Blockchain implementation for food safety in supply chain: A review.

Food safety has emerged as the topmost priority in the current fast-paced food industry era. According to the World Health Organization, around 600 million people, approximately 1 in 10 individuals worldwide, experience illness due to contaminated food consumption, resulting in nearly 0.42 million fatalities annually. The recent development in software and hardware sectors has created opportunities to improve the safety concerns in the food supply chain. The objective of this review is to explain the fundamentals of blockchain and its integration into the supply chain of various food commodities to enhance food safety. This paper presents the analysis of 31 conceptual works, 10 implementation works, 39 case studies, and other investigations in blockchain-based food supply chain from a total of 80 published papers. In this paper, the significance of adapting conceptual ideas into practical applications for effectively tracing food commodities throughout the supply chain has been discussed. This paper also describes the transformative role of blockchain platforms in the food industry, providing a decentralized and transparent ledger to access real-time and immutable records of a product's journey. In addition, both the positive impacts and challenges associated with implementing blockchain technology in the food supply chain have been evaluated. In summary, the blockchain-based food supply chains offer greater transparency, traceability, and trust, ultimately resulting in higher standards of food safety and quality.

Artificial intelligence decision making tools in food metabolomics: Data fusion unravels synergies within the hazelnut (Corylus avellana L.) metabolome and improves quality prediction.

This study investigates the metabolome of high-quality hazelnuts (Corylus avellana L.) by applying untargeted and targeted metabolome profiling techniques to predict industrial quality. Utilizing comprehensive two-dimensional gas chromatography and liquid chromatography coupled with high-resolution mass spectrometry, the research characterizes the non-volatile (primary and specialized metabolites) and volatile metabolomes. Data fusion techniques, including low-level (LLDF) and mid-level (MLDF), are applied to enhance classification performance. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal that geographical origin and postharvest practices significantly impact the specialized metabolome, while storage conditions and duration influence the volatilome. The study demonstrates that MLDF approaches, particularly supervised MLDF, outperform single-fraction analyses in predictive accuracy. Key findings include the identification of metabolites patterns causally correlated to hazelnut's quality attributes, of them aldehydes, alcohols, terpenes, and phenolic compounds as most informative. The integration of multiple analytical platforms and data fusion methods shows promise in refining quality assessments and optimizing storage and processing conditions for the food industry.

A Microbial Phenomics Approach to Determine Metabolic Signatures to Enhance Seabream Sparus aurata Traceability, Differentiating between Wild-Caught and Farmed.

BACKGROUND: The need for efficient and simplified techniques for seafood traceability is growing. This study proposes the Biolog EcoPlate assay as an innovative method for assessing wild and farmed Sparus aurata traceability, offering advantages over other molecular techniques in terms of technical simplicity. METHODS: The Biolog EcoPlate assay, known for its high-throughput capabilities in microbial ecology, was utilized to evaluate the functional diversity of microbial communities from various organs of S. aurata (seabream) from the Mediterranean area. Samples were taken from the anterior and posterior gut, cloaca swabs and gills to distinguish between farmed and wild-caught individuals. The analysis focused on color development in OmniLog Units for specific carbon sources at 48 h. RESULTS: Gills provided the most accurate clusterization of sample origin. The assay monitored the development of color for carbon sources such as α-cyclodextrin, D-cellobiose, glycogen, α-D-lactose, L-threonine and L-phenylalanine. A mock experiment using principal component analysis (PCA) successfully identified the origin of a blind sample. Shannon and Simpson indexes were used to statistically assess the diversity, reflecting the clusterization of different organ samples; Conclusions: The Biolog EcoPlate assay proves to be a quick, cost-effective method for discriminate S. aurata traceability (wild vs. farmed), demonstrating reliable reproducibility and effective differentiation between farmed and wild-caught seabream.

Towards Reducing Food Wastage: Analysis of Degradation Products Formed during Meat Spoilage under Different Conditions.

