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Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products

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  • With the continuous development of spectroscopy technology, surface enhanced Raman spectroscopy (SERS) has been widely used as a fast and sensitive analysis method for the qualitative and quantitative analysis of trace analytes in foods. At present, SERS has been widely used in various fields such as food safety, materials, and biomedicine. However, the advances of SERS in meat safety and quality detection have not been summarized. In this review, the development history and detection principles of SERS are introduced and the advantages and potential of SERS application in the field of meat safety and quality detection evaluated. Then, two classical SERS detection modes were compared, namely labeled detection and label-free detection, in terms of the advantages, disadvantages, and application scopes. Furthermore, the specific applications of SERS in detecting bacteria, viruses, veterinary drug residues, food additives, illegal additives, and biotoxins in meat and meat products were presented. In addition, the development of SERS in meat adulteration and freshness identification are summarized. The prospects of the future development of SERS in meat safety and quality assessment will likely involve multiple method integrations, new material development, and artificial intelligence. It is expected that this review will not only provide a comprehensive summary and exploration of SERS in meat safety and quality assessment but also shed light on the future innovation and continued development of SERS in the food and meat industry.
  • According to the seventh census, China ranks first in the world with a population of over 1.4 billion. Due to the large population and the increase in the number of large commercial complex buildings in China, safety hazards have increased significantly. More serious accidents due to untimely evacuation also abound. According to incomplete statistics, there have been many casualties caused in crowd evacuation in China. Some of the causes of accidents and casualties are shown in Table 1.

    Table 1.  Summary of crowd evacuation casualty accidents in China.
    TimeLocationCause of accidentNumber of casualties
    February 5, 2004Miyun County, BeijingA light show was held, a large trampling accident occurred due to crowding and trampling on the Rainbow Bridge and negligence of security personnel[1].37 people died and 37 people were injured
    December 31, 2014The Bund of ShanghaiA light show was held and someone overbalanced and there were too many people in the venue, resulting in multiple falls and subsequent crowding and trampling accidents[2].36 people died and 49 people were injured
    November 18, 2017Beijing Daxing Xhongmen TownA householder refitted a building without authorization, the personnel after the fire did not get timely evacuation, causing a fire accident[3].19 people died and 8 people were injured
    February 25, 2017Honggu Tan New District, Nanchang City, JiangxiA hotel was privately closed for renovation without the approval of relevant authorities, resulting in blocked evacuation routes. People failed to evacuate in time after a fire broke out[4].10 people died and 13 people were injured
    April 2, 2017Daguan Economic Development Zone,
    Anqing City
    A dust explosion occurred in a workshop. Due to non-compliance with the layout of the workshop and a certain exit was blocked by flammable materials, personnel did not escape in time[5].5 people died and 3
    people were injured
    May 16, 2019Changning District,
    Shanghai
    A plant collapse occurred. Due to the chaotic management of the plant site, serious casualties were ocurred[6].12 dead and 10 seriously injured
    March 7, 2020Quanzhou, Fujian ProvinceA major collapse occurred at a hotel where people were not evacuated in time due to the building's poor design[7].29 people died and 42 people were injured
     | Show Table
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    According to the survey, the study of bibliometrics around the world started in 1917. However, the first use of bibliometrics for literature research in China started in 1964[8]. Literature analysis using bibliometric methods can easily identify not only the hot spots and frontiers of research in the field of safety evacuation, but also the 'leaders' among scholars in the field[9]. At present, scholars in many fields use bibliometrics to evaluate the current status of research and the future development trends in their subject areas. Li & Zhao[10] carried out a study on environmental assessment. Sun & Grimes[11] explored the dynamic structure of Chinese emerging innovation research. In addition, literature reviews have been conducted using bibliometric methods in fields such as business economics[1214], chemistry[1517], computer science[1820], and medical sciences[2123]. However, in the field of safety evacuation, most scholars have favored traditional statistical methods of literature review to analyze the research frontiers in the field. For example, He et al.[24] reviewed the research progress of crowd psychological behavior mechanisms and crowd evacuation animation in the process of safety evacuation. Li et al.[25] reviewed the role and advantages of the cellular automata model in the study of personnel evacuation. Zhou et al.[26] reviewed the research on guidance methods and guidance techniques for crowd evacuation in emergency situations. Ding et al.[27] reviewed the recent literature on vertical evacuation of high-rise buildings. Zhu et al.[28] reviewed the research literature on the movement characteristics of pedestrians on stairs. Few scholars have used bibliometric methods to analyze and review the current state of research in the field of safety evacuation in China. Therefore, this paper adopts a combination of bibliometric and traditional literature review methods to search and count the research literature related to safety evacuation in the Web of Science core database for the 30 years from 1990 to 2021, and analyze the current research status and future development trend of this field. The results of the study can provide a reference for researchers and policy makers in the public safety field.

    The structure of this paper is as follows: the second part of the paper describes the data sources and research methods; the third part describes the results of the literature analysis, including the year of publication and number of articles, subject distribution, author distribution, journal distribution, citation analysis, and keyword co-occurrence analysis; the fourth part describes the research hotspots of safety evacuation in China; and the fifth part provides the research conclusions of this paper.

    The Web of Science database is the world's largest online database of academic journals[29]. To ensure the accuracy and credibility of the data, the literature used in this study was obtained from the Web of Science core database. The Web of Science core database of safety evacuation was searched on December 25, 2021. The search results of the Web of Science database differed slightly from date to date because the database is continuously updated[30]. Therefore, the data on the day of the search were taken as the research sample for this study. Using 'topic' as the search term, we entered 'evacuation' in the search box and searched the database for all literature containing this term in the title, abstract, or keyword list between 1990 and 2021. A total of 23,731 documents were searched. The screening of these articles is divided into three steps. First of all, this paper intends to study the research in the field of safety evacuation in China, so by selecting 'PEOPLES R CHINA', 'CHINA', 'TAIWAN' and 'HONG KONG' in the Countries/Regions column, the relevant literature on safety evacuation research in China was refined, and the remaining 3006 papers were screened out. Then filter out articles in irrelevant fields, such as 'medicine', 'geology', and 'economics' were excluded. Finally, after carefully screening and checking, a total of 1380 documents met the search requirements of this study. It should however be emphasized that the selection of articles related to 'safety evacuation' was carried out manually by the authors. Therefore, there may be a little oversight in the number of articles. The search records included title, author, abstract, keywords, year, journal, etc.

    The types and numbers of documents retrieved are shown in Table 2. Most of the documents were Articles (1,352 articles, 97.97%), and both Meeting and Review Articles types were less than 20 documents. The total sum of the listed types of literature was 1,419, and the sum of the types of literature exceeded the number of retrieved literatures, so there were cases where the same literature belonged to multiple types.

