Pork quality is an economically critical trait in swine production, necessitating rapid and accurate evaluation methods to optimize processing efficiency and ensure trade compliance. Recent advancements in artificial intelligence algorithms and sensor technologies have driven the development of non-destructive detection methods based on artificial intelligence, which are now widely applied in the meat industry. Integrating digital image processing with artificial intelligence learning algorithms and multi-sensor data fusion to achieve automated, real-time monitoring of pork quality throughout processing chains represents a pivotal research direction for ensuring meat safety and quality. This article summarized the current key technologies for non-destructive testing of pork quality, including near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, fluorescence spectroscopy, terahertz spectroscopy, electronic nose/tongue technology and computer vision systems, elaborated the principles, characteristics and application status of different technologies, and discussed and forecasted the shortcomings and future development directions of different technologies, aiming to provide reference for the application of non-destructive testing technology in pork quality evaluation.

Objective To establish a qualitative identification model and rapid identification method of local mutton in Henan province by using near infrared spectroscopy and fisher method. Methods A total of 181 mutton samples were selected from 5 local sheep breeds and 1 Huyang breed in Henan Province, and dried powder samples were prepared. Spectral scanning was performed in the wavelength range of 1400-2500 nm, and discrimination models were established through different pretreatment. Results The results showed that the spectral patterns of different breeds of mutton showed the same trend, and the original spectra could be used to identify sheep and goats with an accuracy of 94.0% and 85.0%, respectively. After spectrum processing by smoothing, first-order derivation, multiplicative scatter correction (MSC) and other different methods, the discrimination accuracy was improved, among which the combination of first-order derivation+MSC had the best effect, the discrimination accuracy of 1400-2500 nm wavelength was 100.0%, and the cross-validation rate was 92.8%. When the model was used to identify 6 varieties of mutton, the accuracy of calibration set reached 100.0%, the cross-validation rate was above 87.5%, and the prediction set of 4 varieties reached 100.0%. After wavelength segmentation, the prediction accuracy for the range of 1400-1620 nm was the best, but the accuracy of individual identification decreased; For different discrimination methods, the identification accuracy of sophora goat was all above 95.0%. Conclusion In summary, near infrared spectroscopy technology in the long-wave range of 1400-2500 nm could accurately identify the variety of mutton, of which the first derivative+MSC preconditioning was the best. For the different varieties, the accuracy of sophora goats was the highest.

Objective To establish a safety, rapid, cost-effective and reliable analytical method for trace elements detection in aluminum foil based on fiber laser induced breakdown spectroscopy. Methods Using standards to evaluate analytical sensitivity and limit of detection of fiber laser induced breakdown spectroscopy after optimization of laser pulse width, pulse energy, repetition rate and baseline-correction, and the optimized method was applied to analyze trace elements in aluminum foil samples. Results Calibration curves for most elements achieved regression coefficients up to 0.99. Detection sensitivity and limit of detection followed the descending order of Mn>Cr>Cu>Ti>Mg>Fe>Zn>Si, and the average relative error of leave-one-out cross validation of all the elements was 14.45%. The detection results of 8 kinds of trace elements in 27 kinds of aluminum foil samples showed that Fe and Si were frequently detected, while Cu and Ti elements were rarely detected and Cr, Mg, Mn and Zn elements were not detected. Conclusion This method requires no sample preparation, offers rapid analysis speed, and enables simultaneous multi-element detection with high sensitivity, which promisingly makes it a reliable approach for rapid determination of trace elements in aluminum foil.

