Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

How processing affects marker peptide quantification - A comprehensive estimation on bovine material relevant for food and feed control

Processing food and feed challenges official control e.g. by modifying proteins, which leads to significant underestimation in targeted, MS-based protein quantification. Whereas numerous studies identified processing-induced changes on proteins in various combinations of matrices and processing conditions, studying their impact semi-quantitatively on specific protein sequences might unveil approaches to improve protein quantification accuracy. Thus, 335 post-translational modifications (e.g. oxidation, deamidation, carboxymethylation, Amadori, acrolein adduction) were identified by bottom-up proteomic analysis of 37 bovine materials relevant in food and feed (meat, bone, blood, milk) with varying processing degrees (raw, spray-dried, pressure-sterilized). To mimic protein recovery in a targeted analysis, peak areas of marker and reference peptides were compared to those of their modified versions, which revealed peptide-specific recoveries and variances across all samples. Detailed analysis suggests that incorporating two modified versions additionally to the unmodified marker may significantly improve quantification accuracy in targeted MS-based food and feed control in processed matrices.

Differentiating Pond-Intensive, Paddy-Ecologically, and Free-Range Cultured Crayfish (Procambarus clarkii) Using Stable Isotope and Multi-Element Analysis Coupled with Chemometrics

The farming pattern of crayfish significantly impacts their quality, safety, and nutrition. Typically, green and ecologically friendly products command higher economic value and market competitiveness. Consequently, intensive farming methods are frequently employed in an attempt to replace these environmentally friendly products, leading to potential instances of commercial fraud. In this study, stable isotope and multi-element analysis were utilized in conjunction with multivariate modeling to differentiate between pond-intensive, paddy-ecologically, and free-range cultured crayfish. The four stable isotope ratios of carbon, nitrogen, hydrogen, and oxygen (δ13C, δ15N, δ2H, δ18O) and 20 elements from 88 crayfish samples and their feeds were determined for variance analysis and correlation analysis. To identify and differentiate three different farming pattern crayfish, unsupervised methods such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used, as well as supervised multivariate modeling, specifically partial least squares discriminant analysis (PLS-DA). The HCA and PCA exhibited limited effectiveness in classifying the farming pattern of crayfish, whereas the PLS-DA demonstrated a more robust performance with a predictive accuracy of 90.8%. Additionally, variables such as δ13C, δ15N, δ2H, Mn, and Co exhibited relatively higher contributions in the PLS-DA model, with a variable influence on projection (VIP) greater than 1. This study is the first attempt to use stable isotope and multi-element analysis to distinguish crayfish under three farming patterns. It holds promising potential as an effective strategy for crayfish authentication.

Metallic and Metal Oxides Nanoparticles for Sensing Food Pathogens—An Overview of Recent Findings and Future Prospects

Nowadays, special importance is given to quality control and food safety. Food quality currently creates significant problems for the industry and implicitly for consumers and society. The effects materialize in economic losses, alterations of the quality and organoleptic properties of the commercial products, and, last but not least, they constitute risk factors for the consumer’s health. In this context, the development of analytical systems for the rapid determination of the sanitary quality of food products by detecting possible pathogenic microorganisms (such as Escherichia coli or Salmonella due to the important digestive disorders that they can cause in many consumers) is of major importance. Using efficient and environmentally friendly detection systems for identification of various pathogens that modify food matrices and turn them into food waste faster will also improve agri-food quality throughout the food chain. This paper reviews the use of metal nanoparticles used to obtain bio nanosensors for the purpose mentioned above. Metallic nanoparticles (Au, Ag, etc.) and their oxides can be synthesized by several methods, such as chemical, physical, physico-chemical, and biological, each bringing advantages and disadvantages in their use for developing nanosensors. In the “green chemistry” approach, a particular importance is given to the metal nanoparticles obtained by phytosynthesis. This method can lead to the development of good quality nanoparticles, at the same time being able to use secondary metabolites from vegetal wastes, as such providing a circular economy character. Considering these aspects, the use of phytosynthesized nanoparticles in other biosensing applications is also presented as a glimpse of their potential, which should be further explored.

