Latest ArticlesTo investigate the contamination status, serotype distribution and antimicrobial resistance characteristics of Salmonella in retail raw chicken in Guangzhou.
From 2023 to 2024, raw chicken samples were collected from retail markets in Guangzhou for Salmonella isolation and identification. Serotyping and antimicrobial susceptibility testing against 21 agents from 9 classes were performed.
Among 280 raw chicken samples, the overall detection rate of Salmonella was 29.29% (82/280) and 85 strains of Salmonella were isolated.Storage temperature and sampling site significantly affected the detection rate. The rate was highest in ambient fresh chicken (34.56%, 47/136), followed by chilled chicken (29.47%, 28/95), and lowest in frozen chicken (14.29%, 7/49)(χ2=7.151, P=0.028). Among sampling sites, the detection rate was highest in wet markets (38.39%, 43/112), compared to supermarkets and online stores (both 23.21%: 26/112 and 13/56, respectively) (χ2=7.476, P=0.024). The predominant serotypes were Salmonella agona, Salmonella corvallis and Salmonella indiana. The detection rate of drug-resistant strains was 92.94% (79/85), with highest resistance to tetracycline (78.82%), followed by ampicillin (67.06%), and chloramphenicol and florfenicol (both 64.71%). All isolates remained susceptible to ceftazidime/avibactam. Multidrug-resistant strains accounted for 70.59%, with some resistant to up to 8 antimicrobial classes.
Salmonella is detected at a relatively high rate in raw chicken in Guangzhou, exhibiting diverse serotypes and severe antimicrobial resistance, underscoring the need for enhanced meat safety surveillance and antimicrobial stewardship.
Persistent organic pollutants (POPs), microplastics (MPs), endocrine disruptors, antibiotics and other emerging contaminants (ECs) are currently major risk factors threatening food safety and harming public health.Traditional food safety analytical methods face technical bottlenecks in addressing unknown and complex new contaminants. In recent years, artificial intelligence (AI) technologies, such as machine learning (ML), have provided a novel and powerful tool to tackle this challenge due to their strong data processing capabilities and excellent pattern recognition performance. This article elaborated on the prominent advantages of AI technology in optimizing sample pre-treatment processes, improving instrumental analysis efficiency, constructing screening databases and extracting confirmatory information in key analytical processes, and assessed its potential applications in the analysis of emerging contaminants in food. Despite broad prospects, this field still faced challenges related to data quality, model interpretability, standardisation and institutional and procedural mechanisms. Overall, AI technology is effectively promoting the development of intelligent and predictive analysis of emerging contaminants in food.
As an emerging discipline, synthetic biology has gradually been introduced into the industrial sector.Moreover, the synthetic biology industry has become an innovation highland in the food industry and is currently one of the industries that best reflects the core competitiveness of countries around the world. The production process of synthetic biology differs from traditional physical separation and chemical synthesis, using various microbial cells as the chassis to efficiently produce target products in a ‘cell factory’. Therefore, the characteristics of its production process pose relatively high requirements for the supervision of its edible safety, and risk control cannot be ignored.At present, global attention is focusing on the health risks of synthetic biological foods. Key international and regional regulatory bodies, including the Codex Alimentarius Commission (CAC), as well as food safety authorities in Europe, the Americas and China, are leading efforts in formulating relevant regulations. This paper systematically reviewed the regulatory status and risk assessment requirements for synthetic biological foods of key international organizations, countries and regions, such as the CAC, the United States and the European Union. It comparatively analysed their similarities and differences in the key points for risk assessment. This review proposed reasonable suggestions for the risk assessment and supervision of the food safety of such foods in China. This study aimed to serve as a further reference for enhancing the safety risk management of biosynthetic three new foods in China.
To investigate the adulteration status of commercial cooked beef products and analyze the characteristics of undeclared animal-derived components.
A total of 133 samples of commercial cooked beef products were collected. Based on the SN/T 2051—2008 Determination of bovine, ovine, porcine-derived materials in food, cosmetic and feed-Real-time PCR method and GB/T 38164—2019 Identification of animal ingredient from common livestock and poultry-Real-time PCR, real-time fluorescent polymerase chain reaction was employed to detect 5 kinds of animal-derived components, namely cattle, sheep, pig, chicken and duck, thereby establishing the profiles of undeclared animal-derived components.