Objective To establish a rapid quantitative detection method for ester content in Nongxiangxing crude Baijiu by using mid-infrared spectroscopy. Methods The mid-infrared spectroscopy analysis technology combined with gas chromatography was used to detect Nongxiangxing crude Baijiu. Partial least squares method was employed to establish mid-infrared quantitative detection models for ethyl hexanoate, ethyl acetate, ethyl lactate, and ethyl butyrate in Nongxiangxing crude Baijiu. Results The detection models for ethyl hexanoate, ethyl acetate and ethyl lactate exhibited linear coefficients (r²) exceeding 0.99 and root mean square error were below 0.07 g/L, indicating that the models had good goodness of fit and stability. The average relative error of the prediction results after external validation was lower than 3.50%, indicating that the models had good detection performance and the predicted values were close to the true values. Due to its low content and narrow spectral range, the prediction effect of the model for ethyl butyrate was poor. Conclusion This method have a good detection ability for the contents of ethyl hexanoate, ethyl acetate and ethyl lactate in Nongxiangxing crude Baijiu. It can meet the basic needs of enterprises for the rapid detection and analysis of crude Baijiu in daily production, providing a new development direction for the rapid detection analysis, and grading of Baijiu.

Fusarium toxins are toxic and harmful secondary metabolites produced by toxigenic Fusarium spp. during infection in grains. Contamination with Fusarium toxins threatens the safety of staple grains and animal health. In recent years, with the deepening of toxin research and the development of detection technologies, modified mycotoxins with changed chemical structures and biochemical properties have been detected. These modified mycotoxins are produced during processing, or through chemical or biological reactions in plants, animals or microorganisms, and could not be identified by conventional detection. Modified toxins can be transduced through the food chain and release free toxins after animal consumption. This article reviewed the recent research progress of modified Fusarium toxins, including the modification types, natural occurrence, toxicology, which would provide references for the comprehensive assessment of the contamination risk of Fusarium toxins in grains and control strategies development.

Fusarium is a ubiquitous pathogen worldwide that can affect the growth and development of plants and pose a serious threat to global food security and biodiversity. Almost all Fusarium bacteria produce mycotoxins, which are diverse and pathogenic. The most toxic ones include trichothecenes, zearalenone (ZEA) and fumonisins. On the one hand, mycotoxins, as pathogenic agents, can infect a wide range of plants, leading to symptoms such as stunted growth, fruit or seed rot, yellowing of leaves, wilting, ulceration, and root or stem rot. These effects result in significant crop damage and economic losses, making mycotoxin contamination a major concern in agriculture. On the other hand, Fusarium is also considered to be the causative agent of fungal infections in humans and animals, and its toxins contaminate cereals and food, causing related pathologies in humans and animals, and have a wide range of clinical manifestations in immunocompromised patients. Most often, Fusarium is difficult to control because the fungus easily overcomes host resistance to various control methods. This review summarized the latest research on Fusarium, exploring its interaction mechanisms with plants and its impact on food security. Additionally, it provided a detailed overview of various methods for detecting Fusarium, aiming to promote research on the comprehensive management of this inevitable food contaminant to support the sustainable development of global food security.

With the increasing attention to food safety and environmental quality, efficient and accurate pollutant detection technology is crucial. Supramolecular solvent microextraction technology, as an emerging sample pretreatment method, has demonstrated unique advantages in the field of food and environmental pollutant detection due to its high efficiency, good selectivity and environmental friendliness. This technology is based on the selective recognition and enrichment ability of specific pollutants by supramolecular solvents (such as nano/micro scale solvents formed by host molecules such as cyclodextrin and crown ether), and achieves rapid separation and concentration of target substances in samples through microextraction operations. As a new type of green solvent, supramolecular solvents have high extraction efficiency, wide polarity range, customizable structure, and both extraction and purification effects, making them widely used in the field of extraction and separation. This review introduced the properties of supramolecular solvents and types of supramolecular solvent microextraction, with a focus on the detailed application of this technology in the detection of food and environmental pollutants, and provided prospects for the work in this field, in order to provide reference for the promotion and application of supramolecular solvent-microextraction technology.