Foodstuffs, particularly perishable ones such as meat, are frequently discarded once the best-before date has been reached, despite the possibility of their continued suitability for human consumption. The implementation of intelligent packaging has the potential to contribute to a reduction in food wastage by enabling the monitoring of meat freshness during storage time independently of the best-before date. The process of meat spoilage is associated with the formation of specific degradation products, some of which can be potentially utilized as spoilage indicators in intelligent packaging. The aim of the review is to identify degradation products whose concentration correlates with meat shelf life and to evaluate their potential use as spoilage indicators in intelligent packaging. To this end, a comprehensive literature research was conducted to identify the factors influencing meat spoilage and the eight key degradation products (carboxylic acids, biogenic amines, total volatile basic nitrogen, aldehydes, alcohols, ketones, sulfur compounds, and esters) associated with this process. These degradation products were analyzed for their correlation with meat shelf life at different temperatures, atmospheres, and meat types and for their applicability in intelligent packaging. The review provides an overview of these degradation products, comparing their potential to indicate spoilage across different meat types and storage conditions. The findings suggest that while no single degradation product universally indicates spoilage across all meat types and conditions, compounds like carboxylic acids, biogenic amines, and volatile basic nitrogen warrant further investigation. The review elucidates the intricacies inherent in identifying a singular spoilage indicator but underscores the potential of combining specific degradation products to expand the scope of applications in intelligent packaging. Further research (e.g., storage tests in which the concentrations of these substances are specifically examined or research on which indicator substance responds to these degradation products) is recommended to explore these combinations with a view to broadening their applicability.

UPRER-immunity axis acts as physiological food evaluation system that promotes aversion behavior in sensing low-quality food.

To survive in challenging environments, animals must develop a system to assess food quality and adjust their feeding behavior accordingly. However, the mechanisms that regulate this chronic physiological food evaluation system, which monitors specific nutrients from ingested food and influences food-response behavior, are still not fully understood. Here, we established a low-quality food evaluation assay system and found that heat-killed E. coli (HK-E. coli), a low-sugar food, triggers cellular UPRER and immune response. This encourages animals to avoid low-quality food. The physiological system for evaluating low-quality food depends on the UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis, particularly its neuronal function, which subsequently regulates feeding behaviors. Moreover, animals can adapt to a low-quality food environment through sugar supplementation, which inhibits the UPRER -PMK-1 regulated stress response by increasing vitamin C biosynthesis. This study reveals the role of the cellular stress response pathway as physiological food evaluation system for assessing nutritional deficiencies in food, thereby enhancing survival in natural environments.

We quickly learn to steer clear of eating the moldy apple, the foul-smelling piece of chicken or the leftovers that taste a little 'off'. This survival instinct is shared across most animal species ­ even those with extremely simple and limited visual or taste systems, like the tiny worm Caenorhabditis elegans. Indeed, assessing the safety and quality of available food items can also rely on cells activating built-in cascades of molecular reactions. However, it remains unclear how these 'cellular stress response programs' actually help guide feeding behaviors. To better understand this process, Liu et al. conducted a series of experiments using C. elegans worms exposed to heat-killed bacteria, which are devoid of many nutrients essential for growth. After initially consuming these bacteria, the worms quickly started to avoid feeding on this type of low-quality food. This suggests that mechanisms occurring after ingestion allowed the worms to adjust their feeding choices. Further work showed that the consumption of heat-killed bacteria triggered two essential stress response pathways, known as the unfolded protein response and the innate immune response. The activation of these pathways was essential for the animals to be able to change their behavior and avoid the heat-killed bacteria. These biochemical pathways were particularly active in the worms' nerve cells, highlighting the importance of these cells in sensing and reacting to food. Finally, Liu et al. also found that adding sugars like lactose and sucrose to the low-quality food could prevent the activation of the stress response pathways. This result suggests that specific nutrients play a central role in how these worms decide what to eat. These findings shed light on the complex systems that ensure organisms consume the nutritious food they need to survive. Understanding these processes in worms can provide insights into the broader biological mechanisms that help animals avoid harmful food.

Manothermosonication - A potential alternative to thermal pasteurisation of liquid whole egg: Comparison of physico-chemical attributes.

Liquid egg products are typically exposed to a defined thermal load to achieve the required safety level, under which their functional properties can be adversely affected. In this study, manothermosonication (MTS) (132 µm, 300 kPa) was investigated as alternative preservation for liquid whole egg (LWE) compared to thermal pasteurisation (60 °C, 3.5 min), assessing results against untreated (fresh) LWE in terms of selected physico-chemical properties. Results showed that MTS resulted in improved LWE foaming properties, increasing foam capacity by a 3.2-fold factor compared to thermal treatment. Emulsion stability was also enhanced after MTS, exhibiting smaller droplet size, and a higher elasticity of gels was obtained. Regarding the protein properties, favourable protein changes (protein unfolding) were identified for MTS through direct (asymmetric flow field flow fractionation) and indirect (surface hydrophobicity and sulfhydryl group content) measurements. In addition, an increase in protein solubility of 11.4 % was observed in MTS compared to thermal treatment.

