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This study presents a fast, non-invasive method to determine the iodine value (IV) of edible oils using Time Domain Nuclear Magnetic Resonance (TD-NMR) and Magnetic Resonance Imaging (MRI) techniques. The IV, which quantifies the degree of unsaturation in fats and oils, is a key parameter in assessing oil quality and detecting potential adulteration. Different edible oils were used in this study (sunflower, soy, olive, sesame, and linseed). Statistically significant regression models (R2 > 0.92) were established between the IV derived from NMR spectra and the longitudinal (T1) and transverse (T2) relaxation times of the oils, which were obtained from MRI and TD-NMR analyses. The regression models obtained allow for the prediction of the IV from the T1 and T2 relaxation times across a range that includes predominantly mono- and polyunsaturated edible vegetable oils. The TD-NMR approach stands out for its speed (

Although antibiotics are the main therapy for bacterial infections, the reports showed that the overuse (or misuse) of antibiotics will results in several problems such as the development of antibiotic-resistant strains, persistence of drug residues, and numerous environmental concerns. Therefore, finding antibiotic alternatives is considered of vital importance. Investigation of the antimicrobial properties of several plant substances and extracts is of great value to replace antibiotics. With this objective, this study aimed to evaluate the antimicrobial activities of an ethanolic extract prepared from olive mill wastewater (OMWW), which is a by-product of olive oil production with considerable environmental burden, against 38 bacterial strains, including fish-associated pathogens, non-pathogenic isolates, collection strains, and one yeast strain, Candida albicans. Disk diffusion, minimum inhibitory concentration (MIC), and minimum bactericidal/fungicidal concentration (MBC/MFC) tests were used to determine the antimicrobial activity of the OMWWE. According to the results, OMWWE provoked strong inhibitory effects against Shewanella baltica strain SY-S145. It also showed a moderate inhibitory effect on Plesiomonas shigelloides strain SY-PS16 and Vibrio anguillarum strain SY-L24. The MIC and MBC of OMWWE on Shewanella baltica SY-S145, Vibrio gigantis strain C24, and V. anguillarum strain SY-L24 were 500 µg/mL. The MIC and MBC on V. parahaemolyticus ATCC 17802 were 1000 µg/mL, whereas the values for Aeromonas salmonicida ATCC 33658 were 500 µg/mL and 1000 µg/mL, respectively. To put it briefly, the OMWW extract showed high antimicrobial activity and can act as an environmentally friendly additive for the control and prevention of diseases caused by A. veronii, A. hydrophila, P. shigelloides, S. baltica, V. anguillarum, and V. parahaemolyticus. Its active agents also prevented infections of both fish-associated pathogens and food spoiling bacteria, which means it can not only help in the disease control mechanism but also in improving the safety of food by reduction of the microbial contamination.

This study presents the development of a sandwich ELISA method for gluten detection in foods, using recombinant Fab antibody fragments against gliadin. The Fabs were chemically biotinylated and immobilized on streptavidin-coated plates as capture antibodies, while alkaline phosphatase-conjugated Fabs were used as detection antibodies. Four different gliadin-binding Fabs were tested and the Fab pair Fab8E-4 and Fab-C showed the best compatibility. An indirect sandwich immunoassay, using unmodified Fab8E-4 for capture and Fab-C as the detection antibody, achieved a detection limit of 26 ng/mL of gliadin, corresponding to 10 mg/kg of gluten in foods. No cross-reactivity was observed against 60 gluten-free species commonly used in the food industry. Analysis of 50 commercial products demonstrated consistent results compared to the standard method for gluten detection. The complete lack of cross-reactivity of the developed immunoassay with oat products potentially provides an advantage over other gluten detection systems.

