Characterization of stewed beef by sensory evaluation and multiple intelligent sensory technologies combined with chemometrics methods

Insights into the flavor endowment of aroma-active compounds in cloves (Syzygium aromaticum) to stewed beef

Clove (Syzygium aromaticum) is one of the most commonly used spices in stewed beef to enrich and improve its aroma during the stewing process. Gas chromatography ion mobility spectroscopy (GC-IMS), Q Exactive GC-Orbitrap-MS-O (QE-GC-MS/O), combined with sensory evaluation were employed to analyze the flavor endowment of aroma-active compounds in cloves to stewed beef. A total of 173 volatiles were identified in the clove powder (CP), stewed beef with clove (SBC), and stewed beef with salt (SBS), of which 21 volatiles were considered as aroma-active compounds. The concept of flavor endowment of aroma-active compounds in cloves was defined innovatively, and the endowment rate values (ERVs) of stewed beef were calculated. Nine aroma-active compounds in cloves were found to have a flavor endowment effect on stewed beef, while the terpenoids exhibited high ERVs. Despite the low ERV of eugenol, it still significantly impacted the aroma profile of SBC due to its high odor activity value (OAV) and flavor dilution (FD) factor. These volatiles offered mainly the clove, herbal, anise, and floral odor to stewed beef, which was also confirmed by sensory evaluation. These findings indicated that the terpenoids, phenolics and ethers in cloves had a significant influence on the overall aroma of stewed beef through the flavor endowment, which contributed to the precise use of cloves and improved the aroma of stewed beef.

Comprehensive foodomics analysis reveals key lipids affect aroma generation in beef

Lipids are vital precursors to beef aroma compounds, but the exact lipid molecules influencing aroma generation remain unconfirmed. This study employs gas chromatography-olfactometry-mass spectrometry and absolute quantitative lipidomics to identify beef's aroma and lipid profiles and to examine lipid alterations post-thermal processing. The aim is to understand the role of lipids in aroma generation during beef's raw-to-cooked transition. Eighteen key aroma compounds were identified as significant contributors to the aroma of beef. 265 lipid molecules were quantified accurately, and we found that triglycerides containing C18:1 or C18:2 chains, such as TG(16:0_18:1_18:1), TG(16:0_18:1_18:2), TG(16:0_16:1_18:1), as well as phosphatidylcholine and phosphatidylethanolamine containing PC(16:1e_20:4), PC(16:0e_20:4), PC(18:2e_18:2), and PE(16:1e_20:4), played important roles in the generation of key aroma compounds in beef. C18:1, C18:2, C18:3, and C20:4 were key substrates for the formation of aroma compounds. In addition, lysophosphatidylcholine and lysophosphatidylethanolamine containing unsaturated fatty acid chains may serve as important aroma retainers.

Chemometrics methods, sensory evaluation and intelligent sensory technologies combined with GAN-based integrated deep-learning framework to discriminate salted goose breeds

The authenticity of salted goose products is concerning for consumers. This study describes an integrated deep-learning framework based on a generative adversarial network and combines it with data from headspace solid phase microextraction/gas chromatography-mass spectrometry, headspace gas chromatography-ion mobility spectrometry, E-nose, E-tongue, quantitative descriptive analysis, and free amino acid and 5'-nucleotide analyses to achieve reliable discrimination of four salted goose breeds. Volatile and non-volatile compounds and sensory characteristics and intelligent sensory characteristics were analyzed. A preliminary composite dataset was generated in InfoGAN and provided to several base classifiers for training. The prediction results were fused via dynamic weighting to produce an integrated model prediction. An ablation study demonstrated that ensemble learning was indispensable to improving the generalization capability of the model. The framework has an accuracy of 95%, a root mean square error (RMSE) of 0.080, a precision of 0.9450, a recall of 0.9470, and an F1-score of 0.9460.

A comprehensive analysis of aroma quality and perception mechanism in ginger-infused stewed beef using instrumental analysis, sensory evaluation and molecular docking

The ginger-infused stewed beef exhibited a satisfactory odor in Chinese cooking meat. This study aimed to reveal its aroma quality and perception mechanism through electronic nose, sensory evaluation and gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS) coupled with chemometric methods and molecular docking. Sensory evaluation and electronic nose analysis indicated ginger could greatly modify aroma profile of beef. Most C6-C10 aldehydes significantly decreased and terpenes increased in ginger-infused stewed beef. Orthogonal partial least squares-discriminant analysis (OPLS-DA) found 7 key markers for distinguishing stewed beef with or without ginger. Ginger additions could reduce fatty acids consumption. Moreover, the key contributors of fatty, bloody, meaty, ginger and mint aroma attributes, namely (E)-2-octenal, 1-octen-3-ol, 2-acetylthiazole, zingiberene and γ-elemene, respectively, selected by partial least squares regression (PLSR) analysis were docked with the olfactory receptor. Hydrogen bonds and hydrophobic interactions were the main interaction forces between olfactory receptor and the five compounds.

