in size. Their presence in the aquatic environment has caused accumulation problems, as microplastics do not easily break down and can be digested by some aquatic organisms. This study was conducted to screen and monitor the level of microplastic pollution in polychaete worms using pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS). The study was conducted in Setiu Wetlands, Malaysia from November 2015 to January 2017 at five-month intervals and covered all monsoon changes. Results from physical and visual analyses indicated that a total number of 371.4 ± 20.2 items/g microplastics were retrieved from polychaete for all seasons, in which, the majority comprised transparent microplastics (49.87%), followed by brown with 138.3 ± 13.6 items/g (37.24%), 21.7 ± 1.9 items/g for blue (5.84%), and 12.9 ± 1.1 items/g for black (3.47%), while the remaining were green and grey-red colors. Statistical analysis using Kruskal–Wallis showed insignificant differences (p > 0.05) between the sampling station and period for the presence of a microplastics amount. Most of the microplastics were found in fiber form (81.5%), whereas the remaining comprised fragment (18.31%) and film (0.19%) forms. Further analysis with Py-GC/MS under a selective ion monitoring mode indicated that pyrolytic products and fragment ions for a variety of polymers, such as polyvinyl chloride, polypropylene, polyethylene, polyethylene terephthalate, polyamide, and polymethylmethacrylate, were detected. This study provides an insightful application of Py-GC/MS techniques for microplastics monitoring, especially when dealing with analytical amounts of samples.

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