The search for natural food additives makes propolis an exciting alternative due to its known antimicrobial activity. This work aims to investigate propolis’ behavior as a nitrite substitute ingredient in cooked ham (a ready-to-eat product) when confronted with pathogenic microorganisms of food interest. The microbial evolution of Listeria monocytogenes, Staphylococcus aureus, Bacillus cereus, and Clostridium sporogenes inoculated at known doses was examined in different batches of cooked ham. The design of a challenge test according to their shelf life (45 days), pH values, and water activity allowed the determination of the mesophilic aerobic flora, psychotropic, and acid lactic bacteria viability. The test was completed with an organoleptic analysis of the samples, considering possible alterations in color and texture. The cooked ham formulation containing propolis instead of nitrites limited the potential growth (δ < 0.5 log10) of all the inoculated microorganisms until day 45, except for L. monocytogenes, which in turn exhibited a bacteriostatic effect between day 7 and 30 of the storage time. The sensory analysis revealed the consumer’s acceptance of cooked ham batches including propolis as a natural additive. These findings suggest the functionality of propolis as a promising alternative to artificial preservatives for ensuring food safety and reducing the proliferation risk of foodborne pathogens in ready-to-eat products.

Consumers in developed and Western European countries are becoming more aware of the impact of food on their health, and they demand clear, transparent, and reliable information from the food industry about the products they consume. They recognise that food safety risks are often due to the unexpected presence of contaminants throughout the food supply chain. Among these, mycotoxins produced by food-infecting fungi, endogenous toxins from certain plants and organisms, pesticides, and other drugs used excessively during farming and food production, which lead to their contamination and accumulation in foodstuffs, are the main causes of concern. In this context, the goals of this review are to provide a comprehensive overview of the presence of toxic molecules reported in foodstuffs since 2020 through the Rapid Alert System for Food and Feed (RASFF) portal and use chromatography to address this challenge. Overall, natural toxins, environmental pollutants, and food-processing contaminants are the most frequently reported toxic molecules, and liquid chromatography and gas chromatography are the most reliable approaches for their control. However, faster, simpler, and more powerful analytical procedures are necessary to cope with the growing pressures on the food chain supply.

Recently, a genetically modified microorganism (GMM) detection strategy using real-time PCR technology was developed to control fermentation products commercialized in the food and feed chain, allowing several unexpected GMM contaminations to be highlighted. Currently, only bacterial strains are targeted by this strategy. Given that fungal strains, like Trichoderma reesei, are also frequently used by the food industry to produce fermentation products, a novel real-time PCR method specific to this fungal species was developed and validated in this study to reinforce the GMM detection strategy. Designed to cover a sequence of 130 bp from the translation elongation factor alpha 1 (Tef1) gene of T. reesei, this real-time PCR method, namely TR, allows for the screening of commercial fermentation products contaminated with T. reesei, genetically modified or not, which is one of the major fungal species used as an industrial platform for the manufacturing of fermentation products. The developed real-time PCR TR method was assessed as specific and sensitive (LOD95% = eight copies). In addition, the developed real-time PCR TR method performance was confirmed to be in line with the “Minimum Performance Requirements for Analytical Methods of GMO Testing” of the European Network of GMO Laboratories. The validated real-time PCR TR method was also demonstrated to be applicable to commercial microbial fermentation products. Based on all these results, the novel real-time PCR TR method was assessed as valuable for strengthening the current GMM detection strategy regarding major fungal species used by the food industry to produce microbial fermentation products.

Fruit juice and wine are important beverages that are consumed all over the world. Due to their constantly increasing demand and high value, fruit juice and wine are one of the most frequent targets of adulteration. Since adulterated foods are proven to have harmful effects on health, several approaches have been utilized for the detection of fruit juice and wine adulteration. Based on the requirement for sample destruction, analytical techniques to assess food authenticity can be classified into 2 main categories, i.e., destructive and non-destructive techniques. This paper provides an overview on the principle of adulteration detection, its application and performance, and the advantages and limitations of various analytical techniques. Destructive approaches, such as physicochemical methods, isotope analysis, elemental analysis, chromatographic techniques, and DNA-based techniques, are reviewed. Furthermore, non-destructive approaches, including spectroscopic-based techniques, nuclear magnetic resonance spectroscopic technique, electronic techniques, and imaging-based techniques, are discussed.