Utilizing superheated steam to prepare traditional Chinese twice-cooked pork bellies, exploring its effects on the texture and flavor of fat layers

Fat greatly impacts the overall texture and flavor of pork belly. Twice-cooked pork bellies (TPB), typically boiled and sliced before "back to pot" being stir-fried, is a classic Sichuan cuisine among stir-fried dishes. In this study, the effects of substituting conventional pan-frying (PCV) with superheated steam (SHS) technology on the sensory, texture, microstructure and flavor of the fat layers were investigated. SHS was used as an alternative to boiling (120 °C for 15, 20, 25, and 30 min), and "back to pot" stir-frying was also by SHS. TPB precooked for 25 min (P25) with SHS performed better quality characteristics than PCV, with less collagen fiber disruption and lipid droplet area, resulting in a lower hardness and higher shear force. Besides, the low-oxygen environment of SHS retarded the lipid peroxidation, showing a significantly lower MDA content than PCV. Differently, PCV exhibited more grassy and fatty flavors, while P25 exhibited a unique aroma of fruity and creamy due to its higher UFA/SFA ratios in the pre-cooking stage. Overall, the sensory scores of P25 were comparable to those of PCV (with no significant difference), revealing that SHS is expected to be applied to the industrial production of stir-fried dishes.

Effect of cooking methods on volatile compounds and texture properties in millet porridge

To instruct the production of millet porridge, the effect of cooking methods on flavor and texture of millet porridge was investigated. A total of 91 volatiles were detected and most volatile compounds decreased with cooking time, e.g. alcohols. The esters as major volatiles had a high content in electric rice cooker (IC). Multiple chemometric results indicated that volatiles from different cooking methods were distinguished respectively. Texture analysis indicated that the hardness of millet porridge prepared in IC had a more dominant decrease trend than electromagnetic oven and the electric pressure cooker before 40 min. In conclusion, different cooking methods had a more significant influence on the volatiles than cooking time, while the texture is opposite. The comprehensive sensory score reached its peak in IC-30 min. The comprehensive sensory scores of IC and EC decreased with the prolongation of cooking time. This study helps to improve the sensory attributes of millet porridge.

Identification of volatile differential markers in strong-aroma Baijiu based on gas chromatography-electronic nose combined with gas chromatography-time-of-flight mass spectrometry

BACKGROUND

Baijiu is a traditional Chinese liquor produced from grains through fermentation, distillation, aging and blending. The flavor of Baijiu is influenced by factors such as raw materials, starter, processes and the environment, and since the relationship between these factors and the flavor of Baijiu is still being analyzed, the identification of different Baijiu is still somewhat difficult. In this paper, the volatile differential markers of 42 types of strong-aroma Baijiu of different origin, alcohol content and grade were explored.

RESULTS

A total of 24 volatile substances were detected by gas chromatography-electronic nose (GC-E-Nose) and 99 volatile substances were detected by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS). The peak areas of the substances obtained by GC-E-Nose were analyzed by the partial least squares (PLS) method, and the substances with variable importance in projection (VIP) >1 were screened out. Combined with the qualitative results of GC-TOF MS, four substances (isobutyric acid, 2-butanone, 2,3-butanediol and 3-methylbutyric acid) were selected as volatile differential markers for strong-aroma Baijiu. An external standard curve was established to accurately quantify these four substances, and the Kruskal-Wallis test confirmed that the absolute contents of these four substances varied significantly among different samples (P < 0.01). Principal component analysis and hierarchical cluster analysis based on the absolute content of these four substances showed that different samples were prioritized for different alcohol contents.

CONCLUSION

These four substances can be used as volatile differential markers of strong-aroma Baijiu samples. This research provides theoretical support for the detection and improvement of Baijiu product quality. © 2024 Society of Chemical Industry.

