Microbiological quality of gluten-free meals, naturally gluten free foods, and gluten free-labelled products.

Background: The rising prevalence of gluten-related disorders such as celiac disease explains the increased consumption of gluten-free foods (GFF). However, these foods must be safe in terms of both gluten content and contamination by pathogenic microorganisms in order to avoid food poisoning. Objective: The objective of this study was to assess the microbiological quality of gluten-free meals, naturally gluten free foods, and gluten free-labelled products. Material and Methods: We collected 62 GFF samples including 20 meals (M-GF), 22 naturally gluten free (N-GFF) and 20 labelled (L-GFF) products, which were investigated for microbiological contamination according to Moroccan regulations guidelines, issued by the International Organization for Standardization (ISO). The analysis consisted of the detection of Salmonella and Listeria monocytogenes in each sample, and the quantification of the microbial load of the following six micro-organisms: total aerobic mesophilic flora, total coliforms, fecal coliforms, Staphylococcus aureus, Sulphite-Reducing Anaerobic, and yeasts and molds. Results: A total of 372 analyses were carried out, showing a microbiological contamination rate of 5.1%. This contamination concerned N-GFF in 8.3% (predominantly with yeasts and molds), and meals prepared at home in 11.7 (predominantly with Staphylococcus aureus and coliforms). Only one case (0.8%) of contamination was observed in products labelled gluten-free and no contamination was noticed in meals prepared in food services. Listeria monocytgenes and Salmonella were not detected in any samples of food analyzed. These results indicate a good compliance of L-GFP and M-GF prepared in food services, while unsatisfactory quality was observed in N-GFF and M-GF prepared at home. Conclusion: Therefore, rigorous hygienic practices and adequate corrective measures should be considered by celiac patients, especially regarding the N-GFF and M-GF prepared at home.

Quantum dots as advanced nanomaterials for food quality and safety applications: A comprehensive review and future perspectives.

The importance of food quality and safety lies in ensuring the best product quality to meet consumer demands and public health. Advanced technologies play a crucial role in minimizing the risk of foodborne illnesses, contamination, drug residue, and other potential hazards in food. Significant materials and technological advancements have been made throughout the food supply chain. Among them, quantum dots (QDs), as a class of advanced nanomaterials with unique physicochemical properties, are progressively demonstrating their value in the field of food quality and safety. This review aims to explore cutting-edge research on the different applications of QDs in food quality and safety, including encapsulation of bioactive compounds, detection of food analytes, food preservation and packaging, and intelligent food freshness indicators. Moreover, the modification strategies and potential toxicities of diverse QDs are outlined, which can affect performance and hinder applications in the food industry. The findings suggested that QDs are mainly used in analyte detection and active/intelligent food packaging. Various food analytes can be detected using QD-based sensors, including heavy metal ions, pesticides, antibiotics, microorganisms, additives, and functional components. Moreover, QD incorporation aided in improving the antibacterial and antioxidant activities of film/coatings, resulting in extended shelf life for packaged food. Finally, the perspectives and critical challenges for the productivity, toxicity, and practical application of QDs are also summarized. By consolidating these essential aspects into this review, the way for developing high-performance QD-based nanomaterials is presented for researchers and food technologists to better capitalize upon this technology in food applications.

Comprehensive fluorescence profiles of contamination-prone foods applied to the design of microcontact-printed in situ functional oligonucleotide sensors.

With both foodborne illness and food spoilage detrimentally impacting human health and the economy, there is growing interest in the development of in situ sensors that offer real-time monitoring of food quality within enclosed food packages. While oligonucleotide-based fluorescent sensors have illustrated significant promise, the development of such on-food sensors requires consideration towards sensing-relevant fluorescence properties of target food products-information that has not yet been reported. To address this need, comprehensive fluorescence profiles for various contamination-prone food products are established in this study across several wavelengths and timepoints. The intensity of these food backgrounds is further contextualized to biomolecule-mediated sensing using overlaid fluorescent oligonucleotide arrays, which offer perspective towards the viability of distinct wavelengths and fluorophores for in situ food monitoring. Results show that biosensing in the Cyanine3 range is optimal for all tested foods, with the Cyanine5 range offering comparable performance with meat products specifically. Moreover, recognizing that mass fabrication of on-food sensors requires rapid and simple deposition of sensing agents onto packaging substrates, RNA-cleaving fluorescent nucleic acid probes are successfully deposited via microcontact printing for the first time. Direct incorporation onto food packaging yields cost-effective sensors with performance comparable to ones produced using conventional deposition strategies.