Matsutake mushrooms, known for their high value, present challenges due to their seasonal availability, difficulties in harvesting, and short shelf life, making it crucial to extend their post-harvest preservation period. In this study, we developed three quality predictive models of Matsutake mushrooms using three different methods. The quality changes of Matsutake mushrooms were experimentally analyzed under two cases (case A: Temperature control and sealing measures; case B: Alteration of gas composition) with various parameters including the hardness, color, odor, pH, soluble solids content (SSC), and moisture content (MC) collected as indicators of quality changes throughout the storage period. Prediction models for Matsutake mushroom quality were developed using three different methods based on the collected data: multiple linear regression (MLR), support vector regression (SVR), and an artificial neural network (ANN). The comparative results reveal that the ANN outperforms MLR and SVR as the optimal model for predicting Matsutake mushroom quality indicators. To further enhance the ANN model’s performance, optimization techniques such as the Levenberg–Marquardt, Bayesian regularization, and scaled conjugate gradient backpropagation algorithm techniques were employed. The optimized ANN model achieved impressive results, with an R-Square value of 0.988 and an MSE of 0.099 under case A, and an R-Square of 0.981 and an MSE of 0.164 under case B. These findings provide valuable insights for the development of new preservation methods, contributing to the assurance of a high-quality supply of Matsutake mushrooms in the market.

Cold chain disruption and refrigeration failures are common issues in the logistics of perishable food products. In these cases, the use of pallet covers should be very useful, delaying the increase of product temperatures inside the pallets until cooling conditions are restored. However, there are no studies about the performance of pallet covers in these types of situations, which could persist for hours. This paper evaluates the performance of three different types of cold chain covers versus having no cover for three different types of vegetables (chard, cucumbers, and carrots). A refrigeration failure during the cold chain was simulated. The three covers presented an improvement in temperature loss compared to the no-cover situation, with the average time for the temperature to increase from 4 to 10 °C with a cover being a range of 214 to 506 min, while for no cover, from 162 to 211 min. Relative humidity (RH) always presented improved preservation with a cover than with no cover, except for one case. The correlation between the thermal images and sensor temperatures was also studied.

Food authenticity is becoming increasingly important to consumers, producers, and retailers. Furthermore, more and more food properties considered to be value-relevant are advertised. Food fraud, which is the intentional misrepresentation of a food’s true qualities, not only harms buyers but also undermines confidence in entire market segments. Worldwide coffee production has had a rising trend despite some setbacks in recent years. Global consumption is also increasing and has only been slightly attenuated by phases of economic weakness. For example, the appetite for coffee in Germany has been growing over the years, with an average consumption of 450 cups per person in 2022, which is equivalent to 5.4 kg of coffee. The top coffee-loving countries consume around 10 kg of coffee per person per year. The rising demand for higher quality coffee with declared origin, botanical variety, and/or processing methods, combined with the significantly higher market prices for such specialty coffee, are opportunities for food fraudsters. In addition to compliance visits to production and processing sites and to auditing a company’s accounting, well-established standardised and efficient laboratory analyses are an important part in fighting food fraud. As a metrological primary method of measurement, nuclear magnetic resonance spectrometry (NMR) has been increasingly used for routine chemical quantitative analysis. The NMR spectra typically show very good signal resolution, excellent reproducibility, and linearity of response independent of the substance. NMR can record signals from most metabolites in a biological sample with a single experiment in just a few minutes. Thus, NMR has a high potential to provide reliable data for the analysis of complex mixtures, such as food extracts. NMR spectra can be used as fingerprints to compare individual samples against databases of authentic references using multivariate analysis. This talk will present recent research on the potential of using NMR with targeted, quantitative analysis and also with non-targeted multivariate analysis to verify several product claims on roasted coffee, i.e. the geographical origin, botanical variety, and farming method (organic/conventional). By using targeted analysis, over a dozen characteristic substances can be quantified with good precision. The chemometrical evaluation of NMR spectra can raise reasonable suspicion about the geographical origin.

The presence of chemical contaminants, toxins, or veterinary drugs in milk, as well as the adulteration of milk from different species, has driven the development of new tools to ensure safety and quality. Several analytical procedures have been proposed for the rapid screening of hazardous substances or the selective confirmation of the authenticity of milk. Mid-infrared spectroscopy and Fourier-transform infrared have been two of the most relevant technologies conventionally employed in the dairy industry. These fingerprint methodologies can be very powerful in determining the trait of raw material without knowing the identity of each constituent, and several aspects suggest their potential as a screening method to detect adulteration. This paper reviews the latest advances in applying mid-infrared spectroscopy for the detection and quantification of adulterants, milk dilution, the presence of pathogenic bacteria, veterinary drugs, and hazardous substances in milk.