Predicting the properties of wheat flour from grains during debranning: A machine learning approach.

In the food industry, meeting food quality demands is challenging. The quality of wheat flour, one of the most commonly used ingredients, depends on the extent of debranning done to remove the aleurone layer before milling. Therefore, the end product management can be simplified by predicting the properties of wheat flour during the debranning stage. Therefore, the chemical and rheological properties of grains were analyzed at different debranning durations (0, 30, 60 s). Then the images of wheat grain were taken to develop a regression model for predicting the chemical quality (i.e., ash, starch, fat, and protein contents) of the wheat flour. The resulting regression model comprises a convolutional neural network and is evaluated using the coefficient of determination (R 2), root-mean-square error, and mean absolute error as metrics. The results demonstrated that wheat flour contained more fat and protein and less ash with increasing debranning time. The model proved reliable in terms of root-mean-square error, mean absolute error, and R 2 for predicting ash content but not starch, fat, or protein contents, which can be attributed to the lack of features in the collected images of wheat kernels during debranning. In addition, the selected method, debranning, was beneficial to the rheological characteristics of wheat flour. The proportion of fine particles increased with the debranning time. The study experimentally revealed that the end product diversity for wheat flour can be controlled to provide selectable ingredients to customers.

Formulation of complementary flours from pretreated pumpkin pulp, soybeans and spinach leaves: Nutritional, functional and sensory characterization.

One of the major causes of the high prevalence of young children suffering from malnutrition in developed countries is inadequate complementary feeding practices, and especially the low quality of homemade complementary foods. The present study aimed to use available local plant foods to formulate a complementary flour Which can be able to meet energy and nutrients requirements of children aged from 6 to 23 months. To achieve this goal, pumpkin was fermented, soybean soaked and roasted, and spinach steamed. The pre-treated ingredients were ground to obtain individual flours, which were blended in various proportions to obtain four complementary flours (PSS1, PSS2, PSS3, PSS4). The proximate and micronutrient composition, and the energy value of the blends were determined, and based on the results, two of them, that is; (PSS1 [Pumpkin 70 %/Soybean 25 %/Spinach 5 %], and PSS2 [Pumpkin 65 %/Soybean 25 %/Spinach 10 %]) were selected to pursue the Study. The functional properties (water absorption capacity, water solubility index, bulk density) and pasting properties of these two flours were then evaluated. Gruels were prepared from the flours and their energy densities, physical as well as sensory properties were evaluated. Moisture, ash, protein, fat, and sugar contents of PSS1 and PSS2 met the FAO/WHO standards. Fiber content in both flours was higher than the recommendation. Vitamin A and iron were sufficient in PSS2, while PSS1 had low iron content. Calcium, phosphorus, and magnesium content of PSS1 and PSS2 were significantly higher than the standards. PSS1 and PSS2 had good water absorption capacity and solubility index, with low viscosity values (213 and 173 cP respectively), interesting functional properties for complementary flours. The gruels prepared with PSS1 and PSS2 flours had good fluidity and energy densities. They were fairly appreciated based on their organoleptic characteristics, with scores of 5.96 and 5.75 for overall acceptability. PSS2 could be recommended as infant flour rich in iron, vitamin A, and protein, with good nutritional values and functional properties.

Tracking perishable foods in the supply chain using chain of things technology.

Modern food supply chains are intrinsically sophisticated due to their multi-participant and multi-echelon structure, which are challenging to handle high turbulent business environment. The development of Perishable Food Supply Chains (PFSC) has to be strong enough to manage any type of disruptions in the food industry. At the same time, the food processing industry must also take responsibility for the social and environmental consequences of their deeds. This has further led to performance deterioration and intensified design complexity. Recently, digitalization and Blockchain technology (BCT) have brought unfathomed rebellions in PFSC. Despite the potential and market hype, the application of BCT to track the perishable products and status of in-transit shipments is still a challengingtask for the food industry due to privacy and security issues, restricted transactional and scalability performance, deficiency of industry standards and managerial abilities, etc. However, integrating the BCT with the eventual benefits of the Internet of Things (IoT) (i.e., Chain of Things (CoT)) increases the performance of good traceability in any supply chain. The proposed CoT-based Track and Trace system (CoT-TTS) employs a set of IoT devices, BCT, and Adaptive Neuro-Fuzzy Inference System (ANFIS). The performance of CoT-TTS is evaluated through a case study using an EOSIO platform. The effectiveness of the proposed system is evaluated in terms of depth, breadth, access, and precision of the transactions.