A poisonous cocktail: interplay of cereulide toxin and its structural isomers in emetic Bacillus cereus.

Food intoxications evoked by emetic Bacillus cereus strains constitute a serious threat to public health, leading to emesis and severe organ failure. The emetic peptide toxin cereulide, assembled by the non-ribosomal peptide synthetase CesNRPS, cannot be eradicated from contaminated food by usual hygienic measures due to its molecular size and structural stability. Next to cereulide, diverse chemical variants have been described recently that are produced concurrently with cereulide by CesNRPS. However, the contribution of these isocereulides to the actual toxicity of emetic B. cereus, which produces a cocktail of these toxins in a certain ratio, is still elusive. Since cereulide isoforms have already been detected in food remnants from foodborne outbreaks, we aimed to gain insights into the composition of isocereulides and their impact on the overall toxicity of emetic B. cereus. The amounts and ratios of cereulide and isocereulides were determined in B. cereus grown under standard laboratory conditions and in a contaminated sample of fried rice balls responsible for one of the most severe food outbreaks caused by emetic B. cereus in recent years. The ratios of variants were determined as robust, produced either under laboratory or natural, food-poisoning conditions. Examination of their actual toxicity in human epithelial HEp2-cells revealed that isocereulides A-N, although accounting for only 10% of the total cereulide toxins, were responsible for about 40% of the total cytotoxicity. An this despite the fact that some of the isocereulides were less cytotoxic than cereulide when tested individually for cytotoxicity. To estimate the additive, synergistic or antagonistic effects of the single variants, each cereulide variant was mixed with cereulide in a 1:9 and 1:1 binary blend, respectively, and tested on human cells. The results showed additive and synergistic impacts of single variants, highlighting the importance of including not only cereulide but also the isocereulides in routine food and clinical diagnostics to achieve a realistic toxicity evaluation of emetic B. cereus in contaminated food as well as in patient samples linked to foodborne outbreaks. Since the individual isoforms confer different cell toxicity both alone and in association with cereulide, further investigations are needed to fully understand their cocktail effect.

Progress and Challenge of Sensors for Dairy Food Safety Monitoring.

One of the most consumed foods is milk and milk products, and guaranteeing the suitability of these products is one of the major concerns in our society. This has led to the development of numerous sensors to enhance quality controls in the food chain. However, this is not a simple task, because it is necessary to establish the parameters to be analyzed and often, not only one compound is responsible for food contamination or degradation. To attempt to address this problem, a multiplex analysis together with a non-directed (e.g., general parameters such as pH) analysis are the most relevant alternatives to identifying the safety of dairy food. In recent years, the use of new technologies in the development of devices/platforms with optical or electrochemical signals has accelerated and intensified the pursuit of systems that provide a simple, rapid, cost-effective, and/or multiparametric response to the presence of contaminants, markers of various diseases, and/or indicators of safety levels. However, achieving the simultaneous determination of two or more analytes in situ, in a single measurement, and in real time, using only one working 'real sensor', remains one of the most daunting challenges, primarily due to the complexity of the sample matrix. To address these requirements, different approaches have been explored. The state of the art on food safety sensors will be summarized in this review including optical, electrochemical, and other sensor-based detection methods such as magnetoelastic or mass-based sensors.

Occurrence of mycotoxins in meat alternatives: Dietary exposure, potential health risks, and burden of disease.