This study examines the occurrence of the artificial sweetener aspartame (E951) in foods and beverages sampled by food control authorities in Germany between 2000 and 2022. The dataset was obtained through the Consumer Information Act. Out of 53,116 samples analyzed, aspartame was present in 7331 samples (14%), of which 5703 samples (11%) in nine major food groups were further evaluated. The results showed that aspartame was most commonly found in powdered drink bases (84%), flavored milk drinks (78%), chewing gum (77%), and diet soft drinks (72%). In the solid food groups, the highest mean aspartame content was detected in chewing gum (1543 mg/kg, n = 241), followed by sports foods (1453 mg/kg, n = 125), fiber supplements (1248 mg/kg, n = 11), powdered drink bases (1068 mg/kg, n = 162), and candies (437 mg/kg, n = 339). Liquid products generally had the highest aspartame content in diet soft drinks (91 mg/L, n = 2021), followed by regular soft drinks (59 mg/L, n = 574), flavored milk drinks (48 mg/kg, n = 207), and mixed beer drinks (24 mg/L, n = 40). These results suggest that aspartame is commonly used in some foods and beverages in Germany. The levels of aspartame found were generally within the legal limits set by the European Union. These findings provide the first comprehensive overview of aspartame in the German food market and may be particularly useful in informing the forthcoming working groups of the WHO International Agency for Research on Cancer (IARC) and the WHO/FAO Joint Expert Committee on Food Additives (JECFA), which are in the process of evaluating the human health hazards and risks associated with the consumption of aspartame.

Assessment of the composition of meat-containing products is the task in demand due to their frequent deviations from declared recipes. The paper presents the developed test system for immunochromatographic determination of total meat content. The assay is based on the simultaneous use of monoclonal antibodies, which specifically interacts with mammalian skeletal troponin I, and polyclonal antibodies, which specifically detect bird immunoglobulin Y. To integrate the detection of both types of meat by the same test strip, the antibodies are mixed in the analytical zone of the test strip and in complex with a gold nanoparticle label. The chosen ratios of the antibodies for both mixtures provide the same contribution of different types of mammalian and bird raw materials of muscle tissues to the label binding. The test system demonstrates suitability for products containing beef, pork, rabbit, lamb, chicken, and turkey meat. The minimal detectable content of meat in samples is 0.1%. The samples for the testing are diluted 100 times, thus eliminating matrix effects, and providing high reproducibility of the color intensity for extracts of different compositions. The obtained results allow the recommendation of the developed test system for rapid on-site control of meat products.

Fruit juices are one of the most adulterated beverages, usually because of the addition of water, sugars, or less expensive fruit juices. This study presents a method based on Fourier transform infrared spectroscopy (FT-IR), in combination with machine learning methods, for the correct identification and quantification of adulterants in juices. Thus, three types of 100% squeezed juices (pineapple, orange, and apple) were evaluated and adulterated with grape juice at different percentages (5%, 10%, 15%, 20%, 30%, 40%, and 50%). The results of the exploratory data analysis revealed a clear clustering trend of the samples according to the type of juice analyzed. The supervised learning analysis, based on the development of models for the detection of adulteration, obtained significant results for all tested methods (i.e., support-vector machines or SVM), random forest or RF, and linear discriminant analysis or LDA) with an accuracy above 97% on the test set. Regarding quantification, the best results are obtained with the support vector regression and with partial least square regression showing an R2 greater than 0.99 and a root mean square error (RMSE) less than 1.4 for the test set.

Food additives are in widespread use in the food industry to extend the shelf life of food, improve its organoleptic characteristics or facilitate industrial processing. Their use is not without controversy, which makes regulation and control crucial for food safety and public health. Among food additives, silicone-based antifoaming agents (polysiloxanes or E900) are difficult to analyze and quantify due to their polymeric nature. Currently, there is no official method of quantifying this additive in foods. In this context, nuclear magnetic resonance (NMR) is a quantitative method for speciation analysis of silicon compounds almost without known interferents. In this work, we describe the evolution of the regulation of the E900 additive, discuss different analytic methods quantifying polydimethylsiloxanes (PDMS), and propose a new method based on NMR suitable for analyzing the content of E900 in the form of PDMS in various types of food from dietary oils to marmalades and jellies, among others. The proposed method consists of a previous quantitative concentration of PDMS by liquid–liquid extraction and the monitoring of the quantification using a bis(trimethylsilyl)benzene (BTMSB) standard to control the variability, ranging within 2–7%, depending on the food. This simple, direct, and reproducible procedure for aqueous and lipidic foods may help to monitor and fill a gap in regulatory legislation regarding the E900 additive.

