Objective To provide a theoretical basis and beneficial reference for the formulation of the local specialty characteristic dairy mooncake standard and the product development of the production and processing enterprises. Methods Dairy mooncakes from Xilingol League, Inner Mongolia was used as experimental samples, the sensory, nutritional, quality, and microbiological characteristics using national food safety standards were analyzed. Results Dairy mooncake samples had a strong milky aroma and high protein content. The results showed that the sensory organs, protein, moisture, sodium, peroxide value, acid value, benzoic acid, sorbic acid, saccharin sodium, lead, total bacterial count, coliform bacteria, mold, Staphylococcus aureus and Salmonella levels in the dairy mooncake samples all met the national limits set by national safety standards. Conclusion The above-mentioned indexes indicate that the local specialty dairy mooncakes exhibit good quality and safety throughout production, processing, storage and distribution. The Xilingol milk-based mooncakes are an innovative combination of dairy products and pastries, which not only broadens the variety of local specialty dairy products but also expands the fusion of milk and flour flavors. More importantly, the Xilingol milk-based mooncakes fill the GB/T 19855—2023 General rules for mooncake quality for “Mongolian-style” milk-based mooncakes with high protein content.

Objective To analyze the overall situation of national food safety supervision and sampling inspection from 2021 to 2023 and the main food safety issues. Methods The food safety supervision and sampling inspection data of the national market regulation departments from 2021 to 2023 were summarized, and the categories of food, unqualified project categories, as well as specific unqualified project were analyzed. Results In the past 3 years from 2021 to 2023, market regulation departments at all levels in China had completed a total of 34 food categories and over 20 million batches of supervision and sampling inspection, with an overall unqualified rate of 2.76%. From the sampling batches, the sampling batches for edible agricultural products and catering food were relatively high, accounting for a total of 51.50%. From the unqualified rate, catering food had the highest unqualified rate of 7.20%, mainly due to the high unqualified rate of catering utensils. The unqualified rate of edible agricultural products (3.44%), vegetable products (3.10%), roasted seeds and nuts products (2.72%) was also relatively high. The analysis results of unqualified project categories showed that in recent years, the main problems had been excessive pesticide residues, microbial contamination, and excessive use of food additives, with a total of 64.78% of unqualified samples. Pesticide residues were mainly found in edible agricultural products such as cowpeas, chives, and celery, etc. The main unqualified projects were imidacloprid, fungicide, chlorpyrifos, etc. The main food categories involved in microbial contamination were instant foods, aquatic products, pastries, fruit products, etc. The main unqualified projects were the total number of colonies, molds, and coliforms. The main food categories with the excessive use of food additives were fruit products, catering food, grain processing products, and seasonings. The main unqualified projects were pigments, aluminum containing additives, preservatives, and seasonings exceed the standard. Conclusion The state should continue to pay attention to key categories in food safety sampling, such as edible agricultural products, catering food, vegetable products, roasted seeds and nuts products, as well as issues such as excessive residues of pesticides and veterinary drugs, microbial contamination, and excessive use of food additives in key projects. The country not only needs to increase sampling efforts, but also strengthens supervision of various links such as production and sales, and strives to ensure food safety.

Mycotoxins are secondary toxic metabolites produced by fungi during their growth and reproduction. They are widely found in various kinds of grain and oil and their products, and can cause serious threat to human health. Mycotoxin contamination has become a common phenomenon and problem in many countries and regions. Mycotoxin detection is the key link to build a mycotoxin prevention and control system. Furthermore, mycotoxins content is one of the health indicators that must be detected in raw grain and its products. It is of great significance to establish accurate and efficient detection methods for mycotoxins in grain, oil and food to ensure food safety. This paper summarized and analyzed the common detection methods of mycotoxins in grain, oil and food, and mainly introduced the different detection techniques and methods and their application characteristics, such as chromatography analysis, spectral analysis and immunoassay. Futhermore, this paper prospected the development trend and related requirements of mycotoxins detection, so as to provide references for the detection and safety supervision of mycotoxins in grain, oil and food.