    Table 2.  Literature category and quantity.
    No.Document typeNumber of
    literature/article
    Proportion (%)
    1Articles1,35297.97
    2Early Access201.45
    3Meeting191.38
    4Review Articles161.16
    5Others120.87
     | Show Table
    DownLoad: CSV

    Bibliometrics is the study of the literature system and bibliometric characteristics. It uses mathematical, statistical and other econometric research methods to quantitatively measure the status of research and the contributions made in a field[31,32]. Therefore, this paper intends to use bibliometric methods to study the current status of research and development trends of safety evacuation from quantitative and qualitative perspectives.

    At present, the commonly used bibliometric analysis software mainly include VOSviewer and CiteSpace. VOSviewer has more advantages in large amounts of data analysis, displaying correlation strength and presenting the relationship between subject terms[33], while CiteSpace is more suitable for document analysis with small amounts of data, in this study we therefore chose VOSviewer for document analysis. VOSviewer software was used to analyze the authors, institutions, sources, and keywords of literature related to safety evacuation in China. VOSviewer software can be used to construct and view bibliometric maps, and providing the basic functions needed to visualize bibliometric networks in a relatively simple way[34]. The size of the circles in the VOSviewer network diagram indicates the level of importance. The larger the circle, the greater the importance. And the lines between the circles indicate the relatedness between research items. The closer the lines, the higher the degree of relatedness[35]. The VOSviewer software was used to visualize and analyze the literature, so as to identify the research hotspots, development trends and general characteristics of related literature in this field.

    According to the search method introduced above, the research progress of the field in different time periods can be clearly viewed. The annual publication volume in the field of safety evacuation in China between 1990 and 2021 is shown in Fig. 1. As can be seen from Fig. 1, the overall trend of annual publications is on the rise, although the number of publications has decreased in some years. Before 2008, there were fewer related studies, and (with the exception of 2006), the number of publications in the remainder of the years did not exceed 10. 2017−2021 was the fastest growing five years in the field of safety evacuation in China, with the number of publications above 100 each year, indicating that the research enthusiasm in this field is increasing. The largest number of publications appears in 2020, with 231 publications, accounting for 16.74% of the total number of publications. It was followed by 2019, with 208 publications, accounting for 15.07% of the total number of publications. And 199 publications in 2021 rank in third place, accounting for 14.42% of the total number of publications.

    Figure 1.  Annual publications in the field of domestic safety evacuation during 1990−2021.

    According to the statistics of the number of publications, research related to safety evacuation in China until 2021 is divided into three phases. The first stage was from 1990 to 2007, which was named as the 'initiation stage'. The number of literature in this stage did not exceed 10 articles per year. Although the number of articles in this period was small, three of the top 10 cited papers were published in this period, and all of them were published in 2006 (see Table 3). According to the number of citations, the typical papers in this period include the following: Song et al.[36] established a 'multi-grid model' based on the social force model to study the interaction between two factors affecting evacuation; Lo et al.[37] explored the method of finding escape exits during emergency evacuation; Song et al.[38] explored the reasons for the complex behavior of people during evacuation; Yang et al.[39] developed a cellular automata model to simulate the effect of kinship behavior on evacuation efficiency during evacuation; Lo et al.[40] proposed a spatial grid evacuation model (SGEM) to simulate the pedestrian evacuation process.

    Table 3.  The top 10 cited literature of Chinese scholars in safety evacuation from 1990 to 2021.
    RankTitle of articleFirst authorSourceCitation
    rates
    Published
    year
    Address
    1Modeling crowd evacuation of a
    building based on seven methodological approaches
    Zheng XiaopingBuilding And Environment3492009Beijing Univ Chem Technol
    2Simulation of evacuation processes
    using a multi–grid model for
    pedestrian dynamics
    Song WeiguoPhysica A Statistical Mechanics And Its Applications2082006Univ Sci & Technol China
    3Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exitsHuang HaijunPhysical Review E1982008Beijing Univ Aeronaut & Astronaut
    4Agent–based modelling and simulation
    of urban evacuation: relative
    effectiveness of simultaneous and
    staged evacuation strategies
    Chen XuweiJournal of The Operational Research Society1832008SW Texas State Univ
    5Route choice in pedestrian evacuation under conditions of good and zero visibility: Experimental and simulation resultsGuo RenyongTransportation Research Part B–Methodological1782012Inner Mongolia Univ
    6A game theory based exit selection
    model for evacuation
    Lo SiumingFire Safety Journal1642006City Univ Hong Kong
    7Agent–based evacuation model of large public buildings under fire conditionsShi JianyongAutomation in Construction1622009Shanghai Jiao Tong Univ
    8Evacuation behaviors at exit in CA
    model with force essentials: A
    comparison with social force model
    Song WeiguoPhysica A Statistical Mechanics And Its Applications1512006Univ Sci & Technol China
    9A social force evacuation model with
    the leadership effect
    Hou LeiPhysica A Statistical Mechanics And Its Applications1452014Shanghai Univ Sci
    10A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategiesXie ChiTransportation Research Part B–Logistics And Transportation Review1372010Univ Texas Austin
     | Show Table
    DownLoad: CSV

    The second phase was from 2008 to 2016, which is named as the 'initial development phase', and the number of literature in this phase is 20-100 per year. This period has the highest number of highly cited literature publications (see Table 3). Based on the number of citations, some typical papers in this period include the following: Zheng et al.[41] analyzed the advantages and disadvantages of seven crowd evacuation models including the cellular automata model; Huang & Guo[42] designed a modified floor field model to simulate pedestrian evacuation in rooms with internal obstacles and multiple exits; Guo et al.[43] studied the pedestrian evacuation path selection problem under good and zero visibility conditions; Shi et al.[44] proposed a system simulation model to simulate the evacuation process of people in a fire situation; Hou et al.[45] investigated the effect of the number and location of leaders on the evacuation efficiency.

    The third phase is from 2017 to 2021, which is named as 'high speed development phase', and the number of papers in this phase is more than 100 per year. In this period, a large number of scholars in China have joined the research field of safety evacuation, so the number of literature exceeds 200 in 2019 and 2020. Among the literature with high numbers of citations, the more typical ones include: Liu et al.[46] proposes a novel emergency evacuation path planning method combining the Extended Social Force Model (ESFM) and the Improved Artificial Bee Colony (IABC) algorithm, this paper has been cited 143 times. Liu et al.[47] established a crowd evacuation simulation approach that is based on navigation knowledge and two-layer control mechanism; Lu et al.[48] studied the influence of group for on personnel evacuation; Zhao et al.[49] study the impact of different obstacle shapes and distance from exit locations on evacuation efficiency; Chen et al.[50] study the collision avoidance behavior of pedestrians in two-exit classrooms during evacuation through a cellular automata model; Liu et al.[51] proposes a video data-driven social force model for simulating crowd evacuation.

    The discipline distribution of the research literature is to understand the distribution of different disciplines in the field of safety evacuation research and to explore the leading disciplines in this field. By looking at the 'Analyze Results' of the Web of Science core database, we can see that there are 56 categories of disciplines involved in this field, among which 15 categories contain only one article and six categories contain only two articles.