The leaves of the coffee plant Coffea are traditionally used in several countries worldwide to prepare tea-like beverages using aqueous infusion in hot water. There are currently no tested methods available to check the regulatory compliance of coffee leaf tea according to the European Union (EU) novel food authorization. This study shows that standard ISO methods for tea analysis could be transferred without modifications to coffee leaf tea analysis. The only difference found was a much lower content of some catechins in coffee leaf tea compared to Camellia sinensis tea, but the methods were clearly applicable for use in controlling the EU’s maximum limits for coffee leaf tea.

Cronobacter genus bacteria are food-borne pathogens. Foods contaminated with Cronobacter spp. may pose a risk to infants or immunocompromised adults. The aim of this study was to determine the microbiological quality of nuts, seeds and dried fruits with special emphasis on the occurrence of Cronobacter spp. Analyses were carried out on 64 samples of commercial nuts (20 samples), dried fruits (24), candied fruits (8), seeds (4), and mixes of seeds, dried fruits and nuts (8). The samples were tested for the total plate count of bacteria (TPC), counts of yeasts and molds, and the occurrence of Cronobacter spp. Cronobacter isolates were identified and differentiated by PCR-RFLP (Polymerase Chain Reaction - Restriction Fragments Length Polymorphism) and RAPD-PCR (Random Amplified Polymorphic DNA by PCR) analysis. TPC, and yeasts and molds were not detected in 0.1 g of 23.4%, 89.1%, and 32.8% of the analyzed samples. In the remaining samples, TPC were in the range of 1.2–5.3 log CFU g−1. The presence/absence of Cronobacter species was detected in 12 (18.8%) samples of: nuts (10 samples), and mixes (2 samples). The 12 strains of Cronobacter spp. included: C. sakazakii (3 strains), C. malonaticus (5), and C. turicensis (4). The results of this study contribute to the determination of the presence and species identification of Cronobacter spp. in products of plant origin intended for direct consumption.

Sweeteners have been used in food for centuries to increase both taste and appearance. However, the consumption of sweeteners, mainly sugars, has an adverse effect on human health when consumed in excessive doses for a certain period, including alteration in gut microbiota, obesity, and diabetes. Therefore, the application of non-nutritive sweeteners in foodstuffs has risen dramatically in the last decade to substitute sugars. These sweeteners are commonly recognized as high-intensity sweeteners because, in a lower amount, they could achieve the same sweetness of sugar. Regulatory authorities and supervisory agencies around the globe have established the maximum amount of these high-intensity sweeteners used in food products. While the regulation is getting tighter on the market to ensure food safety, reliable analytical methods are required to assist the surveillance in monitoring the use of high-intensity sweeteners. Hence, it is also necessary to comprehend the most appropriate method for rapid and effective analyses applied for quality control in food industries, surveillance and monitoring on the market, etc. Apart from various analytical methods discussed here, extraction techniques, as an essential step of sample preparation, are also highlighted. The proper procedure, efficiency, and the use of solvents are discussed in this review to assist in selecting a suitable extraction method for a food matrix. Single- and multianalyte analyses of sweeteners are also described, employing various regular techniques, such as HPLC, and advanced techniques. Furthermore, to support on-site surveillance of sweeteners’ usage in food products on the market, non-destructive analytical methods that provide practical, fast, and relatively low-cost analysis are widely implemented.

The application of stilbenes in the food industry is being considered because of their biological activities. Piceatannol, pterostilbene and ε-viniferin have awakened the industry’s interest. However, before they can be commercialized, we must first guarantee their safety for consumers. The present work reviews the toxicological studies performed with these stilbenes. A wide variety of studies has demonstrated their cytotoxic effects in both cancer and non-cancerous cell lines. In contrast, although DNA damage was detected by some authors, in vitro genotoxic studies on the effects of piceatannol, pterostilbene, and ε-viniferin remain scarce. None of the three reviewed substances have been evaluated using the in vitro tests required by the European Food Safety Authority (EFSA) as the first step in genotoxicity testing. We did not find any study on the toxic effects of these stilbenes in vivo. Thus, more studies are needed to confirm their safe use before they can be authorized as additive in the food industry.

