Background Meat is a perishable product and during storage, the actions of microorganisms and endogenous enzymes result in chemical compositional changes. Total volatile basic nitrogen (TVB-N) is often used as a biomarker of protein and amine degradation. The broad adoption of TVB-N to interpret meat freshness is somewhat restricted. This is the result of limited or inconsistent knowledge pertaining to the association between TVB-N and other freshness parameters, for beef, sheep/goat meat, pork, chicken and other types of meat, especially when compared to fish. Current meat studies have failed to address the mechanisms between TVB-N generation and production, processing and preservation strategies. Scope and approach Etiology of spoilage and freshness indicators in fresh meat are discussed and various mechanisms contributing to meat spoilage are highlighted. Further, the use and application of TVB-N for understanding the freshness of different meat types has been comprehensively reviewed with the aim of establishing its usefulness as a freshness marker. Key Findings and Conclusions TVB-N increases with meat storage and is aligned with other biomarkers of spoilage (i.e. function of duration, temperature, packaging, etc.). But these increases are not always consistent. There are different recommendations of TVB-N limits for meat freshness. These are primarily for fish and seafood products and therefore inappropriate for other meat types, are species specific, arbitrary, or have an element of ambiguity (e.g. an intermediary ‘stale’ classification between fresh and spoilt states). The selection of TVB-N limits can therefore introduce inaccuracy and subjectivity into the appraisal of meat freshness. Several destructive and non-destructive methods have been used to determine TVB-N, however, their capacity is limited to the differential between spoilt and non-spoilt samples through chemometric classification systems based on predefined TVB-N guidelines. Further reference populations and investigations of red meat types are required.

Total volatile basic nitrogen (TVB-N) and its role in meat spoilage: A review

Application of Raman Spectroscopic Methods in Food Safety: A Review

SERS detection of sodium thiocyanate and benzoic acid preservatives in liquid milk using cysteamine functionalized core-shelled nanoparticles.

In the current work, surface-enhanced Raman scattering (SERS) based on gold nanoparticles (AuNPs) and silver-coated gold nanoparticles (Au@AgNPs) with coffee ring effect was employed to simultaneously ascertain urea and ammonium sulfate (AmS) in milk. A small drop (2 µL) of milk with adulterants was dried on a gold-coated slide to examine concentrations ranging from 5, 10, 20, 40 and 80 mg/dL based on spectra ranging from 400 to 1500 cm.-1 A uniform distribution of analytes, with enhanced Raman signals was detected in a small region (maximum 1.9 mm) of coffee ring across the centre of coffee ring pattern. Nanoparticles with core (Au) diameter of 26 nm and shell thickness (Ag) of 6.5 nm were confirmed using transmission electron microscopy (TEM) images. A strong Raman peak at 980 cm-1 was assigned to AmS, while that at 1001 cm-1 was ascribed to urea. With AuNPs, coefficients of determination (R2) of 0.9873 and 0.9859 were achieved for urea and AmS, respectively, while for Au@AgNPs values of 0.9827 and 0.9855 were obtained for urea and AmS, respectively. This study revealed that SERS based on coffee ring effect has the potential to be further exploited for detecting other banned and hazardous adulterants in milk and milk products.

SERS detection of urea and ammonium sulfate adulterants in milk with coffee ring effect.

Background The consumption of alcoholic beverages is an integral part of many socio-cultural traditions. The existing methods of compositional analysis and quality control of alcoholic beverages are not satisfying the burgeoning demands of global market due to their high cost and slow turnaround time. Scope and approach The nondestructive instrumental techniques can be applied for quality control, discrimination and authentication of alcoholic beverages. The cost of analysis, reduction in time, environment friendliness, and non-destructive nature of these techniques offers bright prospects for the future. Key findings and conclusions This review aims to highlight the most relevant and current information on the use of nondestructive instrumental techniques for evaluating quality, discrimination and authentication of alcoholic beverages. Moreover, it will serve as a guidance document for large scale production units for implementation of these laboratory-based smart techniques. This article also covers the challenges faced by the beverage industry which needs to be resolved or investigated in future studies.

Recent trends in quality control, discrimination and authentication of alcoholic beverages using nondestructive instrumental techniques

Better milk safety control can offer important means to promote public health. However, few technologies can detect different types of contaminants in milk simultaneously. In this regard, the present work proposes a single-drop Raman imaging (SDRI) strategy for semiquantitation of multiple hazardous factors in milk solutions. By developing SDRI strategy that incorporates the coffee-ring effect (a natural phenomenon often presents in a condensed circle pattern after a drop evaporated) for sample pretreatment and discrete wavelet transform for spectra processing, the method serves well to expose typical hazardous molecular species in milk products, such as melamine, sodium thiocyanate and lincomycin hydrochloride, with little sample preparation. The detection sensitivity for melamine, sodium thiocyanate, and lincomycin hydrochloride are 0.1 mg kg–1, 1 mg kg–1, and 0.1 mg kg–1, respectively. Theoretically, we establish that the SDRI represents a novel and environment-friendly method that screens the milk saf...

Single-Drop Raman Imaging Exposes the Trace Contaminants in Milk

The wide use of antibacterial hand soaps containing triclosan has raised a potential threat to health, and the detection of triclosan is thus extremely important Here we introduce an efficient approach for nondestructive screening of triclosan in hand soaps Using Raman spectroscopy in a digitally labelled approach, we utilized the strategy of modified competitive adaptive reweighted sampling (MCARS) to assign spectral features according to a higher density wavelet transform (HDWT) domain, which is named digital labeled Raman spectroscopy (DLRS) DLRS efficiently isolates the features of triclosan from matrix components, enabling the nondestructive quantitative analysis of triclosan in real antibacterial hand soaps, irrespective of the details of the soap matrix We demonstrate the feasibility of DLRS using a practical test in which we seek to quantify triclosan in several kinds of antibacterial hand soaps nondestructively The results illustrate DLRS as a promising tool for nondestructive detection of triclosan in antibacterial hand soaps without any sample pretreatment, which may well extend to digital separation of some analytes of interest in the presence of complex chemical substances

Nondestructive detection of triclosan in antibacterial hand soaps using digitally labelled Raman spectroscopy

A gas Fourier transform infrared spectroscopy methodology for the rapid and accurate discrimination of chicken spoilage through volatiles analysis

Fake liquors have caused severe body injuries or even deaths worldwide, rapid detection of such lethal drinks is thus quite necessary. Methanol has been identified as a primary cause of the problem...

Detection of lethal fake liquors using digitally labelled gas-phase Fourier transform infrared spectroscopy

On-line monitoring of key nutrients in yoghurt samples using digitally labelled Raman spectroscopy

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