Deep learning domain adaptation to understand physico-chemical processes from fluorescence spectroscopy small datasets and application to the oxidation of olive oil.

Fluorescence spectroscopy is a fundamental tool in life sciences and chemistry, with applications in environmental monitoring, food quality control, and biomedical diagnostics. However, analysis of spectroscopic data with deep learning, in particular of fluorescence excitation-emission matrices (EEMs), presents significant challenges due to the typically small and sparse datasets available. Furthermore, the analysis of EEMs is difficult due to their high dimensionality and overlapping spectral features. This study proposes a new approach that exploits domain adaptation with pretrained vision models, along with a novel interpretability algorithm to address these challenges. Thanks to specialised feature engineering of the neural networks described in this work, we are now able to provide deeper insights into the physico-chemical processes underlying the data. The proposed approach is demonstrated through the analysis of the oxidation process in extra virgin olive oil (EVOO), showing its effectiveness in predicting quality indicators and identifying the spectral bands and thus the molecules involved in the process. This work describes a significantly innovative approach to deep learning for spectroscopy, transforming it from a black box into a tool for understanding complex biological and chemical processes.

Unlocking the potential of biostimulants in sustainable agriculture: Effect of wood distillate on the nutritional profiling of apples.

In this work, we report the investigation of the effect of exposure of apple trees to the bioeffector wood distillate (WD), a plant biostimulant used for improving the nutritional profiling of crop plants. We measured the effect by evaluating the biochemical and nutritional profile of both pulps and skin of fruits. WD (0.2 %, v/v) was applied once a week by foliar application, from May 2023 until September 2023. The results indicate that the WD-treated apples have a significant increase in several analyzed parameters (i.e., phenols, flavonoids, tannins, total antioxidant power, sugars, pectin, free amino acids, and mineral element content), especially in the pulp. These data were also confirmed by NMR and LC-ESI-MS techniques. This study pointed out that WD could be a handy tool for the cultivation of fruit trees.

Critical review on toxic contaminants in surface water ecosystem: sources, monitoring, and its impact on human health.

Surface water pollution is a critical and urgent global issue that demands immediate attention. Surface water plays a crucial role in supporting and sustaining life on the earth, but unfortunately, till now, we have less understanding of its spatial and temporal dynamics of discharge and storage variations at a global level. The contamination of surface water arises from various sources, classified into point and non-point sources. Point sources are specific, identifiable origins of pollution that release pollutants directly into water bodies through pipes or channels, allowing for easier identification and management, e.g., industrial discharges, sewage treatment plants, and landfills. However, non-point sources originate from widespread activities across expansive areas and present challenges due to its diffuse nature and multiple pathways of contamination, e.g., agricultural runoff, urban storm water runoff, and atmospheric deposition. Excessive accumulation of heavy metals, persistent organic pollutants, pesticides, chlorination by-products, pharmaceutical products in surface water through different pathways threatens food quality and safety. As a result, there is an urgent need for developing and designing new tools for identifying and quantifying various environmental contaminants. In this context, chemical and biological sensors emerge as fascinating devices well-suited for various environmental applications. Numerous chemical and biological sensors, encompassing electrochemical, magnetic, microfluidic, and biosensors, have recently been invented by hydrological scientists for the detection of water pollutants. Furthermore, surface water contaminants are monitored through different sensors, proving their harmful effects on human health.

Influence of electrohydrodynamics on the drying characteristics, microstructure and volatile composition of apricot abalone mushroom (Pleurotus eryngii).

The study explored the use of current fluid dynamics drying technology for apricot abalone mushroom, examining how different output voltages (15, 25, and 35 kV) affected drying characteristics, microstructure, and volatile components. Comparisons were made with samples dried using hot air drying (HAD) and natural air drying (AD). Results revealed that HAD had the fastest drying rate at 0.29664(g·h-1). However, apricot abalone mushroom treated with electrohydrodynamic drying (EHD) maintained a color closer to fresh samples, exhibited a 21% increase in the ordered structure of protein secondary structure, a 12.5-fold increase in bound water content, and the most stable cell structure compared to HAD and AD treatments. A total of 83 volatile organic compounds were identified in the apricot abalone mushroom, with alcohols and aldehydes being the most prominent in terms of threshold and relative content, peaking in the 35 kV treatment group. These findings provide both experimental and theoretical insights into applying current fluid dynamics for drying apricot abalone mushroom.