This study aimed to present the occurrence of sixteen mycotoxins in 105 meat alternatives based on wheat, legumes, and vegetables from Italy. The targeted mycotoxins were aflatoxins (AFB1, AFB2, AFG1, AFG2), fumonisins B1 and B2 (FB1, FB2), alternariol (AOH), alternariol monomethyl ether (AME), tentoxin (TEN), ochratoxin A (OTA), zearalenone (ZEN), T-2/HT-2 toxin, deoxynivalenol (DON), enniatin B (ENNB), and beauvericin (BEA). The occurrence of mycotoxins was between 0% (AFB2) - 97.4% (ENNB). Mycotoxin co-occurrence varied from binary combinations up to mixtures of twelve. To assess the dietary exposure and potential health risks we simulated the replacement of meat consumption for Italian consumers with meat alternatives. The cumulative exposure to Alternaria mycotoxins and trichothecenes indicated a potential health risk while the exposure to aflatoxins and ochratoxin A indicated a potential health concern related to liver and renal cancer in the model scenario. Moreover, we estimated the risk of liver cancer from exposure to AFB1 and quantified the potential burden using Disability-Adjusted Life Years (DALYs). Luckily, the potential risk of liver cancer was low between 0 and 0.05/100,000 individuals with an associated burden of disease of 0.83 DALYs/100,000 individuals. Taking into consideration the presence of meat alternatives on the food market and the ongoing shift towards plant-based diets there is a need for continuous monitoring to keep the occurrence at safe levels. More attention is needed from the regulatory side for policymakers to consider the legislations of mycotoxins in meat alternatives.

From field to table: Ensuring food safety by reducing pesticide residues in food.

The present review addresses the significance of lowering pesticide residue levels in food items because of their harmful impacts on human health, wildlife populations, and the environment. It draws attention to the possible health risks-acute and chronic poisoning, cancer, unfavorable effects on reproduction, and harm to the brain or immunological systems-that come with pesticide exposure. Numerous traditional and cutting-edge methods, such as washing, blanching, peeling, thermal treatments, alkaline electrolyzed water washing, cold plasma, ultrasonic cleaning, ozone treatment, and enzymatic treatment, have been proposed to reduce pesticide residues in food products. It highlights the necessity of a paradigm change in crop protection and agri-food production on a global scale. It offers opportunities to guarantee food safety through the mitigation of pesticide residues in food. The review concludes that the first step in reducing worries about the negative effects of pesticides is to implement regulatory measures to regulate their use. In order to lower the exposure to dietary pesticides, the present review also emphasizes the significance of precision agricultural practices and integrated pest management techniques. The advanced approaches covered in this review present viable options along with traditional methods and possess the potential to lower pesticide residues in food items without sacrificing quality. It can be concluded from the present review that a paradigm shift towards sustainable agriculture and food production is essential to minimize pesticide residues in food, safeguarding human health, wildlife populations, and the environment. Furthermore, there is a need to refine the conventional methods of pesticide removal from food items along with the development of modern techniques.

Virtual display of targets: A new level to rise the current understanding of ochratoxin A toxicity from a molecular standpoint.

Ochratoxin A (OTA) is a mycotoxin spread worldwide contaminating several food and feed commodities and rising concerns for humans and animals. OTA toxicity has been thoroughly assessed over the last 60 years revealing a variety of adverse effects, including nephrotoxicity, hepatotoxicity and possible carcinogenicity. However, the underpinning mechanisms of action have yet to be completely displayed and understood. In this framework, we applied a virtual pipeline based on molecular docking, dynamics and umbrella simulations to display new OTA potential targets. The results collected consistently identified OGFOD1, a key player in protein translation, as possibly inhibited by OTA and its 2'R diastereomer. This is consistent with the current knowledge of OTA's molecular toxicology and may fill some gaps from a mechanistic standpoint. This could pave the way for further dedicated analysis focusing their attention on the OTA-OGFOD1 interaction, expanding the current understanding of OTA toxicity at a molecular level.

Recent advances in activated water systems for the postharvest management of quality and safety of fresh fruits and vegetables.