Characterization of flavor profile of Steamed beef with rice flour using gas chromatography-ion mobility spectrometry combined with intelligent sensory (Electronic nose and tongue)

The intelligent senses (Electronic nose and tongue), were combined with headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and free amino acid were used in combination to determine the aroma and taste components during the processing of Chinese traditional dish Steamed beef with rice flour (SBD). The findings revealed that E-nose and E-tongue, could clearly distinguish and identify the aroma and taste of SBD. A total of 66 volatile substances and 19 free amino acids were identified by HS-GC-IMS and amino acid analyzer, respectively. The highest contribution to aroma in the production of SBD was alcohols, esters and aldehydes. Further analysis of relative odor activity showed that 3-Methylbutanol-D, 3-Methylbutanol-M and 3-Methylthio propanal is the marinating stage (T2) main aroma components. Ethyl 3-methylbutanoate-M and Ethyl 3-methylbutanoate-D were the main aroma components in the seasoning stage (T3). Additionally, the calculation of the taste activity value showed that Glutamic contributed significantly to the umami of SBD. Alanine was a representative taste component in the marinating stage (T2), while Proline, Aspartic, Lysine, Glutamic, Valine, Arginine, and Histidine were characteristic amino acids of the seasoning stage (T3). Consequently, this study offers valuable insights into the industrial-scale production and flavor regulation of SBD products.

A novel olfactory biosensor based on ZIF-8@SWCNT integrated with nanosome-AuNPs/Prussian blue for sensitive detection of hexanal

Hexanal is considered as an important volatile compound indicator for the assessment of freshness and maturity of foods. Therefore, sensitive and stable monitoring of hexanal is highly desired. Herein, an efficient receptor immobilization strategy based on ZIF-8@ Single-walled carbon nanotube (SWCNT) and nanosomes-AuNPs/Prussian blue (PB) was proposed for the development of olfactory biosensors. ZIF-8@SWCNT as dual support materials provided a high density of active sites for nanosomes loading. Moreover, the co-electrodeposition of nanosomes-AuNPs and PB on the sensor interface effectively amplified the electrochemical signal and maintained the activity of the receptor. The combination of ZIF-8@SWCNT with AuNPs/PB imparts excellent sensing performance of the biosensor with a wide detection range of 10-16-10-9 M, a low detection limit of 10-16 M for hexanal, and a long storage stability of 15 days. These results indicate that our biosensor can be a powerful tool for versatile applications in food and other related industries.

Insights into the starch and proteins molecular structure changes of foxtail millet sourdough: Effect of fermentation from grains of cereal to pre-meal

This study investigated the effects of foxtail millet sourdough fermentation time (0, 8, 16, and 24 h) on the protein structural properties, thermomechanical, fermentation, dynamic rheological, starch granules crystalline regions molecular mobility, and starch microstructural characteristics. The fermentation led to a significant increase in the concentration of free amino acids from protein hydrolysis. Fourier transform infrared spectroscopy (FTIR) revealed changes in protein secondary structure and the presence of functional groups of different bioactive compounds. The result of thermomechanical properties showed a significant increase in the stability (0.70-0.79 min) and anti-retrogradation ability (2.29-3.14 Nm) of lactic acid bacteria (LAB) sourdough compared to the control dough, showing a wider processing applicability with radar profiler index. In contrast, sourdoughs with lower tan δ values had higher elasticity and strength. Scanning electron microscopy showed that the surface of the starch appeared from smooth to uneven with patchy shapes and cavities, which declined the crystallinity from 34.00 % to 21.57 %, 23.64 %, 25.09 %, and 26.34 % respectively. Fermentation changed the To, Tp, Tc, and ΔH of the starch. The results of the study will have great potential for application in the whole grain sourdough industry.

Molecular mechanism for the influence of yam starch multiscale structure on the sensory texture of cooked yam

Yam is a dual-purpose crop as both medicine and food. However, the mechanism controlling the eating quality of yam remains to be elucidated. This study explored the influence of starch multiscale structure on the texture of yam. The results indicated that FS and RC yam have higher hardness and chewiness, while BZ, XM, and PL yam possess waxiness, Fineness, and Stickiness. Statistically, high amylose (AM) can increase hardness, chewiness, and compactness; and average molecular size (Rh) is positively correlated with stickiness, fineness, and waxiness. Specifically, medium- and long-chain amylose (1000 < X ≤ 10,000) and amylopectin (24 < X ≤ 100), particularly medium-chain amylose (1000 < X ≤ 5000) and long-chain amylopectin (24 < X ≤ 36), primarily affect sensory and rheological stickiness. The long chains of amylose form a straight chain interspersed in the crystalline and amorphous regions to support the entire lamellar structure. Higher proportion of amylose long chains, promoting the starch's structural rigidity, which in turn enhanced its hardness-related attributes. Moreover, a higher ratio of long chains within amylopectin results in tightly intertwined adjacent outer chains, forming double helix crystalline zones. This consequently augmenting the texture quality linked to stickiness-related attributes.