Objective To establish a method for simultaneous determination of 50 kinds of antibiotics in dried sea cucumbers by multifunctional purification column combined with ultra performance liquid chromatography-tandem mass spectrometry. Methods The sample was extracted with 50% acetonitrile aqueous solution. After purification by multifunctional purification column, 50 kinds of antibiotics were separated using Waters ACQUITY UPLC HSS T3 (100 mm×2.1 mm, 1.8 μm) column with acetonitrile and 0.1% formic acid aqueous solution (include 5mmol/L ammonium acetate) for gradient elution. The mass spectrum was performed by electrospray positive ion mode scanning and multi-reaction monitoring acquisition, and quantified by external standard method. Results The results showed that 50 kinds of antibiotics exhibited good linearity in the range of 0.1-100.0 ng/mL, and the correlation coefficients were all greater than 0.99. The limit of detection ofthe method was 0.1-2.0 µg/kg, the limit of quantitation was 0.5-5.0 μg/kg. Recovery tests were carried out at 3 levels (1 times, 2 times, 10 times of the limit of quantitation) in the blank matrix, the average recoveries of the limit of detection were in the range of 54.83%-120.01%, and all the relative standard deviations (n=6) were 0.08%-9.15%. Conclusion This method has the technical advantages of simple operation process, excellent detection sensitivity, reliable precision, and good reproducibility, it can be applied to rapid screening and qualitative and quantitative detection of multiple antibiotics in dried sea cucumbers.

Objective To investigate the effects of high-voltage electric field (HVEF), acidic electrolyzed water (AEW) and their combined treatment on γ-aminobutyric acid (GABA) enrichment in germinating Fagopyrum esculentum. Methods Fagopyrum esculentum seeds were respectively treated with HVEF, AEW, and the combined AEW+HVEF treatment. Morphological indices (100-seed weight, germination rate, shoot length), GABA content, and activities of glutamate decarboxylase (GAD), γ-aminobutyric acid transaminase (GABA-T) and succinic semialdehyde dehydrogenase (SSADH) were measured at different time points during germination (0, 8, 12, 32 and 40 h) to analyze the effects of different treatments on GABA enrichment. Results All treatments increased GABA content in Fagopyrum esculentum, with the combined treatment showing a more significant effect. Under the combined treatment, GABA content in germinating Fagopyrum esculentum reached 198.72 mg/100 g at 24 h of germination, which was 35.6% higher than the control group, and 8.3% and 6.1% higher than the AEW and HVEF single-treatment groups, respectively, demonstrating a significant synergistic effect. The dual regulation of the combined treatment promoted GABA accumulation by activating GAD activity and inhibiting GABA-T and SSADH activities. Conclusion This study analyzes the changes in enzyme activities of the GABA metabolic pathway during Fagopyrum esculentum germination, revealing that the combined treatment of HVEF and AEW achieves efficient GABA enrichment through a dual mechanism of “activating synthesis enzymes and inhibiting decomposition enzymes”. The findings provide a new method for developing functional germinated Fagopyrum esculentum foods.

Objective To establish and evaluate the application of direct mercury analysis for the determination of total mercury in food. Methods A direct mercury analysis method was developed based on catalytic pyrolysis-gold amalgamation atomic absorption spectroscopy. By stepwise optimization of pyrolysis temperatures (150 °C/550 °C for low-concentration ranges and 200 °C/650 °C for high-concentration ranges) and carrier gas flow rates (150-200 mL/min), plant-derived samples (e.g., rice, jujube), animal-derived samples (e.g., snakehead, fish meal), and 14 kinds of food samples were analyzed. The method’s detection limit, accuracy, stability and spike recovery were evaluated to assess its performance and matrix applicability. Results The method established dual linear calibration curves of 0-10 ng and 25-200 ng, with correlation coefficients of 0.9993 and 0.9998, respectively. The limit of detection and limit of quantitation were 0.0002 mg/kg and 0.0005 mg/kg, respectively. Spike recoveries ranged from 90% to 116%, the intra-day and inter-day repeatability relative standard deviation was less than or equal to 6.5% and less than or equal to 7.7%, respectively. The method was systematically validated for complex matrices, including plant-derived, animal-derived, and processed foods, with all results complying with the GB 2762-2022 National food safety standard-Limits of contaminants in foods. Conclusion The proposed method eliminates the need for chemical digestion in sample pretreatment, significantly shortens the analytical time, and prevents mercury volatilization losses. It overcomes the limitations of single-matrix analysis and achieves rapid total mercury detection in diverse complex food matrices, thereby providing an efficient and reliable technical solution for food safety risk monitoring and regulatory compliance.