Understanding food safety hazard risks is essential to avoid potential negative heath impacts in the food supply chain in a post-COVID-19 pandemic era. Development of strategies for virus direction in foods plays an important role in food safety and verification. Early warning, tracing, and detection should be implemented as an integrated system in order to mitigate thecoronavirus disease 2019 (COVID-19) outbreak, in which the detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is critical as it not only concerns screening of populations but also monitoring of possible contaminated sources such as the food supply chain. In this review, we point out the consequences in different aspects of our daily life in the post-COVID-19 pandemic from the perspective of the food supply chain and the food industry. We summarize the possible transmission routes of COVID-19 in the food supply chain before exploring the development of corresponding detection tools of SARS-CoV-2. Accordingly, we compare different detection methods for the virus in foods, including different pretreatments of food matrices in the virus detection. Finally, the future perspectives are proposed.

According to the EU legislation, ochratoxin A contamination is controlled in wines. Tokaj wine is a special type of sweet wine produced from botrytized grapes infected by “noble rot” Botrytis cinerea. Although a high contamination was reported in sweet wines and noble rot grapes could be susceptible to coinfection with other fungi, including ochratoxigenic species, no screening of Tokaj wines for mycotoxin contamination has been carried out so far. Therefore, we developed an analytical method for the determination of ochratoxin A (OTA) and ochratoxin B (OTB) involving online SPE coupled to HPLC-FD using column switching to achieve the fast and sensitive control of mycotoxin contamination. The method was validated with recoveries ranging from 91.6% to 99.1% with an RSD less than 2%. The limits of quantification were 0.1 and 0.2 µg L−1 for OTA and OTB, respectively. The total analysis time of the online SPE-HPLC-FD method was a mere 6 min. This high throughput enables routine analysis. Finally, we carried out an extensive investigation of the ochratoxin contamination in 59 Slovak Tokaj wines of 1959–2017 vintage. Only a few positives were detected. The OTA content in most of the checked wines did not exceed the EU maximum tolerable limit of 2 µg L−1, indicating a good quality of winegrowing and storing.

Pesticides are among the most important contaminants in food, leading to important global health problems. While conventional techniques such as high-performance liquid chromatography (HPLC) and mass spectrometry (MS) have traditionally been utilized for the detection of such food contaminants, they are relatively expensive, time-consuming and labor intensive, limiting their use for point-of-care (POC) applications. Electrochemical (bio)sensors are emerging devices meeting such expectations, since they represent reliable, simple, cheap, portable, selective and easy to use analytical tools that can be used outside the laboratories by non-specialized personnel. Screen-printed electrodes (SPEs) stand out from the variety of transducers used in electrochemical (bio)sensing because of their small size, high integration, low cost and ability to measure in few microliters of sample. In this context, in this review article, we summarize and discuss about the use of SPEs as analytical tools in the development of (bio)sensors for pesticides of interest for food control. Finally, aspects related to the analytical performance of the developed (bio)sensors together with prospects for future improvements are discussed.

Scientific research in the nanomaterials field is constantly evolving, making it possible to develop new materials and above all to find new applications. Therefore, nanoparticles (NPs) are suitable for different applications: nanomedicine, drug delivery, sensors, optoelectronics and food control. This review explores the recent trend in food control of using noble metallic nanoparticles as determination tools. Two major uses of NPs in food control have been found: the determination of contaminants and bioactive compounds. Applications were found for the determination of mycotoxins, pesticides, drug residues, allergens, probable carcinogenic compounds, bacteria, amino acids, gluten and antioxidants. The new developed methods are competitive for their use in food control, demonstrated by their validation and application to real samples.