    In this study, the number of relevant articles in each discipline were counted, and the hot disciplines in the field were investigated according to the ranking of the literature volume. The top 10 discipline categories in terms of literature volume and the number of publications are shown in Table 4. The sum of the volume of each discipline category in the table exceeds the sum of the retrieved literature, indicating that the disciplines are not independent of each other, and a piece of literature may be involved in more than one discipline. From Table 4, we can see that the top 10 disciplines in terms of volume are Engineering, Physics, Computer Science, Transportation, Operations Research Management Science, Mathematics, Construction Building Technology, Science Technology Other Topics, Environmental Sciences Ecology, and Materials Science. The leading discipline in this field is Engineering, with 542 articles, accounting for 39.275% of the total number of articles. This is followed by Physics (349 articles, 25.290%). The third is Computer Science (303 articles, 21.957%). Literature review shows that evacuation studies are mostly concentrated in buildings, such as super high-rise buildings, underground multi-story buildings, etc. Moreover, the research on the dynamics of crowd evacuation behavior is usually biased toward physical modeling, so Engineering and Physics disciplines are the two disciplines with the largest number of articles. Computer Science is also on the list, indicating that computer technology is increasingly being used in the study of safety evacuation, and intelligent evacuation tools are being explored and gradually applied.

    Table 4.  Statistics on the distribution of the top 10 disciplines in the literature related to the field of safety evacuation in China during the period 1990−2021.
    RankSubject categoryNumber of
    publications
    Percentage of total
    publications (%)
    1Engineering54239.275
    2Physics34925.290
    3Computer Science30321.957
    4Transportation14310.362
    5Operations Research Management Science1128.116
    6Mathematics1037.464
    7Construction Building Technology977.029
    8Science Techology Other Topics836.014
    9Environmental Sciences Ecology805.797
    10Materials Science735.290
     | Show Table
    DownLoad: CSV

    Finding the distribution of authors of the literature helps to understand the important contributions of the authors in the field. The retrieved literature was written by more than 200 different authors, and the top 10 authors of the published literature were counted, and the statistical results are shown in Fig. 2. The authors of the literature were clustered and analyzed by VOSviewer to obtain a collaborative network view of the authors related to safety evacuation, as shown in Fig. 3, where the colors in the figure represent collaborative clusters (groups), which can identify the highly productive authors in the field, as well as the collaborative relationships among the authors. It is worth noting that the literature search results in the Web of Science database cannot distinguish between authors with the same name, so the author searched the literature manually in order to filter the authors with the same name and the same institution as the same author.

    Figure 2.  Statistics of the top 10 authors in the number of publications in the field of safety evacuation Web of Science from 1990 to 2021.
    Figure 3.  Network diagram of researchers in the field of safe evacuation from 1990 to 2021.

    The author with the highest number of publications is Song Weiguo (Univ Sci & Technol China, 22%), who has published work in 27 journals. The next highest author is Lo Siuming (City Univ Hong Kong, 14%), and it is noteworthy that the two scholars have co-authored more than 10 publications. In addition, many of the papers are co-authored by multiple authors. For example, Song Weiguo & Zhang Jun co-authored in 2021: Where luggage-related facilities should be placed along passageways in traffic hubs: right, left, or in the middle?[52]; Yang Lizhong & Fu Zhijian co-authored in 2018: Update schemes of multi-velocity floor field cellular automatization for pedestrian dynamics[31]; Ma Jian & Lo Siuming co-authored: Pedestrian ascent and descent fundamental diagram in 2017[53]. Figure 3 also shows that the main research scholar in this field is Song Weiguo. According to the color division of the network diagram, the authors can be roughly divided into 11 groups, indicating that scholars studying safety evacuation in China are closely connected with each other, and mostly choose to conduct research through teamwork.

    In addition, most of the scholars in the field of safety evacuation conduct their research within universities, and therefore most of the institutions to which the published related articles belong are universities. Further analysis of the research institutions of the safety evacuation-related literature in China using VOSviewer software helps to understand the leading institutions in the field. Statistics on the number of articles issued by each institution are shown in Table 5 (taking the top 10). There are three institutions with more than 100 articles, namely University of Science and Technology of China (149 articles), Beijing Jiaotong University (109 articles), and Tsinghua University (107 articles). So these three institutions are leading the way in this field.

    Table 5.  Statistics on the number of articles issued by each institution.
    RankLiterature research institutionNumber of publications
    1University of Science and Technology of China149
    2Beijing Jiaotong University109
    3Tsinghua University107
    4City University of Hong Kong78
    5Southwest Jiaotong University67
    6Wuhan University of Technology50
    7Tongji University48
    8Chinese Academy of Sciences41
    9Southeast University38
    10Beihang University38
     | Show Table
    DownLoad: CSV

    The search yielded 1,380 papers from about 270 journals, of which 130 journals published only one paper in the field of safety evacuation and 39 journals published two related papers. The core journals in this field can be derived through law of Bradford, and the formula for calculating the number of Bradford core journals was proposed by the Belgian scholar L. Egghe[51] , that is, r0 = 2ln(eE × Y), where E is a constant value of 0.5772, and Y denotes the number of papers in the journals with the largest amount of literature, which is 172 in this paper, and is brought in to obtain the number of core journals of about 11 papers. VOSviewer software was used to draw the journal co-occurrence network diagram, as shown in Fig. 4. The information of core journals is shown in Table 6. The analysis shows that the journal Physica A- Statistical Mechanics And Its Applications has the highest number of publications with 172 articles, accounting for 12.5% of the total literature, and is the most prolific journal in this field. The next most prolific journal is Safety Science (80 articles, 5.8%). Third in the list is the IEEE Access journal (42 articles, 3.0%). The complex of connecting lines between the circles in the Fig. 4 indicates that the journals are closely linked and are citing each other.

    Figure 4.  Network diagram of relevant journals in the field of safety evacuation.
    Table 6.  Information of core journals in the field of safety evacuation.
    RankJournal nameNumber of articlesPercentage
    of total
    publications (%)
    Impact factor*
    1Physica A Statistical Mechanics and Its Applications17212.464%3.295
    2Safety Science805.797%5.16
    3IEEE Access423.043%4.983
    4Mathematical Problems in Engineering372.681%1.125
    5International Journal of Modern Physics C362.609%1.453
    6Simulation Modelling Practice and Theory312.246%3.336
    7Sustainability302.174%2.966
    8Chinese Physics B292.101%1.265
    9Journal of Statistical Mechanics Theory and Experiment282.029%1.425
    10Fire Safety Journal271.957%2.802
    11IEEE Transactions on Intelligent Transportation Systems241.739%8.632
    * Impact factor taken from 2021
     | Show Table
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    The number of citations reflects the recognition and influence of the literature in its field, as well as the current research hotspots and trends in the field. Among the 1,380 documents retrieved, 22 documents were cited more than 100 times and two documents were cited more than 200 times. Table 3 summarizes the top 10 cited literature in the field of safety evacuation during the period 1990–2021. From Table 3, it can be seen that most of the top 10 cited articles are from before 2010. And combined with the analysis of the number of publications above, it can be seen that the number of citations is higher before 2010 although the number of publications is lower. The most cited literature is the review paper by Zheng et al. Modeling crowd evacuation of a building based on seven methodological approaches published in Building And Environment in 2009[41]. The article describes seven approaches to studying crowd evacuation in buildings and discusses the advantages and disadvantages of each. Later scholars cited this literature to explore: a modified approach to pedestrian dynamics that allows for crowd dynamics guidance[54]; a novel social force model describing pedestrian movement on stairs and evacuation dynamics[55]; the effect of building environment and evacuation behavior on evacuation time[56].