A new comprehensive quantitative index for the assessment of essential amino acid quality in beef using Vis-NIR hyperspectral imaging combined with LSTM

The quality of beef is usually predicted by measuring a single index rather than a comprehensive index. To precisely determine the essential amino acid (EAA) contents in 360 beef samples, the feasibility of optimized spectral detection techniques based on the comprehensive EAA index (CEI) and comprehensive weight index (CWI) constructed by factor analysis was explored. Two-dimensional correlation spectroscopy (2D-COS) was used to analyse the mechanisms of spectral peak shifts in complex disturbance systems with CEI and CWI contents, and 15 sensitive feature variables were extracted to establish a quantitative analysis model of a long short-term memory network (LSTM). The results indicated that 2D-COS had good predictive performance in both CEI-LSTM (R2P of 0.9095 and RPD of 2.76) and CWI-LSTM (R2P of 0.8449 and RPD of 2.45), which reduced data information by 88%. This indicates that utilizing 2D-COS can eliminate collinearity and redundant information among variables while achieving data dimensionality reduction and simplification of calibration models. Furthermore, a spatial distribution map of the comprehensive EAA content was generated by combining the optimal prediction model. This study demonstrated that the comprehensive index method furnishes a new approach to rapidly evaluate EAA content.

Evaluation of the aroma and taste contributions of star anise (I. Verum hook. f.) in braised duck leg via flavor omics combined with multivariate statistics

To promote the rationalized and standardized application of star anise in braised poultry products, the effects of different concentrations of star anise (0 %, 0.1 %, 0.2 %, 0.3 %, and 0.4 %) on the aroma and taste compounds intensities of braised duck legs from the perspective of flavor were evaluated by using flavor omics approach combined with multivariate statistics. The volatile flavor results showed that there were 17 key aroma compounds with odor activity values (OAVs) > 1, including aldehydes, alcohols, ketones, furans, hydrocarbons, and ethers. Most of the aroma compounds related to lipid oxidation were significantly inhibited when the concentration of star anise reached 0.2 %, especially inhibited the concentrations of the unpleasant off-odorants containing hexanal, heptanal, 1-octen-3-ol, and 2-pentyl-furan by 30.27 %, 15.08 %, 30.30 %, and 41.63 %, respectively. And the flavor intensities of these compounds were negatively correlated with the concentration of star anise. Additionally, star anise gave braised duck legs characteristic aroma such as floral and herbal notes. The taste results revealed that the maximum umami value (4.36 g MSG/100 g) of braised duck legs was observed when the concentration of star anise reached 0.2 %. Six flavor markers were obtained via PLS-DA model, and the flavors of braised duck legs with different concentrations of star anise were distinguished. This study provided a vital theoretical basis for the rational application and flavor control of star anise in braised poultry products.

From amino acid analysis to improved gel properties: The role of dl-valine in Landaise goose myofibrillar protein

The impact of exogenous limiting amino acids on protein gel formation was investigated to enhance the gelation properties of Landaise goose myofibrillar protein (MP). Amino acid composition and gel properties were analyzed, and homologous protein modeling and molecular docking techniques were used to simulate binding sites. Valine was identified as the first limiting amino acid. The addition of 0.075 % dl-valine proved optimal to enhance the gel strength (59.5 g) and water retention (76.76 %) of MP gels. Hydrophobic interactions and disulfide bonds were found to be the main forces maintaining conformational stability of the MP-dl-valine gels. The propyl group of dl-valine can form hydrophobic interactions with protein, contributing to stable complexes. DL valine could also strengthen chemical bonds and secondary structure, convert free water to immobile water, and improve the microstructure of the gel. Therefore, valine can be utilized as a nutritional and gel enhancer in Landaise goose meat products.