Construction of "ant-like tentacle" structure for ultra-sensitive detection of low-concentration ammonia through colorimetric fluorescent dual-signal gas-sensitive cotton fabric.

Detection and monitoring of ammonia (NH3) are crucial in various industries, including plant safety management, food freshness testing, and water pollution control. Nevertheless, creating portable, low-cost, highly sensitive, and easily regenerated ppm-level NH3 sensors poses a significant challenge. In this investigation, an innovative "ant-like tentacle" fabrication strategy was proposed, and a colorimetric fluorescent dual-signal gas-sensitive cotton fabric (PAH-fabric) for NH3 detection was successfully prepared by conventional dyeing using suitable molecular-level photoacid (PAH) sensitive units. The visual recognition lower detection limit of the ultra-low is 1.09 ppm-level. PAH-fabric is not only straightforward, convenient, and cost-effective to prepare, but it can also be efficiently regenerated and recycled multiple times (maintaining excellent gas-sensitive performance even after 100 cycles) by strategically leveraging volatile acid fumigation. Detailed molecular reaction mechanisms involved in the NH3 response and PAH-fabric regeneration are elucidated. PAH-fabric, available either as a portable kit or an alarm system, offers a promising approach for ultra-low NH3 detection. The demonstrated "ant-like tentacle" fabrication strategy introduces numerous possibilities for designing and developing sensors with adjustable response thresholds, particularly those requiring high sensitivity.

Intelligent Biopolymer-Based Films: Promising New Solutions for Food Packaging Applications.

The development of biopolymer-based films represents a promising direction in the packaging industry that responds to stringent needs for sustainability, reducing the ecological impact. Traditional fossil-derived polymers present major concerns because of their long decomposition time and their significant contribution to the pollution of the environment. On the contrary, biopolymers such as chitosan, PVA, and PLA offer viable alternatives. This study aimed to obtain an innovative pH indicator for smart packaging using a synthetic non-toxic anthocyanin analogue dye incorporated in bio-based films to indicate meat freshness and quality. The pH-responsive color-changing properties of the dye make it suitable for developing intelligent films to monitor food freshness. The obtained polymeric films were characterized by FT-IR and UV-VIS spectroscopy, and their thermal properties were assessed using thermogravimetric methods. Moisture content, swelling capacity, and water solubility of the polymeric films were also evaluated. The sensitivity of the biopolymer-flavylium composite films to pH variations was studied in the pH range of 2 to 12 and noticeable color variations were observed, allowing the monitoring of the meat's quality damage through pH changes. The pH-responsive films were applied directly on the surface or in the proximity of pork and chicken meat samples, to evaluate their colorimetric response to fresh and spoilt meat. This study can be the starting point for creating more durable packaging solutions leading to a circular economy.

Rational design of a NIR fluorescent probe and its application in food detection of viscosity and biosystem imaging.

Viscosity is one of the most important parameters of liquid foods and shows significant change during food spoilage. It is also an important component of the cell microenvironment and is closely associated with the development of liver injury. In this work, a viscosity-sensitive fluorescent probe named WZ-V based on the twisted intramolecular charge transfer (TICT) mechanism was successfully designed. WZ-V had a large Stokes shift, long wavelength emission, and the fluorescence intensity shows 290-fold enhancement in high viscosity. Probe WZ-V successfully detected viscosity changes caused by food thickeners, as well as in milk, orange juice, and lemonade spoilage processes. This provides a new tool for regulating the viscosity of liquid foods and monitoring viscosity changes during food spoilage. In addition, WZ-V has been successfully applied to image viscosity changes in liver injury, which provides an important reference for the study of liver diseases.

Chitosan and inulin synergized with Lactiplantibacillus plantarum LPP95 to improve the quality characteristics of low-salt pickled tuber mustard.