    The second most cited is: Simulation of evacuation processes using a multi–grid model for pedestrian dynamics published in 2006 in the journal Physica A - Statistical Mechanics And Its Applications, written by Song et al.[36]. This article analyzed the rules of interactions among pedestrians or pedestrians and constructions and the influences of interaction forces and drift on evacuation time. Later scholars carried out research on the relationship between microscopic features of pedestrian dynamics based on this paper[57], and novel meta-automata models considering heterogeneous behavior of pedestrians[58].

    The third is Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits[42], published in Journal of Physical Review E. In this article, a modified floor field model is proposed to simulate pedestrian evacuation in rooms with internal obstacles and multiple exits, and employing a logit-based discrete choice principle to govern the exit selection. Later scholars cited this literature to study: pedestrian path selection behavior during evacuation in indoor areas with obstacles[59]; pedestrian evacuation dynamics affected by fire spread[60].

    It is worth noting that among the top 10 cited papers, two papers are from Song and three papers are from the journal Physica A Statistical Mechanics And Its Applications.

    In addition, co-citation analysis of the relevant literature is considered in this paper. Based on the Minimum number of citations of a cited reference = 50, 50 literature records satisfying the threshold value are selected from 24,818 references to generate a visual network mapping of the co-citation analysis of the literature (as shown in Fig. 5). In the co-citation analysis network of the literature, the size of the nodes reflects the total frequency of citations of a particular literature, i.e., the higher the number of citations, the larger the nodes[61]. From Fig. 5, the top two cited articles are all from the authors Helbing et al[62], who wrote Simulating dynamical features of escape panic in 2000 and Social force model for papers in 1995. The third is the paper Simulation of pedestrian dynamics using a two-dimensional cellular automation by Burstedde et al.[63].

    Figure 5.  The network diagram of the co-citation analysis of the relevant literature.

    Keywords are conceptual words extracted by authors from the text to describe their research in a concise way. The analysis of keywords can help with understanding the research hotspots and future development trends in related fields, which is the core content of this study, and it is also one of the important ways to effectively search literature. The keyword analysis method in Callon et al. From translations to problematic networks: An introduction to co-word analysis[64] has been widely cited. In this paper, VOSviewer software was used to conduct keyword analysis on 1,380 retrieved articles and draw the network diagram of literature keyword co-occurrence, as shown in Fig. 6. In the total of 4,261 keywords, those with more than 20 occurrences were recorded, and a total of 70 keywords met the requirements. The connecting lines between the circles in Fig. 6 indicate the relevance of the keywords, indicating that the keywords are closely connected with each other. The keywords in Fig. 6 are roughly divided into four groups by color, and the keywords in the same group usually have closer relationships[65]. Words such as simulation, behavior, cellular automata are a cluster, such as shown by Dang et al.[66] who explored a virtual reality large-scale crowd evacuation chain navigation grid based on meta-cellular automata. Model, time, emergency evacuation are a cluster, e.g., Wang et al.[67] explored a subway station emergency evacuation model considering personality traits. Flow, social force mode, pedestrians are a cluster, such as Wang & Cao[68] studied a simulation model of pedestrian evacuation strategy under limited visibility. Movement, crowd, speed are a cluster, e.g., Huang et al.[69] studied an experiment on the evacuation behavior of passengers in high-rise deck buses.

    Figure 6.  Literature keyword co-occurrence network from 1990 to 2021.

    The keywords with high frequency are simulation, evacuation, model, behavior, dynamics, flow, social force model, pedestrian evacuation, emergency evacuation, and pedestrian dynamics. This indicates that the current research in the field of safety evacuation in China is mainly focused on these hot spots. The term 'simulation' appears most frequently, which indicates that model simulation is more widely studied in the field of safety evacuation in China. In addition, the study of pedestrian dynamics is also more common.

    The keywords in different years also have obvious differences. According to the analysis of the year of publication and the number of articles above, keyword co-occurrence analysis was conducted in three phases using VOSviewer software, and the keyword co-occurrence network diagram is shown in Fig. 7. From Fig. 7, the hot keywords in the first stage (1990–2007) are jamming transition, cellular automata; simulation, computer, and evacuation model. The hot keywords in the second stage (2008–2016) are behavior, dynamics, flow, model, and cellular automata. And the hot keywords in the third phase (2017–2021) are simulation, flow, exit choice, route choice, and fire. The hot keywords in the different stages are shown in Table 7.

    Figure 7.  Co-occurrence network of literature keywords at each stage: (a) the first stage; (b) the second stage; (c) the third stage.
    Table 7.  Hot keywords in different stages.
    No.1990–20072008–20162017–20211990–2021
    1simulationsimulationsimulationsimulation
    2firemodelbehaviorevacuation
    3modelbehaviormodelmodel
    4computerdynamicsevacuationbehavior
    5jamming transitionflowdynamicsdynamics
    6pedestrian dynamicsevacuationflowflow
    7cellular automatacellular-automata modesocial force modelsocial force model
    8pedestrian flowsocial force modelpedestrian evacuationpedestrian evacuation
    9evacuationpedestrian dynamicsoptimizationemergency evacuation
    10occupant evacuationjamming transitionemergency evacuationpedestrian dynamics
     | Show Table
    DownLoad: CSV

    When comparing the hot keywords in the three stages, it is found that the hot keywords in each stage have not changed much. The simulation study has been the hot method of safety evacuation research in China, steadily appearing in the first place. Compared with the first stage, the study of pedestrian behavior in the second and third stages gradually becomes a hot spot. In Fig. 7, it can be seen that in addition to the hot keywords, the research on the selection of paths and exits has also increased significantly in the third stage, where the research combined with optimization, i.e., the optimal evacuation path selection under fire situations, is also increasing. It can be seen that with the development of economy and technology in China, the number of high-rise buildings and large integrated commercial buildings is gradually increasing, and the resulting safety accidents are also increasing, so people's attention to the safe evacuation after fire is also increasing, and the research hotspots are gradually shifting to the selection of optimal escape paths.