Characterization of Flavor Profile of Sauced Pork from Different Regions of China Based on E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectroscopy

This study aimed to investigate the volatile flavor compounds and tastes of six kinds of sauced pork from the southwest and eastern coastal areas of China using gas chromatography-ion mobility spectroscopy (GC-IMS) combined with an electronic nose (E-nose) and electronic tongue (E-tongue). The results showed that the combined use of the E-nose and E-tongue could effectively identify different kinds of sauced pork. A total of 52 volatile flavor compounds were identified, with aldehydes being the main flavor compounds in sauced pork. The relative odor activity value (ROAV) showed that seven key volatile compounds, including 2-methylbutanal, 2-ethyl-3, 5-dimethylpyrazine, 3-octanone, ethyl 3-methylbutanoate, dimethyl disulfide, 2,3-butanedione, and heptane, contributed the most to the flavor of sauced pork (ROAV ≥1). Multivariate data analysis showed that 13 volatile compounds with the variable importance in projection (VIP) values > 1 could be used as flavor markers to distinguish six kinds of sauced pork. Pearson correlation analysis revealed a significant link between the E-nose sensor and alcohols, aldehydes, terpenes, esters, and hetero-cycle compounds. The results of the current study provide insights into the volatile flavor compounds and tastes of sauced pork. Additionally, intelligent sensory technologies can be a promising tool for discriminating different types of sauced pork.

Classification of oolong tea varieties based on computer vision and convolutional neural networks

BACKGROUND

In the contemporary food industry, accurate and rapid differentiation of oolong tea varieties holds paramount importance for traceability and quality control. However, achieving this remains a formidable challenge. This study addresses this lacuna by employing machine learning algorithms - namely support vector machines (SVMs) and convolutional neural networks (CNNs) - alongside computer vision techniques for the automated classification of oolong tea leaves based on visual attributes.

RESULTS

An array of 13 distinct characteristics, encompassing color and texture, were identified from five unique oolong tea varieties. To fortify the robustness of the predictive models, data augmentation and image cropping methods were employed. A comparative analysis of SVM- and CNN-based models revealed that the ResNet50 model achieved a high Top-1 accuracy rate exceeding 93%. This robust performance substantiates the efficacy of the implemented methodology for rapid and precise oolong tea classification.

CONCLUSION

The study elucidates that the integration of computer vision with machine learning algorithms constitutes a promising, non-invasive approach for the quick and accurate categorization of oolong tea varieties. The findings have significant ramifications for process monitoring, quality assurance, authenticity validation and adulteration detection within the tea industry. © 2023 Society of Chemical Industry.

Elucidating the effect of different processing methods on the sensory quality of chestnuts based on multi-scale molecular sensory science

Chestnuts are known for their unique flavor and nutritional value. However, the flavor changes in chestnuts after processing remain unclear. Multi-intelligent sensory technologies and headspace solid-phase microextraction-arrow gas chromatography-mass spectrometry (HS-SPME-Arrow-GC-MS) combined with multivariate statistical analysis were applied to evaluate the effect of packaging and heat sterilization procedures on the sensory quality of chestnuts. The results showed that the significant variations (p < 0.05) between the different chestnut processing methods were revealed via the electronic eye (E-eye), electronic nose (E-nose), and electronic tongue (E-tongue). The packaging had a more significant influence on the sensory quality of the chestnuts than heat sterilization procedures. HS-SPME-Arrow-GC-MS identified 83 volatile compounds. The processed chestnuts exhibited higher aldehyde, ester, and alkene concentrations, while N2 packaging was more favorable to flavor elicitation and retention. Therefore, combining intelligent sensory techniques with GC-MS can rapidly determine the chestnut quality and guide industrial production.

Spectral data fusion in nondestructive detection of food products: Strategies, recent applications, and future perspectives

In recent years, the food industry has shown a growing interest in the development of rapid and nondestructive analytical methods. However, the utilization of a solitary nondestructive detection technique offers only a constrained extent of physical or chemical insights regarding the sample under examination. To overcome this limitation, the amalgamation of spectroscopy with data fusion strategies has emerged as a promising approach. This comprehensive review delves into the fundamental principles and merits of low-level, mid-level, and high-level data fusion strategies within the domain of food analysis. Various data fusion techniques encompassing spectra-to-spectra, spectra-to-machine vision, spectra-to-electronic nose, and spectra-to-nuclear magnetic resonance are summarized. Moreover, this review also provides an overview of the latest applications of spectral data fusion techniques (SDFTs) for classification, adulteration, quality evaluation, and contaminant detection within the purview of food safety analysis. It also addresses current challenges and future prospects associated with SDFTs in real-world applications. Despite the extant technical intricacy, the ongoing evolution of online data fusion platforms and the emergence of smartphone-based multi-sensor fusion detection technology augur well for the pragmatic realization of SDFTs, endowing them with formidable capabilities for both qualitative and quantitative analysis in the realm of food analysis.