Over the last three decades, decontamination management of fresh fruits and vegetables (FFVs) in the packhouses and along the supply chains has been heavily dependent on chemical-based wash. This has resulted in the emergence of resistant foodborne pathogens and often the deposition of disinfectant byproducts on FFVs, rendering them unacceptable to consumers. The management of foodborne pathogens, microbial contaminants, and quality of FFVs are a major concern for the horticultural industries and public health. Activated water systems (AWS), such as electrolyzed water, plasma-activated water, and micro-nano bubbles, have gained significant attention from researchers over the last decade due to their nonthermal and nontoxic mode of action for microbial inactivation and preservation of FFVs quality. The aim of this review is to provide a comprehensive summary of recent progress on the application of AWS and their effects on quality attributes and microbial safety of FFVs. An overview of the different types of AWS and their properties is provided. Furthermore, the review highlights the chemistry behind generation of reactive species and the impact of AWS on the quality attributes of FFVs and on the inactivation/reduction of spoilage and pathogenic microbes (in vivo or in vitro). The mechanisms of action of microorganism inactivation are discussed. Finally, this work highlights challenges and limitations for commercialization and safety and regulation issues of AWS. The synergistic prospect on combining AWS for maximum microorganism inactivation effectiveness is also considered. AWS offers a potential alternative as nonchemical interventions to maintain quality attributes, inactivate spoilage and pathogenic microorganisms, and extend the shelf-life for FFVs.

Determination and risk assessment of aflatoxin B1 in the kernel of imported raw hazelnuts from Eastern Azerbaijan Province of Iran.

Aflatoxin B1 (AFB1) is widespread and seriously threatens public health worldwide. This study aimed to investigate AFB1 in imported hazelnut samples in northwest of Iran (Eastern Azerbaijan Province) using High-Performance Liquid Chromatography with a Fluorescent Detector (HPLC-FLD). In all tested samples AFB1 was detected. The mean concentration of AFB1 was 4.20 µg/kg and ranged from 3.145 to 8.13 µg/kg. All samples contained AFB1 levels within the maximum acceptable limit except for one sample. Furthermore, the human health risk assessment of AFB1 from consuming imported hazelnuts by Iranian children and adults was evaluated based on the margin of exposure (MoE) and quantitative liver cancer risk approaches. The MoE mean for children was 2529.76, while for adults, it was 8854.16, indicating a public health concern. The present study found that the risk of developing liver cancer among Iranian children was 0.11100736 per 100,000 people, and in the Iranian adult population was 0.0314496 cancers per 100,000 people. Since environmental conditions potentially affect aflatoxin levels in nuts, countries are advised to monitor aflatoxin contents in imported nuts, especially from countries with a conducive climate for mold growth.

Evaluation of biotoxins and toxic metal risks in mussels from the Sea of Marmara following marine mucilage.

The mucilage phenomenon observed in the Sea of Marmara in 2021, has raised public concern about seafood safety. Mediterranean mussels serve as a vehicle in food chain, enabling the transfer of pollutants. Farmed and wild mussels were collected from 4 different stations throughout the fishing season. Biotoxins causing amnesic, paralytic, or diarrhetic shellfish poisonings (ASP, PSP, or DSP) were examined during monthly samplings. Potential health risks posed by cadmium, lead and arsenic were assessed. Health risks were evaluated considering 150 g/week mussel consumption, accounting for the different age groups of consumers (50, 60, 70 kg). Estimated Weekly Intake calculations of metals were determined to be lower than Provisional Tolerable Weekly Intake at all age groups throughout the sampling period in all stations. Target Hazard QuotientCd of mussels captured from Istanbul Strait was always determined <1, while it was equal to 1 for 50 kg individuals in Gelibolu samples. All THQAs were >1. Target carcinogenic Risk was evaluated for Pb and iAs, which were found to be negligible and acceptable, respectively. No biotoxins responsible for ASP, PSP, or DSP were detected. Hg levels were under detectable limits. Excluding Cd, the results did not reveal any risks associated with mussel consumption during mucilage.

Machine learning-enabled high-throughput industry screening of edible oils.

Long-term consumption of mixed fraudulent edible oils increases the risk of developing of chronic diseases which has been a threat to the public health globally. The complicated global supply-chain is making the industry malpractices had often gone undetected. In order to restore the confidence of consumers, traceability (and accountability) of every level in the supply chain is vital. In this work, we shown that machine learning (ML) assisted windowed spectroscopy (e.g., visible-band, infra-red band) produces high-throughput, non-destructive, and label-free authentication of edible oils (e.g., olive oils, sunflower oils), offers the feasibility for rapid analysis of large-scale industrial screening. We report achieving high-level of discriminant (AUC > 0.96) in the large-scale (n ≈ 11,500) of adulteration in olive oils. Notably, high clustering fidelity of 'spectral fingerprints' achieved created opportunity for (hypothesis-free) self-sustaining large database compilation which was never possible without machine learning. (137 words).