    In the next few years, with the increase of large underground commercial complexes in China, the research of safety evacuation may shift from above-ground buildings to underground buildings. The evacuation of people in underground shopping malls may become a new hot issue. In addition, studies on the safe evacuation of people often requires the organization of large crowds for experiments, whereas the experimental costs are large and there are more uncertainties during experiments. Therefore, in the field of evacuation research, the most used method is computer simulation. With the rapid development of intelligent technology in China in recent years, intelligent evacuation tools are also being gradually explored and applied. In summary, the trends in the field of evacuation of people are mainly focused on the 'modification of evacuation models' and the 'evacuation behavior of pedestrians'. Among them, the combination with 'fire', 'optimization' and 'emergency management' is also becoming a research trend.

    According to the keyword analysis, it can be seen that the keywords 'simulation' and 'model' appear more frequently, so the research of crowd evacuation through model simulation has been the research hotspot in the field of safety evacuation in China. In the second and third stages, the keyword 'behavior' appears more frequently, so the study of pedestrian behavior gradually becomes a hot spot. In view of this research hotspot, the following analysis will focus on the research on crowd behavior of large-scale group evacuation. In the third stage, there is a significant increase in the research on crowd path and exit selection behavior, in which the research combined with 'optimization', i.e., the optimal evacuation path selection of crowds under fire situations, is also significantly increased. In response to this research hotspot, the following part will summarize the research on path planning during crowd evacuation and the optimization of exit bottlenecks. In summary, the following research hotspots will be specifically reviewed related to three aspects: first, research on large-scale mass crowd evacuation; second, research on path planning during crowd evacuation; and third, research on optimal design of evacuation exits.

    The behavior of crowds in emergency situations is complex and stochastic, so scholars have paid particular attention to the uncertainty in the evacuation process of pedestrians. The specific description of the research methods and the findings of the study can be found in Table 8. In the study of large-scale group evacuation behavior, Wang et al. proposed a method to qualitatively simulate panic propagation in mass crowd evacuation, and established a simulation model of panic behavior based on system dynamics[70], to study the uncertainties affecting mass evacuation from the perspectives of efficiency and risk[71]. Cui et al.[72] analyzed the behavioral characteristics of large event audience groups and proposed a large-scale group evacuation method for large events. Zhan et al.[73] studied the path selection model for large-scale typhoon-resistant crowd evacuation in an uncertain environment under typhoon disaster. Ma et al.[74] proposed a large crowd evacuation method based on RFID (radio frequency identification) mutation theory for large crowds in cultural museums. Mei et al.[75] proposed a simulation method using the entangled emotional model (EEM) to deal with the gathering phenomenon and group collision problem during large-scale crowd evacuation.

    Table 8.  Specific analysis of the cited literature on mass crowd evacuation.
    Author, yearPanicModelAlgorithmMeasured variablesMain research contents
    Wang, 2012The numbers evacuated; correct rate of evacuation direction; speed; human trafficThe model reproduces a well-known phenomenon in crowd evacuation, namely fast is slow, and confirms that the severity of disaster exponentially positively correlates with the panic spread, and the effectiveness of rescue guidance is influenced by the leading emotion in the crowds as a whole.
    Wang, 2013DensityThe effectiveness of rescue strategies was found to be strongly related to crowd density. The higher the crowd density, the larger the minimum number of passageways for effective evacuation will be.
    Cui, 2016This paper proposes an audience behavior rehearsal and simulation system that can be applied to the real activity. The system can realize the behavior planning of the audience in the early period of large-scale organization and modularize the organization flow.
    Zhan, 2019TimeA route selection model for anti-typhoon crowd evacuation vehicles was built. The vehicle road impedance coefficient was used to embody the abilities of different vehicles in executing evacuation tasks. And the proposed method can provide emergency decision makers with a scientific and reasonable route selection scheme for anti-typhoon crowd evacuation vehicles.
    Ma, 2020Density; speedThis paper proposes a large-scale crowd evacuation method based on the mutation theory of RFID. The advantage of this algorithm is that it can overcome the contradiction between the prediction accuracy and the tracking speed, and the accuracy of the algorithm to predict the flow of large-scale people is improved, making the evacuation model more relevant to the actual situation.
    Mei, 2020Time; density; human trafficThis paper proposes a particle model, and the simulation method of the entangled emotional model (EEM) is used to deal with the gathering phenomenon and group collisions in the evacuation process. The model simulates the crowd’s kinship by forming multiple entangled pairs, which can form multiple motion clusters for a large number of people.
     | Show Table
    DownLoad: CSV

    In a word, research on mass crowd evacuation is becoming more and more concerned with the quantification of crowd psychological and behavioral characteristics under the influence of emergency complexity scenes. It is the choice of many scholars to add the study of panic psychology to the study of mass evacuation. They determine the law or phenomenon of large-scale evacuation, such as 'fast is slow', by studying variables such as human flow, evacuation time, speed, and density. At the same time, by means of computer simulation and algorithms, these studies can reproduce large-scale crowd evacuation processes and provide data reference for the evacuation decision from the angle of efficiency and risk. Some typical large-scale evacuation models are shown in Fig. 8.

    Figure 8.  Schematic diagram of a large-scale evacuation model. Reprinted from Ma et al. & Yang et al.[71,72].

    When an emergency occurs in a complex building, it is difficult for people to choose a suitable evacuation route according to the dynamic changes of evacuation situation due to panic and unfamiliarity with the environment. Scientific and reasonable planning of pedestrian evacuation paths can effectively improve evacuation efficiency, so the research on pedestrian evacuation path planning has increased significantly in recent years. A full list of the analyses identified in this work can be found in Table 9. Yang et al.[76] used an ant colony optimization algorithm to navigate pedestrian evacuation paths with complete information, and concluded that pedestrians with complete information are able to choose shorter evacuation paths. Lu et al.[77] investigated the path selection behavior of pedestrians going up and down stairs in the absence of visibility. Song et al.[78] proposed an evacuation path selection algorithm considering hazard and time factors. Xu et al.[79] proposed an improved Dijkstra algorithm to study the dynamic multi-objective path planning problem. Liu et al.[80] proposed an improved artificial bee colony algorithm (IACS) to solve the evacuation path planning problem on cruise ships. Liu et al.[81] proposed a potential-based three-dimensional cellular automata model to describe the route choice behavior of pedestrians while evacuating terraced stands. Zhang et al.[82] built a two-story airport terminal based on a social force model to describe the path selection behavior of passengers. Wang et al.[83] proposes a BIM-based method for real-time dynamic escape path prediction analysis of people for crowd escape path planning. Zhao et al.[84] proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM for simulating the movement of pedestrians, to providing pedestrians with timely route selection. Niu et al.[85] proposed a real-time evacuation strategy based on a comprehensive route constraint according to the Intelligent Decision P System (IDPS). Ping et al.[86] studied the problem of evacuation path selection for the crew of offshore platforms.