Changes provoked by altitudes and cooking methods in physicochemical properties, volatile profile, and sensory characteristics of yak meat

The present study aimed to shed light on the effects of altitudes and three cooking methods (boiling, steaming, and roasting) on the physicochemical quality, volatile profile, and sensorial characteristics of yak meat. Composite meat samples were prepared to represent each cooking method and altitude level from the longissimus thoracis et lumborum (LTL) muscle of nine yaks. The techniques employed were gas chromatography-mass spectrometry (GC-MS) and electronic nose (E-nose) along with chemometrics analysis to study the changes occurring in yak volatile profile, and TBARS measurement in lipid oxidation during cooking. Among the cooking methods, boiling and steaming exhibited higher protein and fat content while lower volatile compound contents. Additionally, roasted yak meat received the highest sensory scores, along with decreased L*-values, while elevated a*- and b*-values, and tenderness. A total of 138 volatile compounds were detected, and among them, 36 odorants were identified as odor-active compounds in cooked yak meat. It is evidenced that low-altitude yak presented more complex and richer flavor profiles than high-altitude ones. Moreover, yak meat from low- and high-altitude was classified into two groups by an electronic nose (E-nose) owing to distinct flavor characteristics. Overall, roasted yak meat originating from low altitudes tends to be more popular from a sensory perspective.

Predicting VOCs content and roasting methods of lamb shashliks using deep learning combined with chemometrics and sensory evaluation

A comparison was made between the traditional charcoal-grilled lamb shashliks (T) and four new methods, namely electric oven heating (D), electric grill heating (L), microwave heating (W), and air fryer treatment (K). Using E-nose, E-tongue, quantitative descriptive analysis (QDA), and HS-GC-IMS and HS-SPME-GC-MS, lamb shashliks prepared using various roasting methods were characterized. Results showed that QDA, E-nose, and E-tongue could differentiate lamb shashliks with different roasting methods. A total of 43 and 79 volatile organic compounds (VOCs) were identified by HS-GC-IMS and HS-SPME-GC-MS, respectively. Unsaturated aldehydes, ketones, and esters were more prevalent in samples treated with the K and L method. As a comparison to the RF, SVM, 5-layer DNN and XGBoost models, the CNN-SVM model performed best in predicting the VOC content of lamb shashliks (accuracy rate all over 0.95) and identifying various roasting methods (accuracy rate all over 0.92).

The Application of Ultraviolet Treatment to Prolong the Shelf Life of Chilled Beef

This study simulated the storage conditions of chilled beef at retail or at home, and the sterilization and preservation effects of short-time ultraviolet irradiation were studied. The conditions of different irradiation distances (6 cm, 9 cm, and 12 cm) and irradiation times (6 s, 10 s, and 14 s) of ultraviolet (UV) sterilization in chilled beef were optimized, so as to maximally reduce the initial bacterial count, but not affect the quality of the chilled beef. Then, the preservation effect on the chilled beef after the optimized UV sterilization treatment during 0 ± 0.2 °C storage was investigated. The results showed that UV irradiation with parameters of 6 cm and 14 s formed the optimal UV sterilization conditions for the chilled beef, maximally reducing the number of microorganisms by 0.8 log CFU/g without affecting lipid oxidation or color change. The 6 cm and 14 s UV sterilization treatment of the chilled beef was able to reduce the initial microbial count, control the bacterial growth, and delay the increase in the TVB-N values during storage. Compared with the control group, the total bacterial count decreased by 0.56-1.51 log CFU/g and the TVB-N value decreased by 0.20-5.02 mg N/100 g in the UV-treated group. It was found that the TBARS value of the UV treatment group increased during late storage; on days 9-15 of storage, the TBARS values of the treatment group were 0.063-0.12 mg MDA/kg higher than those of the control group. However, UV treatment had no adverse impact on the pH, color, or sensory quality of chilled beef. These results prove that UV treatment can effectively reduce the microbial count on the surface of beef and improve its microbial safety, thus maintaining the quality of beef and prolonging its shelf life. This study could provide a theoretical basis for the preservation technology of chilled beef in small-space storage equipment.