Among the 133 samples, 16 were detected with undeclared animal-derived components, resulting in the adulteration rate of 12.03%. The adulteration rate in cooked dried meat products from large and medium-sized supermarkets was significantly higher than that from small supermarkets and other sales venues. Among the detected undeclared animal-derived components, chicken-derived components had the highest detection rate (68.75%), followed by pork-derived (25.00%) and duck-derived components (18.75%), while sheep-derived components showed the lowest detection rate (12.50%).The profile of undeclared animal-derived components comprised 6 types, with the single adulteration of chicken-derived components being the most prevalent (62.50%).
The inspected commercial cooked beef products on the market have some adulteration issues, mainly involving the addition of chicken-derived components. Regulatory authorities should establish a regular sampling inspection mechanism for beef products and promote the full coverage of the traceability system to ensure product quality and safety.
To analyze the distribution characteristics, usage patterns and exposure contribution via beverage consumption of sweeteners in beverages sold around school campuses from the perspective of beverage category segmentation.
A total of 834 samples from 7 beverage categories, including flavored beverages, were randomly collected. The content of 4 kinds of sweeteners (sodium saccharin, acesulfame potassium, aspartame and neotame) were determined using high performance liquid chromatography (HPLC). Compliance with sweetener usage was evaluated according to the GB 2760—2014 National food safety standard-Standard for the Use of Food Additives and differences among categories were analyzed using the chi-square test.
Special purpose beverages had the highest non-compliance rate (14.7%, 14/95), followed by flavored beverages (14.6%, 36/247), both being higher than that of coffee beverages (0%, 0/15). The rate of unauthorized use of sodium saccharin in flavored beverages was (9.3%, 23/247) (its use was prohibited in beverages according to the standard). The exceedance rate of neotame in special purpose beverages was (10.5%, 10/95).
There are significant category-specific variations in sweeteners non-compliance in beverages around school campuses: Flavored beverages are the key category for the unauthorized use of sodium saccharin, while special purpose beverages are the high-risk category for neotame exceedance. It is recommended that quarterly targeted sampling and inspection be implemented for these 2 kinds of beverage categories, along with enhanced supervision of sweetener usage compliance, so as to provide direct scientific support for targeted regulation of beverages around school campuses and health risk warning for adolescents.
Food safety issues have garnered increasing global attention, creating an urgent need for the development of rapid, accurate and on-site detection technology, and the integration of intelligent and rapid detection methods provides a crucial direction for future development. This paper aimed to systematically review the latest advances in the integration of artificial intelligence (AI) and rapid food detection technology. Using this as the core analytical perspective, it compared and examined the different roles, integration modes and driving logics of such integration in the technological development paths of China and major developed countries. A comparison of development paths between China and other countries revealed that China had established a rapid screening system suitable for grassroots regulatory use through technologies like colloidal gold multi-test card. In contrast, developed countries had focused more on high-precision biosensing technologies and established comprehensive precision detection networks that cover the entire industry chain. Rapid detection technologies in China currently faced challenges, including incomplete maturation of core material preparation processes and the operational proficiency of grassroots testing personnel not meeting the requirements of intelligent equipment. In the future, the direction of multi-source and multi-element fusion would become one of the important development trends, which was mainly reflected in the in-depth integration of AI with biosensors. For instance, the coupling of Raman spectroscopy with deep learning could not only achieve rapid and accurate detection of complex food matrices, but also derived the evolution of detection systems from a single-purpose tool into intelligent decision-making systems. Furthermore, this paper proposed that to enhance the grasp of the development trajectory of intelligent food rapid detection technology and improve rove China’s technology research and development layout, it was important to strengthen international cooperation and mutual recognition of detection standards. Active participation in the International Technical Alliance for Food Detection was essential to contribute greater efforts toward advancing the global food safety governance system.
To analyze and evaluate the situation of multiple pesticide residues and risk assessment in commercially available “Feizixiao” Litchi chinensis in Hainan.
In 2024, 35 batches of commercially available “Feizixiao” Litchi chinensis samples (referred to as “Feizixiao”) were collected from 13 cities and counties in Hainan Province (Haikou, Qiongzhong, Danzhou, Lingao, Wenchang, Wanning, Ding’an, Lingshui, Chengmai, Sanya, Baoting, Qionghai, Wuzhishan). Gas chromatography-tandem mass spectrometry (GC-MS/MS) was used to detect 195 kinds of pesticide residues in the samples. The detected pesticide residue components were analyzed, and risk ranking as well as dietary exposure risk assessment of these residues were conducted based on the risk ranking method.