    Table 9.  Specific analysis of the cited literature in evacuation path planning.
    Author, YearExperimentModelAlgorithmVisibilityObstaclesMain research content
    Yang, 2021This paper proposes an obstacle avoidance method in the microscopic SFM, which emphasizes the solution of choosing which obstacle to detour and which side to detour in the multiple obstacle scene. Herding behavior, individual preference affected by obstacles and walls are taken into consideration when defining the desired direction of pedestrians with local information in this algorithm.
    Lu, 2021This paper carries out a series of pedestrian evacuation experiments on a staircase for both ascent and descent based on video tracking technology to extract the trajectories of pedestrians. Pedestrians tend to use the enclosure for help when ascending and descending without visibility, and offset angle is correlated with pedestrians’ route-choice behavior. These studies are helpful to understand pedestrian evacuation characteristics on stairs without visibility.
    Song, 2021By combining GIS and a fire hazard assessment method for indoor spaces, a new evacuation route selection approach that considers hazards and time is proposed in this paper.
    Xu, 2021This paper constructs a multi-indicator emergency risk assessment method that considers the evacuation speed of different population types and health consequences caused by various risk components. Then he proposes a modification of the well-known Dijkstra algorithm to deal with the problem for emergency route selection under the real effect of disaster extension. The proposed model provides reliable and practical emergency route planning services for various personnel types under different accident scenarios.
    Liu, 2021This study uses an IACS to analyze the multi-path dynamic planning of emergency evacuations on cruise ships. And the ACS is combined with the increasing flow method to improve the evacuation efficiency.
    Liu, 2021A potential-based three-dimensional route choice model for pedestrian evacuation on terraced stands is proposed. The proposed potential field algorithm reflects the influence on route choice behavior of heterogeneous heights, route distance, pedestrian congestion, and route capacity.
    Zhang, 2021A double-level model was established to describe passengers’ path planning behaviors. The avoiding force model including common avoiding force and additional horizontal avoiding force was established, and the route and node choice models were established to describe pass engers’ path planning in long-range space.
    Wang, 2020This paper proposes a real-time dynamic fire escape path prediction analysis method with BIM, and designs single and multi-person escape route planning method. The shortest path is planned by Dijkstra algorithm.
    Zhao, 2020This paper proposes a new crowd evacuation simulation method. The proposed MABCM algorithm can effectively improve the performance of ABC, and the method balances distance and congestion and shortens evacuation time to a certain extent.
    Niu, 2020This work proposes a real-time evacuation strategy. Experiments are conducted to simulate five different scenarios in a fire evacuation. The evacuation strategy with a comprehensive route constraint has a significant improvement in the evacuation efficiency and has higher robustness.
    Ping, 2018To quantify the influence of evacuation route selection on crew evacuation efficiency, two scenarios are considered. It is reasonable to prescribe the evacuation routes in advance.
     | Show Table
    DownLoad: CSV

    Obviously, current research on path selection is often carried out at the fire scene, and the research on visibility and obstacles is mostly related to it. Regarding the research on path planning, most of the documents included in the Web of Science database are the research on path planning models. Scholars use some algorithms to develop models and make corresponding algorithm flow charts or evacuation path planning flow charts, some of the more typical flowcharts are shown in Fig. 9. The model is combined with the algorithm to carry out relevant crowd evacuation simulation research. Therefore, the new model is compared with the existing model, and the advantages and disadvantages of the model are proposed. In this part of the study, Ant colony algorithm and Dijkstra algorithm are commonly used algorithms; cellular automata model and the Social Force Model are the basis for building various innovative models. In addition, the acquisition of pedestrian motion trajectory in the experiment is carried out by video tracking technology. In addition, the research in this aspect is increasingly combined with intelligent algorithms, showing obvious interdisciplinary characteristics.

    Figure 9.  Evacuation algorithm flow chart or evacuation path planning flow chart. Reprinted fromSong et al. & Xu et al. [75,76]

    Evacuation exits are very important in conventional buildings, and there is usually more than one exit in a large building, so how to use them reasonably for effective evacuation in emergency situations is becoming an important topic, and most scholars have studied the evacuation of planar exits in buildings. A full list of the analyses identified in this work can be found in Table 10. Zhang et al.[87] proposed a pedestrian multiple exit selection model based on a continuous model. Ma et al.[88] developed a pedestrian dynamic exit decision model considering people's exit selection strategies based on a social force model. Yue et al.[89] improves the cellular automata model to study the influence of classroom obstacles on personnel evacuation path selection. Zhang & Jia[90] studied a large-scale group evacuation strategy guidance model, which generates leader location and exit selection options. Wang et al.[91] integrated game theory into a cellular automata simulation framework to study the pedestrian evacuation exit selection mechanism. Gao et al.[92] proposed a modified cellular automata model based on Floor Field theory to study the effect of different exit weight coefficients on evacuation efficiency. Yang et al.[93] proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. Liu et al.[94] proposed a cellular automata model based on fuzzy logic approach to study the exit selection problem during pedestrian evacuation. Cao et al.[95] proposed an extended multi-grid model to study the exit selection problem of people in a two-exit room under fire situation. Li et al.[96] developed an exit selection model considering pedestrian evacuation preferences based on a meta-cellular automata model.

    Table 10.  Specific analysis of the cited literature regarding planar exits.
    Author, YearModelAlgorithmLeaderObstaclesObject of studyMain research content
    Zhang, 2021Distance from a pedestrian to an exit; Pedestrian density
    near an exit; Exit width
    This paper proposes a multi-exit evacuation model based on a continuous model. And the model takes into account the distance between pedestrians and exits, the pedestrian density near exits, and the width of exits. The model can reproduce the phenomenon of pedestrian congestion and exit congestion, and improve the evacuation efficiency as well as utilization rate of exits significantly.
    Ma, 2021Exit quantity; Exit positionA dynamic exit decision model (EDM) is proposed to simulate decisions of evacuees in the multi-exit evacuation. The model can accurately evaluate the evacuation efficiency of different multi-exit layouts and optimize the design rules.
    Yue, 2021An exit with a prepositive obstacleIn this paper, a retardation coefficient is introduced to describe the effect of obstacles slowing down pedestrian movement. A special technique is adopted to calculate the shortest estimated distance from cell site to exit considering obstacle layout and retardation coefficient. The repulsion and isolation effect of obstacles on pedestrian flow is manifested by the clusters of evacuation path chains.
    Zhang, 2021Position of leader; Number of leaders;
    Exit selection strategy
    A simulation algorithm is proposed to integrate a pedestrian following model and strategic guidance model based on the follower-leader interaction. The guidance strategy can realize the full use of guidance capacity, information confusion reduction and uniform exit usage, all of which contribute to a reduction in evacuation time.
    Wang, 2020Visual radius; Initial crowd distribution; exit layout;By integrating game theory into a cellular automata simulation framework, the pedestrian exit choice mechanism is explicitly modeled in this paper. The model is used to study the visual radius and choice firmness of a pedestrian, initial crowd distribution of the room, exit layout as well as exit width.
    Gao, 2020Exit quantity; Exit width; Distribution of pedestriansIn this paper, A modified cellular automata model based on Floor Field theory is proposed to solve the problem of congestion in front of exits caused by the asymmetrical layout of exits or pedestrians in a multi-exit building.
    Yang, 2020The limited visibility and guide quantity; Export position; Exit widthThis paper chooses the fuzzy logic theory to investigate the problems of guide selection by informed followers and exit selection by guides. Guide’s normalized distance to the exit and the normalized density around the exit are chosen as the input variables of the fuzzy inference system to assist in deciding which exit to choose for guides.
    Liu, 2020Exit quantity; Exit width; Export position; Obstacle attributesThis paper proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. The combination of the output variable of fuzzy logic, exit width and herding behavior can effectively determine the target exit and solve the position conflict among pedestrians.
    Cao, 2018The effect of utility threshold
    on evacuation, active
    occupant on evacuation
    The exit selection based on random utility theory, as well as the pedestrian movement in fire, is investigated. The effects of different occupant types, the utility threshold, heat release rate of fire, burning materials and pre-movement time on evacuation are discussed.
    Li, 2017Exit widthBased on estimated evacuation time and shortest distance, pedestrian exit choice model is established considering pedestrian preference.
     | Show Table
    DownLoad: CSV