Objective To achieve rapid and non-destructive determination of aflatoxin B₁ (AFB₁) content in Triticum aestivum L. kernels by establishing a quantitative prediction model based on near-infrared spectroscopy technology. Methods The reflectance spectra of Triticum aestivum L. samples in the wavelength range of 900-1700 nm were collected, and the AFB₁ content in Triticum aestivum L. was determined by high performance liquid chromatography. The raw spectral data of the Triticum aestivum L. samples were subjected to preprocessing, and the feature wavelengths were extracted in order to establish a prediction model. A model for predicting the AFB₁ content was developed using a back propagation neural network (BPNN), random forest (RF), and support vector machine (SVM), the results of this model were compared with those of a full-wavelength modelling approach. Results The SVM model constructed following the application of multiplicative scatter correction (MSC) and competitive adaptive reweighted sampling (CARS) processing demonstrates superior performance compared to the other models and the full-band modelling model. Conclusion The combination of the CARS algorithm and the MSC-CARS-SVM model allows for the rapid and non-destructive detection of AFB₁ content. The feasibility of using near-infrared spectroscopy for quantitative analysis of AFB₁ content has been demonstrated, and this approach can be employed to assess the quality of Triticum aestivum L. during storage.

Objective To rapidly and non-destructively detect aflatoxin in mildly moldy Zea mays using near-infrared spectroscopy (NIRS) technology. Methods Mildly moldy Zea mays samples were selected as experimental materials, with the content of aflatoxin B₁ (AFB₁) as the detection indicator. A total of 153 sample images were collected using the NIRS imaging acquisition system. Three kinds of preprocessing methods, including multiplicative scatter correction, standard normal variate transformation, and moving average smoothing (MAS), were applied to preprocess the raw near-infrared spectral data (RNSD). Backpropagation neural network (BPNN), extreme learning machine, and support vector machine were employed to model and analyze the preprocessed spectral data along with AFB₁ content data, evaluating the impact of preprocessing methods on model performance. Furthermore, the stepwise projection algorithm (SPA) was performed to select characteristic spectra from the preprocessed data for comprehensive comparison after incorporating them into the models. Results The optimal spectral preprocessing method was MAS. Ten characteristic spectra were selected through SPA, and the BPNN model exhibited the best prediction results, achieving a coefficient of determination of 0.932 and a relative prediction deviation of 3.922. This model demonstrated good performance and reliability. Conclusion It is feasible to determine AFB₁ content in mildly moldy Zea mays using NIRS technology. The findings of this study provide an important reference for the application of NIRS in identifying other agricultural products.

Objective To investigate the effects of different storage conditions on the water migration and volatile component changes of Zea mays, and to screen out characteristic volatile components. Methods Low field-nuclear magnetic resonance (LF-NMR) and gas chromatography-ion mobility spectrometry (GC-IMS) technology were used to study the changes in micro moisture, volatile component composition, and relative content of Zea mays under controlled temperature and humidity conditions. Results With the extension of storage time, moisture, fatty acid value, starch, and alcohol soluble protein indicators all undergo certain changes. When stored for 30 days, the moisture content reached equilibrium; the maximum value of fatty acid value was 46.11 mgKOH/100 g when stored at 65% RH for 90 days at 30 ℃, and the fatty acid value was still suitable for storage after 120 days; storing at 20 ℃ was beneficial for the accumulation of starch content; alcohol soluble proteins were significantly affected by temperature; under 65% RH conditions, as the storage temperature increased, the bound moisture content gradually decreased, resulting in the transformation of T20 strongly bound water to T21 weakly bound water and T22 strongly bound water to T23 weakly bound water; under 55% RH conditions, as the storage temperature increased, the bound water content gradually decreased, and the changes in the peaks of non flowing water and free water were consistent with those of bound water; the volatile components in the sample were classified as acids (2 types), aldehydes (20 types), ketones (15 types), alcohols (15 types), esters (12 types), furans (2 types), olefins (3 types), and amines (1 type). Conclusion As the storage temperature increases, the ability of Zea mays to retain moisture gradually weakens, while as the humidity increases, its ability to retain moisture increases. The high temperature and high humidity environment promotes the release of volatile components such as aldehydes and alcohols, while ketones and esters decrease. The 3-pentanone, 1-octen-3-one-M, 1-butanol, 3-methyl-D, 1-hexanol-D, isovaleric acid, methyl ester can be used as characteristic volatile components to distinguish mold growth in high moisture Zea mays, providing reference for the identification of mold growth in high moisture Zea mays.