Low-salt pickled vegetables are in line with a healthier diet, yet ensuring consistent quality of such products is challenging. In this study, low-salt tuber mustard pickles fermented with Lactiplantibacillus plantarum LPP95 in the presence of chitosan and inulin were analyzed over a 30-day period, and quality changes were evaluated. Total acid productions along with high bacterial counts (106 CFU/mL) were observed in the initial 20 days during indoor storage temperature, in which the reduced fiber aperture was found significantly lead to an increase in crispness (16.94 ± 1.87 N) and the maintenance of a low nitrate content (1.23 ± 0.01 mg/kg). Moreover, the combined pickling treatment resulted in higher malic acid content, lower tartaric acid content, and a decrease in the content of bitter amino acids (e.g., isoleucine and leucine), thus leading to an increase in the proportion of sweet amino acids. Additionally, combined pickling led to the production of unique volatile flavor compounds, especially the distinct spicy flavor compounds isothiocyanates. Moreover, the combined pickling treatment resulted in an increase in the abundance of Lactiplantibacillus and promoted microbial diversity within the fermentation system. Thus, the synergistic effect among chitosan, inulin, and L. plantarum LPP95 significantly enhanced the quality of pickles. The study offers a promising strategy to standardize the quality of low-salt fermented vegetables.

Climate change versus Mediterranean diet: A hazardous struggle for the women's heart.

Climate change impacts food systems, causing nutritional deficiencies and increasing cardiovascular diseases (CVD). Regulatory frameworks like the European Farm-to-Fork Strategy aim to mitigate these effects, but current EU food safety regulations inadequately address health risks from poor diet quality and contaminants. Climate change adversely affects food quality, such as nutrient depletion in crops due to higher CO2 levels, leading to diets that promote chronic diseases, including CVD. Women, because of their roles in food production and their unique physiological responses to nutrients, face distinct vulnerabilities. This review explores the interplay between climate change, diet, and cardiovascular health in women. The review highlights that sustainable diets, particularly the Mediterranean diet, offer health benefits and lower environmental impacts but are threatened by climate change-induced disruptions. Women's adherence to the Mediterranean diet is linked to significant reductions in CVD risk, though sex-specific responses need further research. Resilient agricultural practices, efficient water management, and climate-smart farming are essential to mitigate climate change's negative impacts on food security. Socio-cultural factors influencing women's dietary habits, such as traditional roles and societal pressures, further complicate the picture. Effective interventions must be tailored to women, emphasizing education, community support, policy changes, and media campaigns promoting healthy eating. Collaborative approaches involving policymakers, health professionals, and the agricultural sector are crucial for developing solutions that protect public health and promote sustainability. Addressing the multifaceted challenges posed by climate change to food quality and cardiovascular health in women underscores the need for integrated strategies that ensure food security, enhance diet quality, and mitigate environmental impacts.

Effects of thermal processing on natural antioxidants in fruits and vegetables.

Research on the content of polyphenolic compounds in fruits and vegetables, the extraction of bioactive compounds, and the study of their impact on the human body has received growing attention in recent years. This is due to the great interest in bioactive compounds and their health benefits, resulting in increased market demand for natural foods. Bioactive compounds from plants are generally categorized as natural antioxidants with health benefits such as anti-inflammatory, antioxidant, anti-diabetic, anti-carcinogenic, etc. Thermal processing has been used in the food sector for a long history. Implementing different thermal processing methods could be essential in retaining the quality of the natural antioxidant compounds in plant-based foods. A comprehensive review is presented on the effects of thermal blanching (i.e., hot water, steam, superheated steam impingement, ohmic and microwave blanching), pasteurization, and sterilization and drying technologies on natural antioxidants in fruits and vegetables.

Contributions of Gamma-Aminobutyric Acid (GABA) Produced by Lactic Acid Bacteria on Food Quality and Human Health: Current Applications and Future Prospects.

The need to increase food safety and improve human health has led to a worldwide increase in interest in gamma-aminobutyric acid (GABA), produced by lactic acid bacteria (LABs). GABA, produced from glutamic acid in a reaction catalyzed by glutamate decarboxylase (GAD), is a four-carbon, non-protein amino acid that is increasingly used in the food industry to improve the safety/quality of foods. In addition to the possible positive effects of GABA, called a postbiotic, on neuroprotection, improving sleep quality, alleviating depression and relieving pain, the various health benefits of GABA-enriched foods such as antidiabetic, antihypertension, and anti-inflammatory effects are also being investigated. For all these reasons, it is not surprising that efforts to identify LAB strains with a high GABA productivity and to increase GABA production from LABs through genetic engineering to increase GABA yield are accelerating. However, GABA's contributions to food safety/quality and human health have not yet been fully discussed in the literature. Therefore, this current review highlights the synthesis and food applications of GABA produced from LABs, discusses its health benefits such as, for example, alleviating drug withdrawal syndromes and regulating obesity and overeating. Still, other potential food and drug interactions (among others) remain unanswered questions to be elucidated in the future. Hence, this review paves the way toward further studies.