    Combined with computer simulations, study on the rational allocation of multiple exits within a building has been closely linked to the evacuation path planning study in the previous section. In the study of the model, scholars will include the drawn model framework diagram in the text, and some of the typical framework diagrams are shown in Fig. 10. In this part of the study, cellular automata model and social force model remain the most commonly used models. In addition, continuous model and pedestrian cell transport model are also included. Game theory, fuzzy logic theory, and random utility theory are all involved in the study of the models. During the simulation, most scholars choose to use Moore neighborhood to calculate the probability of pedestrians choosing different exits, as shown in Fig. 11. Moreover, this part of the research is more combined with leaders and obstacles. Exit width, quantity, position, etc. are the research hotspots in this section.

    Figure 10.  Model frame diagram. Reprinted from Ma et al. & Yue et al. [85,86].
    Figure 11.  Moore neighborhood. Reprinted from Zhang & Jia, Liu et al. & Cao et al. [87,91,92].

    Crowding of pedestrians at the exits is a common phenomenon during crowd evacuation, and serious congestion may cause serious trampling accidents. Therefore, in recent years, some scholars have started to consider the special exit bottleneck problem, and the research on the structural optimization of the bottleneck exit has improved significantly. A full list of the analyses identified in this work can be found in Table 11. Li et al.[97] studied the influence of geometric structure characteristics of the convex exit on crowd evacuation, and showed that the convex exit structure is more conducive to crowd evacuation in emergency situations. Li et al.[98] studied the effect of exit position and corner exit form on crowd evacuation. Wu et al.[99] investigated the utilization of different exits in subway stations and the optimization of congestion at bottlenecks. Wang et al.[100] studied pedestrian flow at narrow exits and explored the effects of exit location, bottleneck length, and obstacles on evacuation efficiency. Wang et al.[101] studied the effect of adding obstacles of different sizes and locations in front of 30° angle exits on evacuation. Li et al.[102] studied the effect of exit design with internal and external doors and different exit widths on evacuation efficiency. Wang et al.[103] studied the effect of buffer zones before evacuation exits on evacuation efficiency. Song et al.[104] proposed the active rotation torque (ART) model that can simulate both non-competitive and competitive pedestrian behaviors near exit bottlenecks. Wang et al.[105] studied pedestrian flow characteristics at exit bottlenecks considering different door sizes and locations. Shi et al.[106] investigated the effect of different exit configurations on pedestrian flow exit performance under normal and slow pedestrian flow conditions. Tian et al.[107] studied the influence of different exit widths and positions of rooms without obstacles on evacuation efficiency. Wang et al.[108] proposed a new multi-agent based congestion evacuation model incorporating panic behavior, and studied the phenomenon of people gathering in front of exits in panic situations by simulations.

    Table 11.  Specific analysis of the cited literature on non-planar exits.
    Author, YearModelAlgorithmExperimentObject of studyMain research content
    Li, 2022The convex exit structureUsing social force model-based software, MassMotion, this paper studies the influence of geometric structure characteristics of the convex exit on crowd evacuation and put forward the optimal design strategy of this structure, so as to improve the efficiency of evacuation in an emergency.
    Li, 2022The evacuation efficiency of the 30° corner exitIn this paper, Massmotion based on social force model is used to carry out a numerical simulation on exit position and corner exit form to find out the mechanism and influence law of the slight architectural adjustment on the flow at bottleneck. The 30° angle may be a more appropriate corner exit option. In this layout, pedestrian walking direction changes less and the steering angle is smaller.
    Wu, 2022Railings at evacuation exitsTo alleviate the congestion of the evacuation in a largescale and multifunctional subway station, the utilization of different exits and the optimization of congestion at bottlenecks were investigated in this study. When the number of exits in the divided area is large, setting railings can alleviate the congestion at the exit.
    Wang, 2022The exit location; the bottleneck length; an obstacle near an exitThis paper studies pedestrian flow at narrow exits and explored the effects of exit location, bottleneck length, and obstacles on evacuation efficiency. With the increasing of bottleneck length, pedestrian flow efficiency gradually decreases. Placing an obstacle near exits in an emergency may not make the evacuation worse.
    Wang, 2022Corner exit; the size
    and location of the
    obstacle
    This paper studies the effect of adding obstacles of different sizes and locations in front of 30° angle exits on evacuation. The distance from the obstacle to the exit has the greatest influence on evacuation. At the short distance, the length of the obstacle can be increased to shorten the evacuation time.
    Li, 2020Different exit widths
    and operating doors
    Considering the differences in the individual characteristics of pedestrians and the influence factors of buildings, we proposed a safety evacuation model for limited spaces. Evacuation efficiency, bottleneck area density, escape route characteristics, and similar factors were analyzed on the basis of different exit widths and operating doors. When the exit widths are 1.0, 1.1, 1.8 and 1.9 m, the exit crowd and average densities are at their lowest.
    Wang, 2019Exit buffer zoneIn this paper, a tentative experiment was designed to preliminarily reveal the role of buffer zone in crowd evacuation. Then a social force based simulation model was established by Massmotion according to the properties of the experiment. The longer the buffer zone, the faster the agents can escape.
    Song, 2018Non-competitive and competitive pedestrian behaviors near exit bottlenecksActive rotation torque is proposed to model the active rotation behavior of pedestrians turning their torsos in the desired direction. A three-circle model is adopted to represent the shape of pedestrians to study the phenomenon of people actively squeezing to pass through an exit. The torque model can be applied to manifold scenarios with various door widths and different safety separation belt settings. And the model can simulate both non-competitive and competitive pedestrian behaviors near exit bottlenecks more accurately than the circular social force model.
    Wang, 2019Pedestrian flow features at bottlenecks, i.e. room exitsIn this paper, pedestrian flow features at bottlenecks are investigated with human-experiments considering varying door sizes and locations. The time lapses between two successive pedestrians displayed heavy-tailed distribution. In narrow door scenarios, the specific capacity was continuously decreased from the middle exit scenarios to the corner exit scenarios.
    Shi, 2019Different exit locations and obstacles near exitThis study aims to examine the effect of different geometrical layouts at the exit towards the pedestrian flow via controlled laboratory experiments with human participants. Corner exit performed better than middle exit under same obstacle condition. the effectiveness of obstacle is sensitive to its size and distance from the exit.
    Tian, 2015Different widths and positions of the exitsIn this paper, we proposed an improved and simple method to calculate the floor field. In our method, the pedestrians are treated as the movable obstacles which will increase the value of the floor field. The additional value is interpreted as the blocking effect of preceding pedestrians.
    Wang, 2015Pedestrian congestion behavior at the exitA new multi-agent based congestion evacuation model incorporating panic behavior is proposed in this paper. Pedestrians in this model are divided into four classes and each pedestrian’s status can be either normal, being overtaken, or casualty. The agents gather in front of the exits and present arched shapes close to the exits. Under the panic state the agents cohere closely and almost do not change the target exit. If there are obstacles, the congestion can be alleviated.
     | Show Table
    DownLoad: CSV