Prevalence of Bacillus cereus in food products in Poland.

INTRODUCTION AND OBJECTIVE: Bacillus cereus is a foodborne pathogen causing two main types of gastrointestinal diseases: emetic and diarrheal. The aim of this study was to investigate the prevalence of the Bacillus cereus group in ready-to-eat (RTE) food products available in retail in Poland. MATERIAL AND METHODS: Samples were collected by Sanitary and Epidemiological Stations within the framework of the national official control and monitoring sampling programme in Poland. In 2016-2020, a total of 45,358 food samples, such as: 'confectionery products and products with cream', as well as 'cereal grains and cereal and flour products', 'milk and milk products', 'sugar and others', 'meat offal and meat products', 'poultry offal and poultry products', 'eggs and egg products', 'fish, seafood and their preserves', 'vegetables' (including legumes), 'coffee, tea, cocoa, fruit, and herbal teas', 'delicatessen and culinary products', and 'foods for particular nutritional uses' were collected. RESULTS: The presence of the presumptive B. cereus group was monitored mainly in two categories of food products: 'confectionery products and products with uncooked cream' and 'confectionery products and products with heat-treated cream'. The number of samples disqualified due to presumptive B. cereus was 339 (0.75%). CONCLUSIONS: This study provides useful information regarding the contamination of RTE products with the B. cereus group, which may have implications for food safety.

Assessment of some chemical residues in Egyptian raw milk and traditional cheese.

Background: The assessment of risks related to food safety is becoming a challenge in developing countries with its consequent health hazards. Chemical risk assessment in dairy products is important to maintain consumer health locally and internationally. Since milk and dairy products are essential foods for a wide range of customers, mostly children, patients, and pregnant women, it is very important to estimate the risks of some chemical residues, such as pesticides, some heavy metals, and aflatoxins. Aim: This work aims to determine the levels of chemical contamination in milk and traditional Egyptian cheese. Methods: Heavy metals were determined in samples by atomic absorption spectrometry. GC-mass spectrometry (MS)/MS and LC-MS/MS were also used for measuring pesticide residues. The Aflatoxin M1 was determined by enzyme-linked immune-sorbent assay. Results: Raw milk samples were tested and showed elevated concentrations of lead and cadmium, (46% and 4%, respectively). The heavy metals detected in the Egyptian cheese samples were variable depending on the type of cheese. Moreover, p.p.-DDE phenofose was present in 45% and 29% of raw milk and Ras cheese samples, respectively. For Aflatoxin M1, only 7% of milk samples and 2.9% of Ras cheese samples exceeded the acceptable limits. Conclusion: More surveying and risk assessment of chemical residues in milk and milk products are essential for controlling health risks to consumers.

Human health risk assessment based on a total diet study of daily mercury intake in Chengdu, China.

To assess the total daily mercury intake and main exposure sources of residents, six food groups, including marine fish, freshwater fish, poultry, livestock, vegetables, and cereals, were collected from five districts of Chengdu, China. The median concentrations of total mercury (THg) and methylmercury (MeHg) were 12.8 and 6.94 µg kg-1 ww, respectively. Cereals (32.2%), vegetables (30.5%), and livestock (16.2%) contributed to a much larger extent to the total consumption for the participants in Chengdu. All food categories that contributed the most of THg (2.16 µg day-1) and MeHg 1.44 (µg day-1) to the daily intake in Chengdu were cereals and marine fish, respectively. The total Hazard Ratios values below 1 in this study indicate that there is no health risk associated with Hg ingestion from the consumption of these foods for the residents in Chengdu.

Development of a processing factor prediction model for pesticides in processed tomato foods using elastic net regularization.

A novel regularized elastic net regression model was developed to predict processing factor (PF) for pesticide residues, which represents a change in the residue levels during food processing. The PF values for tomato juice, wet pomace and dry pomace in the evaluations and reports published by the Joint FAO/WHO Meeting on Pesticide Residues significantly correlated with the physicochemical properties of pesticides, and subsequently the correlation was observed in the present tomato processing study. The elastic net regression model predicted the PF values using the physicochemical properties as predictor variables for both training and test data within a 2-fold range for 80-100% of the pesticides tested in the tomato processing study while overcoming multicollinearity. These results suggest that the PF values are predictable at a certain degree of accuracy from the unique sets of physicochemical properties of pesticides using the developed model based on a processing study with representative pesticides.