Application of Computer Microtomography and Hyperspectral Imaging to Assess the Homogeneity of the Distribution of Active Ingredients in Functional Food

Functional foods represent one of the most intensively investigated and widely promoted areas in the food and nutrition sciences’ market today. The purpose of this work is to determine the possibility of using computed microtomography to assess the homogeneity of distribution of active pharmaceutical ingredients (vitamins K and D and calcium) throughout chocolate. Algorithms for analyzing of microtomographic images were proposed to quantify the distribution of active pharmaceutical ingredients (API) in chocolate: the Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging. The use of the methods of analysis and processing of microtomographic images allows for a quantitative assessment of the homogeneity of the distribution of components throughout the sample, without a 3D reconstruction process. In computer microtomography analysis, it is possible to assess the distribution of those components whose density differs by at least a unit in the accepted scale of gray levels of images and for grain sizes not smaller than the voxel size. The proposed image analysis algorithms, Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging, allow for the assessment of distribution of active ingredients in chocolate.

Detection of chicken DNA in commercial dog foods

BACKGROUND

These days the number of potential food allergens is very large, but chicken is one of the most common allergens in dogs. Elimination diet is one of the clinical tools for the diagnosis of allergies and allergy tests are not very reliable. The restriction diet is most commonly carried out by feeding pet foods, relying on the ingredients on the label to select an elimination diet not containing previously eaten foods. Unfortunately, mislabeling of pet food is quite common. The purpose of this study was to determine the absence or presence of chicken DNA using both qualitative and quantitative polymerase chain reaction (PCR) analysis methods in dry and wet maintenance complete pet foods for adult dogs. Results were used to verify the declared composition on the labels.

RESULTS

Eleven out of fifteen (73%) dog foods were produced as declared by the manufacturer, two of which showed the presence of chicken protein as stated on the label. The remaining nine foods contained amounts of chicken DNA below 1%, consistent with declarations that no chicken was added in the composition. Four of tested dog foods (27%) were not produced consistently with the declaration on the packaging. Two dog foods (one dry and one wet) did not contain the claimed chicken protein. In two foods the addition of chicken DNA was detected at the level of over 2% and almost 6%, respectively.

CONCLUSIONS

In this study, we focused on one of the most commonly undeclared animal species on the label-chicken protein-and performed DNA analyzes to investigate possible contamination and mislabeling. The results showed some inaccuracies. However, most of them are trace amounts below 1%, which proves compliance with the label. Our results showed that undeclared animal species can be as common as missing an animal protein declared on the label. The conducted research indicates that both dry and wet analyzed foods should not be recommended as a diagnostic tool in elimination tests, because it may result in false negative results. Over-the-counter maintenance foods for dogs should not be recommended for the diagnosis and treatment of food hypersensitivity.

Application of 13C Quantitative NMR Spectroscopy to Isotopic Analyses for Vanillin Authentication Source

The carbon stable isotope ratio (δ¹³C) is a valuable chemical parameter in the investigation of the geographic origin, quality, and authenticity of foods. The aim of this study is the evaluation of the feasibility of ¹³C-NMR (Nuclear Magnetic Resonance) spectroscopy to determine the carbon stable isotope ratio, at natural abundance, of small organic molecules, such as vanillin, without the use of IRMS (Isotope Ratio Mass Spectrometry). The determination of vanillin origin is an active task of research, and differentiating between its natural and artificial forms is important to guarantee the quality of food products. To reach our goal, nine vanillin samples were analyzed using both ¹³C quantitative NMR spectroscopy (under optimized experimental conditions) and IRMS, and the obtained δ¹³C values were compared using statistical analysis (linear regression, Bland–Altman plot, and ANOVA (analysis of variance)). The results of our study show that ¹³C-NMR spectroscopy can be used as a valuable alternative methodology to determine the bulk carbon isotope ratio and to identify the origin of vanillin. This makes it attractive for the analysis in the same experiment of site-specific and total isotope effects for testing authenticity, quality, and typicality of food samples. Moreover, the improvement of NMR spectroscopy makes it possible to avoid the influence of additives on carbon stable isotope ratio analysis and to clearly identify fraud and falsification in commercial samples.