Various fruit and vegetable wastes, particularly peels, seeds, pulp, and unprocessed residues from the food industry, are abundant sources of antioxidants and essential antimicrobial agents. These valuable bioactive compounds recovered from the food industry have a great application in food, agriculture, medicine, and pharmacology. Food-derived natural antimicrobials offer advantages such as diminishing microbial loads and prolonging the shelf life of food products particularly prone to microbial spoilage. They not only enrich the foods with antioxidants but also help prevent microbial contamination, thereby prolonging their shelf life. Similarly, incorporating these natural antimicrobials into food packaging products extends the shelf life of meat products. Moreover, in agricultural practices, these natural antimicrobials act as eco-friendly pesticides, eliminating phytopathogenic microbes responsible for causing plant diseases. In medicine and pharmacology, they are being explored as potential therapeutic agents. This review article is based on current studies conducted in the last four years, evaluating the effectiveness of food-based natural antimicrobials in food, agriculture, medicine, and pharmacology.

Plant phenolic compounds demonstrate bioactive properties in vitro and/or in vivo, which creates demand for their precise determination in life sciences and industry. Measuring the concentration of individual phenolic compounds is a complex task, since approximately 9000 plant phenolic substances have been identified so far. The determination of the total phenolic content (TPC) is less laborious and is used for the qualimetric evaluation of complex multicomponent samples in routine analyses. Biosensors based on phenol oxidases (POs) have been proposed as alternative analytical devices for detecting phenolic compounds; however, their effectiveness in the analysis of food and vegetal matrices has not been addressed in detail. This review describes catalytic properties of laccase and tyrosinase and reports on the enzymatic and bienzymatic sensors based on laccase and tyrosinase for estimating the total phenolic index (TPI) in food-related samples (FRSs). The review presents the classification of biosensors, POs immobilization, the functions of nanomaterials, the biosensing catalytic cycle, interference, validation, and some other aspects related to TPI assessment. Nanomaterials are involved in the processes of immobilization, electron transfer, signal formation, and amplification, and they improve the performance of PO-based biosensors. Possible strategies for reducing interference in PO-based biosensors are discussed, namely the removal of ascorbic acid and the use of highly purified enzymes.

This work aimed to investigate the bio-distribution and the persistence of fipronil and its primary metabolite fipronil sulfone after oral and dermal administration by simulating natural farming conditions. Fipronil and fipronil sulfone detection and quantification were performed in different poultry matrices using an LC-MS/MS method coupled with modified QuEChERS extraction. After oral administration, fipronil was detected in feathers at each sampling time, in eggs for 28 days, and in the internal organs at the end of the experiment. After dermal administration, high levels of fipronil were detected in feathers, accounting for 195.85 ± 8.54 mg/kg, which were reduced by a third after 60 days. No traces of fipronil were detected in the eggs or internal organs. In addition, fipronil sulfone showed remarkable residues in all samples in trial 2. The data obtained confirmed that inappropriate use of unauthorized pesticides can lead to severe contamination of entire poultry farms. The contemporary presence of fipronil sulfone in feathers and eggs associated with the lack of fipronil in eggs suggests recent dermal contamination or past oral contamination. Moreover, simultaneous analysis of hens' feathers and eggs could represent a new method to improve large-scale monitoring programs and animal welfare, limiting their slaughter.

Due to legal regulations, the rise of globalised (online) commerce and the need for public health protection, the analysis of spirit drinks (alcoholic beverages >15% vol) is a task with growing importance for governmental and commercial laboratories. In this article a newly developed method using nuclear magnetic resonance (NMR) spectroscopy for the simultaneous determination of 15 substances relevant to assessing the quality and authenticity of spirit drinks is described. The new method starts with a simple and rapid sample preparation and does not need an internal standard. For each sample, a group of 1 H-NMR spectra is recorded, among them a two-dimensional spectrum for analyte identification and one-dimensional spectra with suppression of solvent signals for quantification. Using the Pulse Length Based Concentration Determination (PULCON) method, concentrations are calculated from curve fits of the characteristic signals for each analyte. The optimisation of the spectra, their evaluation and the transfer of the results are done fully automatically. Glucose, fructose, sucrose, acetic acid, citric acid, formic acid, ethyl acetate, ethyl lactate, acetaldehyde, methanol, n-propanol, isobutanol, isopentanol, 2-phenylethanol and 5-(hydroxymethyl)furfural (HMF) can be quantified with an overall accuracy better than 8%. This new NMR-based targeted quantification method enables the simultaneous and efficient quantification of relevant spirit drinks ingredients in their typical concentration ranges in one process with good accuracy. It has proven to be a reliable method for all kinds of spirit drinks in routine food control.