Objective To establish a rapid colloidal gold card method for the determination of fumonisin and T-2/HT-2 toxin in Triticum aestivum L. and Zea mays. Methods The limit of detection, limit of quantitative, precision and accuracy of the method were evaluated in 6 laboratories. Results The limits of detection of fumonisin and T-2/HT-2 toxin methods were 150 μg/kg and 5 μg/kg, respectively. The limits of quantitation were 450 μg/kg and 11 μg/kg, respectively. When the fumonin content in Triticum aestivum L. and corn ranged from 426.39 to 3897.22 μg/kg, the relationship between the method repeatability standard deviation S_r and reproducibility standard deviation S_R and fumonin content was obtained, namely, repeatability standard deviation S_r=1.478m^0.600 and reproducibility standard deviation S_R=4.269m^0.591. When the T-2/HT-2 toxin content in Triticum aestivum L. and Zea mays ranged from 426.39 to 3897.22 μg/kg, the relation between repeatability standard deviation S_r and reproducibility standard deviation S_R and T-2/HT-2 toxin content m was as follows: Repeatability standard deviation S_r=3.1901m^0.218, reproducibility standard deviation S_R=0.2507m^0.492 (Triticum aestivum L. matrix). Repeatability standard deviation S_r=0.8357m^0.333, reproducibility standard deviation S_R=1.1231m^0.585 (Zea mays matrix). The recoveries of fumonisin and T-2/HT-2 toxin ranged from 95.42% to 101.90% and 83.30% to 118.20% respectively. There was no significant difference between the paired t test and the standard method. Conclusion The method has good accuracy and can be widely used for rapid and quantitative determination of fumonisin and T-2/HT-2 toxin in Triticum aestivum L. and Zea mays.

There are many types of pollutants in food, and exposure involves multiple stages such as raw material, processing, transportation, storage, packaging, and sales. With the improvement of people's requirements for the healthy, nutritive and safe condiments, the pollutants in food have received more and more attention. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) combines the separation ability of liquid chromatography with the advantages of high resolution mass spectrometry, such as wide mass range, fast scanning speed, and high sensitivity, making it an important means in the field of food safety analysis. This review summarized the technical characteristics of quadrupole-time of flight mass spectrometry and quadrupole-orbitrap mass spectrometry, as well as the research progress in the detection of pollutants in food using LC-HRMS technology over the past 5 years. The article focused on the application of LC-HRMS in the targeted and non-targeted determination of pesticides residues, veterinary drugs and their metabolites, food additives, illegal additives and mycotoxins, and prospected the development trend. Aiming to provide reference for the detection of pollutants in food in the future.

Edible agricultural products are primary products derived from agriculture, forestry, livestock husbandry and fishery, which are important components of people's daily diet. The widespread use of pesticides in recent years has effectively promoted agricultural development, but the problem of pesticide residue pollution caused by illegal use of banned or restricted pesticides and unscientific pesticide application has attracted considerable attention to the safety of edible agricultural products. As an agricultural powerhouse, China has a fairly comprehensive range of pesticides, and new pesticides are constantly emerging. Therefore, effective regulation of pesticide residues in edible agricultural products, as well as exploration of more convenient, quick, efficient, and sensitive detection methods, has become an important research topic for the inspection and testing industry. This paper briefly summarized pesticide residues in edible agricultural products, focused on the relevant technical methods of pesticide residues detection in edible agricultural products, and looked forward to new detection technologies and methods, in order to provide references for improving the detection of pesticide residues in edible agricultural products, and ensure food safety and people's health.

Objective To prepare a polydopamine (PDA)-based lateral flow immunochromatography assay for the highly sensitive detection of deoxynivalenol (DON) in cereals. Methods In this paper, PDA was synthesized by dopamine self-oxidative polymerization, and the PDA labeled monoclonal antibody (PDA-mAb) probe was prepared by a one-step conjugation method. Subsequently, the PDA lateral flow immunochromatography assay was established using DON antigen as the test line (T line) and goat anti-mouse antibody as the control line (C line). Results The results showed that the cut-off value of the PDA lateral flow immunochromatography assay for detecting DON was 6.0 ng/mL, the visual limit of detection was 0.9 ng/mL, half maximal inhibitory concentration was 1.13 ng/mL, which were 0.88 times and 3.08 times higher than those of fluorescent microsphere test strip and colloidal gold test strip, respectively. Meanwhile, the PDA lateral flow immunochromatography assay possessed well stability and specificity. In addition, the proposed lateral flow immunochromatography assay has been successfully used for the detection of DON in corn, millet, and oats samples, with minimum detection limits of 8.40, 6.87, and 9.89 μg/kg, recoveries ranging from 80.10%-122.05%, and relative standard deviations less than 12.01%. Conclusion In summary, the PDA lateral flow immunochromatography assay established in this work is sensitive, accurate, rapid and simple, and provides technical support for the detection of mycotoxins in cereals.