The total detection rate of pesticide residues was 100%, with a sample qualification rate of 62.9%.A total of 16 pesticide components were detected, among which only 8 had corresponding maximum residue limits established in China, accounting for 50% of the detected pesticides. The 4 kinds of pesticides had a detection rate exceeding 50%, namely difenoconazole (91.4%), lambda-cyhalothrin and gamma-cyhalothrin (80.0%), flumiproparil(71.4%) and cypermethrin and beta-cypermethrin (51.4%). The distribution of pesticide residue types detected per batch was as follows: 1 batch with 1 type, 6 batches with 2–3 types, 6 batches with 4 types, and 22 batches with 5 or more types, with a maximum of 8 types detected in a single batch. Based on the residue risk scores, among the detected pesticides, 3 were classified as low-risk, 10 as medium-risk and 3 as high-risk. In the chronic dietary exposure risk assessment of diverse populations, the acceptable daily intake for males exceeded that for females, yet both exhibited low exposure risk levels.
The detection rate of pesticide residues in commercially available “Feizixiao” Litchi chinensis in Hainan is relatively high, possibly related to the current standard specifying the whole fruit as the testing part and the lack of corresponding residue limits for some pesticides, which requires standard improvement. Multiple pesticide types are detected in single batches, likely due to alternating/repeated pesticide application during production; the results can support scientific pesticide use. Risk assessment shows most residue and chronic dietary exposure risks are low-to-medium and controllable, and consumers can reduce potential impacts by properly cleaning the peel.
To analyze the common defects on inspection observations in on-site food inspections conducted by the U.S. Food and Drug Administration (FDA).
This study analyzed the inspection observations (also known as form 483) issued by the FDA on-site food inspections from 2020 to 2024, and the data on inspection observations that fail to meet the requirements of part 117 of title 21 of the Code of Federal Regulations, used the cited regulation clause numbers as the analytical dimension. Additionally, based on the content of warning letters, discussed and summarized the common defects found in food manufacturers during inspections, as well as the implications and recommendations for Chinese food manufacturing enterprises that exporting to the USA.
FDA inspections revealed that, food manufacturers enterprises had a high incidence of defects in areas such as sanitary operations, processes and controls, hazard analysis, preventive control measures and personnel management. The FDA maintains continuous oversight of the implementation of corrective actions for inspection observations.
Food manufacturing enterprises exporting to the USA should promptly implement effective rectification and provide responses to identified defects, implement targeted continual improvements, continuously improve their food safety management systems and raise the level of quality management.
To establish a analytical method for detecting pesticide residues of 9 kinds of diamide insecticides in medicinal and edible homologous food by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).
In this experiment, 2.00 g of 4 kinds of medicinal and edible homologous food samples: Lycium barbarum, Fructus Mori, Chrysanthemum morifolium Ramat and Angelica sinensis were selected. The extraction solvent was 0.1% formic acid in acetonitrile, and the extraction procedure involved vortex oscillation for 5 min followed by ultrasonication for 10 min. The extraction salts used were 4 g magnesium sulfate+1 g NaCl+1 g C6H5Na3O7·2H2O+0.5 g C6H6Na2O7·1.5 H2O. The purification method employed 150 mg MgSO4, 50 mg C18 and 50 mg primary secondary amine (PSA) per milliliter of extract.
The results showed that within the range of 2.0–100.0 μg/L, the linear correlation coefficient of 9 kinds of diamide insecticides was greater than 0.999, the method developed in this study demonstrates excellent stability and repeatability. Limit of detection was 3.0 μg/kg and the limit of quantitation was 10.0 μg/kg. When the sample was spiked at levels of 10, 20 and 100 μg/kg, the recovery rates were 70.6%-96.0% and relative standard deviations were 3.4%-9.0% (n=6).
This study addresses the limitations of existing detection methods for diamide insecticide residues by developing a more comprehensive and effective analytical method. The improved methodology enhances the accuracy and reliability of pesticide residue detection in medicinal and edible homologous food, demonstrating significant practical value in ensuring the food safety of these dual-purpose items.
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