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents.

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

Changing climate, shifting mycotoxins: A comprehensive review of climate change impact on mycotoxin contamination.

Climate change (CC) is a complex phenomenon that has the potential to significantly alter marine, terrestrial, and freshwater ecosystems worldwide. Global warming of 2°C is expected to be exceeded during the 21st century, and the frequency of extreme weather events, including floods, storms, droughts, extreme temperatures, and wildfires, has intensified globally over recent decades, differently affecting areas of the world. How CC may impact multiple food safety hazards is increasingly evident, with mycotoxin contamination in particular gaining in prominence. Research focusing on CC effects on mycotoxin contamination in edible crops has developed considerably throughout the years. Therefore, we conducted a comprehensive literature search to collect available studies in the scientific literature published between 2000 and 2023. The selected papers highlighted how warmer temperatures are enabling the migration, introduction, and mounting abundance of thermophilic and thermotolerant fungal species, including those producing mycotoxins. Certain mycotoxigenic fungal species, such as Aspergillus flavus and Fusarium graminearum, are expected to readily acclimatize to new conditions and could become more aggressive pathogens. Furthermore, abiotic stress factors resulting from CC are expected to weaken the resistance of host crops, rendering them more vulnerable to fungal disease outbreaks. Changed interactions of mycotoxigenic fungi are likewise expected, with the effect of influencing the prevalence and co-occurrence of mycotoxins in the future. Looking ahead, future research should focus on improving predictive modeling, expanding research into different pathosystems, and facilitating the application of effective strategies to mitigate the impact of CC.

Aggregation-induced emission nanoparticles facilitating multicolor lateral flow immunoassay for rapid and simultaneous detection of aflatoxin B1 and zearalenone.

Herein we developed a multicolor lateral flow immunoassay (LFIA) test strip for rapid and simultaneous quantitative detection of aflatoxin B1 (AFB1) and zearalenone (ZEN). Three differently colored aggregation-induced emission nanoparticles (AIENPs) were designed as LFIA signal tags, with red and green AIENPs for targeting AFB1 and ZEN at the test line, and yellow AIENPs for indicating the validity of the test strip at the control (C) line. After surface functionalization with antibodies, the developed AIENP-based multicolor LFIA allows simultaneous and accurate quantification of AFB1 and ZEN using an independent C-line assisted ratiometric signal output strategy. The detection limits of AFB1 and ZEN were 6.12 and 26 pg/mL, respectively. The potential of this method for real-world applications was well demonstrated in corn and wheat. Overall, this multicolor LFIA shows great potential for field screening of multiple mycotoxins and can be extended to rapid and simultaneous monitoring of other small molecule targets.

Machine Learning-Assisted Portable Microplasma Optical Emission Spectrometer for Food Safety Monitoring.

To meet the needs of food safety for simple, rapid, and low-cost analytical methods, a portable device based on a point discharge microplasma optical emission spectrometer (µPD-OES) was combined with machine learning to enable on-site food freshness evaluation and detection of adulteration. The device was integrated with two modular injection units (i.e., headspace solid-phase microextraction and headspace purge) for the examination of various samples. Aromas from meat and coffee were first introduced to the portable device. The aroma molecules were excited to specific atomic and molecular fragments at excited states by room temperature and atmospheric pressure microplasma due to their different atoms and molecular structures. Subsequently, different aromatic molecules obtained their own specific molecular and atomic emission spectra. With the help of machine learning, the portable device was successfully applied to the assessment of meat freshness with accuracies of 96.0, 98.7, and 94.7% for beef, pork, and chicken meat, respectively, through optical emission patterns of the aroma at different storage times. Furthermore, the developed procedures can identify beef samples containing different amounts of duck meat with an accuracy of 99.5% and classify two coffee species without errors, demonstrating the great potential of their application in the discrimination of food adulteration. The combination of machine learning and µPD-OES provides a simple, portable, and cost-effective strategy for food aroma analysis, potentially addressing field monitoring of food safety.