Protein Signatures to Trace Seafood Contamination and Processing

Lipidomics in forensic science: a comprehensive review of applications in drugs, alcohol, latent fingermarks, fire debris, and seafood authentication

Forensic science, an interdisciplinary field encompassing the collection, examination, and presentation of evidence in legal proceedings, has recently embraced lipidomics as a valuable tool. Lipidomics, a subfield of metabolomics, specializes in the analysis of lipid structures and functions, offering insights into biological processes that can aid forensic investigations. While not a substitute for DNA analysis in personal identification, lipidomics complements this technique by focusing on small biological molecules, with distinct sample requirements. This review comprehensively explores the current applications of lipidomics in forensic science. The review commences with an introduction to the concept and historical background of lipidomics, subsequently delving into its utilization in diverse areas such as drug analysis, ethyl alcohol and substitute assessment, latent fingermark detection, fire debris analysis, and seafood authentication. By showcasing the various biological materials and methods employed, this review underscores the potential of lipidomics as a powerful adjunct in forensic investigations.

Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review

Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.

In-depth insight into the effects of tapioca or corn acetylated distarch phosphate on the gel properties and in vitro digestibility of kung-wan

Modified starch is increasingly applied in the meat industry as an effective functional ingredient to provide meat products with the desired textural properties and appearance. This study aimed to investigate the effects of incorporating tapioca acetylated distarch phosphate (TADSP) or corn acetylated distarch phosphate (CADSP) on the gel properties and in vitro digestibility of Chinese-style meatballs known as kung-wan. The results showed that TADSP and CADSP significantly enhanced the textural properties of kung-wan in a dose-dependent manner (P < 0.05), as well as enhanced the rheological behavior of meat batters. TADSP resulted in a denser meat protein gel network compared to CADSP, primarily because the lower pasting temperature of TADSP made it gelatinize earlier and more completely during heating than CADSP and subsequently filled in the meat protein gel network. The intermolecular forces observed in kung-wan with TADSP or CADSP were hydrogen bonds and hydrophobic interactions. Furthermore, the protein digestibility of kung-wan was increased with higher levels of TADSP and CADSP (P < 0.05). Notably, kung-wan with TADSP exhibited significantly higher protein digestibility than those with CADSP at the same level (P < 0.05). Our results offer valuable insights into the potential application of acetylated distarch phosphate in kung-wan.

Investigation of the effects and mechanism of incorporation of cross-linked/acetylated tapioca starches on the gel properties and in vitro digestibility of kung-wan

The effects and mechanism of incorporation of cross-linked tapioca starch (CTS) or acetylated tapioca starch (ATS) on the gel properties and in vitro digestibility of kung-wan (a Chinese-style meatball) were evaluated. The results indicated that incorporation of either CTS or ATS significantly enhanced the gel properties of kung-wan in a dose-dependent manner (P < 0.05), as well as the rheological properties of meat batter. Moreover, hydrogen bonds and electrostatic interaction were the major intermolecular forces in kung-wan when incorporated with CTS or ATS. Meanwhile, CTS and ATS acted as fillers in the meat protein gel matrix, which was further verified by the microstructure of kung-wan. However, CTS produced a more uniform and dense meat protein gel network than ATS, which was mainly due to its limited swelling characteristics. In addition, the incorporation of CTS or ATS significantly increased the in vitro digestibility of protein in kung-wan with increasing level of addition (P < 0.05). However, no significant differences in protein digestibility were detected between the CTS and ATS groups at the same addition level (P > 0.05). Our results provided some critical points for the actual application of modified tapioca starch to promote the quality profiles of kung-wan.

In-Depth Insight into the Mechanism of Incorporation of Abelmoschus manihot Gum on the Enhancement of Gel Properties and In Vitro Digestibility of Frankfurters

This study aimed to investigate the effects of different concentrations (0.1, 0.2, 0.3, 0.4, and 0.5% w/w) of Abelmoschus manihot gum (AMG) on the gel properties and in vitro digestibility of frankfurters. The results indicated that AMG incorporation significantly enhanced the emulsion stability and texture of frankfurters, as well as the dynamic rheological characteristics of raw meat batter, with the optimal concentration being 0.3% (p < 0.05). Furthermore, hydrogen bonds and disulphide bonds were the main molecular forces of the frankfurters in the presence of AMG. Microstructural images showed that more uniform and dense microstructures of frankfurters were formed due to AMG supplementation. In addition, AMG incorporation significantly increased the in vitro protein digestibility of frankfurters as the level of addition increased (p < 0.05). In conclusion, our results provided critical information for the practical application of AMG in the production of emulsified meat products.

Deep-Stacking Network Approach by Multisource Data Mining for Hazardous Risk Identification in IoT-Based Intelligent Food Management Systems

Food quality and safety issues occurred frequently in recent years, which have attracted more and more attention of social and international organizations. Considering the increased quality risk in the food supply chain, many researchers have applied various information technologies to develop real-time risk identification and traceability systems (RITSs) for preferable food safety guarantee. This paper presents an innovative approach by utilizing the deep-stacking network method for hazardous risk identification, which relies on massive multisource data monitored by the Internet of Things timely in the whole food supply chain. The aim of the proposed method is to help managers and operators in food enterprises to find accurate risk levels of food security in advance and to provide regulatory authorities and consumers with potential rules for better decision-making, thereby maintaining the safety and sustainability of food product supply. The verification experiments show that the proposed method has the best performance in terms of prediction accuracy up to 97.62%, meanwhile achieves the appropriate model parameters only up to 211.26 megabytes. Moreover, the case analysis is implemented to illustrate the outperforming performance of the proposed method in risk level identification. It can effectively enhance the RITS ability for assuring food supply chain security and attaining multiple cooperation between regulators, enterprises, and consumers.