    In conclusion, the study of special exit bottlenecks is often combined with the study of crowd congestion, where the study of exit location, angle and morphology is the most common, and the study of congestion optimization at exit bottlenecks has also made good progress. The Mass Motion software based on the social force model is often used for evacuation exit studies. In addition, in this part of the research, many scholars choose to carry out crowd evacuation experiments, in order to better observe the phenomenon of exit blockage by combining experiments and simulations. Some of the typical exit evacuation experiments are shown in Fig. 12.

    Figure 12.  The exit evacuation experiments. Reprinted from Wang et al. & Shi et al. [97,98,100,102,103].

    The purpose of this review is to unearth the data from the research literature in the field of crowd evacuation in China, a country with the largest population in the world, and explore the correlation of the research work of crowd evacuation at the current stage and the research hotspots in recent years, so as to provide some reference for the research of crowd evacuation around the world. By searching the Web of Science core database of articles related to the field of safety evacuation in China during 1990−2021, after screening, there were 1,380 papers. Using bibliometric methods, the number of relevant articles, year of publication, author distribution, journal distribution, keywords, etc., were analyzed in detail and VOSviewer software was used to explore the research hotspots in this field. The following conclusions were obtained from this study:

    The 1,380 retrieved documents were divided into three phases in chronological order, indicating a rising trend of the number of publications. There are 56 categories of disciplines involved in the field of safety evacuation in China and the top three disciplines are Engineering, Physics and Computer Science. Song is the scholar who has published the most articles in the field of safety evacuation in China. The literature comes from nearly 200 journals, with the greatest number of articles published in Physica A Statistical Mechanics And Its Applications. Most of the top 10 cited papers are reported before 2010, and the most cited paper is Modeling crowd evacuation of a building based on seven methodological approaches published by Zheng et al.[41].

    The analysis of keywords shows that the current research hotspots in the field of safety evacuation in China mainly focus on simulation, model and behavior. The cellular automata model has been a popular model for safety evacuation research. In the second and third stages, the keyword 'behavior' appears more frequently. In the third stage, the research on crowd path planning and exit selection behavior has increased significantly. According to the keyword analysis, the hot spots of safety evacuation research in China are mass crowd evacuation, evacuation path planning, and optimal design of evacuation exits in recent years.

    Safety evacuation is of great significance to ensure that personnel escape from dangerous situations smoothly during emergencies. With the deepening of the research in this field, it will play a very positive role in the healthy and stable development of society. Although this paper mainly focuses on the research status of one country, it also has certain reference value for related research around the world. In the field of evacuation, many Chinese scholars also refer to the work basis of foreign scholars, and Chinese scholars have extensive exchanges with scholars worldwide. However, there are still some shortcomings in the existing studies, and in future research, the following aspects should be considered:

    (1) At the research scale, most of the research in the field of safety evacuation is focused on the interior of buildings, and the research direction is rather monotonous. The research on crowd evacuation outside buildings can be increased in the future. For example, the study of crowd evacuation under outdoor toxic gas diffusion scenarios, combined with refuge areas.

    (2) Domestic research on crowd evacuation has been carried out for many years, and the creation of models has been very skillful, but there are still many difficult points that have not yet been fully understood. In different accident scenarios, the path selection of evacuation process, pedestrian evacuation behavior decisions, etc. are significantly different, so the future still establishes the need for emergency evacuation models in different disaster environments to form a unified model framework.

    (3) According to the number of publications in recent years, the number of publications in the field of safety evacuation is not continuously increasing, indicating that the research in this field is still in the exploration stage, so the field still needs to increase innovative research efforts and cultivate more outstanding talent.

    In future work, we will further investigate and analyze the research status and trend of this field globally, so as to provide more useful information for promoting the study of crowd evacuation.

    This research was sponsored by the Major Natural Science Research Projects in Colleges and Universities of Jiangsu Province (No.19KJA460011), the National Natural Science Foundations of China (No.71774079, No.51874182), the Qinglan Project of Jiangsu Province and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

  • The authors declare that they have no conflict of interest.

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  • Cite this article

    Wu M, He H. 2024. Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products. Food Materials Research 4: e029 doi: 10.48130/fmr-0024-0018
    Wu M, He H. 2024. Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products. Food Materials Research 4: e029 doi: 10.48130/fmr-0024-0018

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Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products

Food Materials Research  4 Article number: e029  (2024)  |  Cite this article

Abstract: With the continuous development of spectroscopy technology, surface enhanced Raman spectroscopy (SERS) has been widely used as a fast and sensitive analysis method for the qualitative and quantitative analysis of trace analytes in foods. At present, SERS has been widely used in various fields such as food safety, materials, and biomedicine. However, the advances of SERS in meat safety and quality detection have not been summarized. In this review, the development history and detection principles of SERS are introduced and the advantages and potential of SERS application in the field of meat safety and quality detection evaluated. Then, two classical SERS detection modes were compared, namely labeled detection and label-free detection, in terms of the advantages, disadvantages, and application scopes. Furthermore, the specific applications of SERS in detecting bacteria, viruses, veterinary drug residues, food additives, illegal additives, and biotoxins in meat and meat products were presented. In addition, the development of SERS in meat adulteration and freshness identification are summarized. The prospects of the future development of SERS in meat safety and quality assessment will likely involve multiple method integrations, new material development, and artificial intelligence. It is expected that this review will not only provide a comprehensive summary and exploration of SERS in meat safety and quality assessment but also shed light on the future innovation and continued development of SERS in the food and meat industry.

    • Meat and meat products occupy a prominent place in the human diet. With the economic recovery from the COVID-19 pandemic, meat consumption is constantly increasing. A report jointly released by the Organization for Economic Cooperation and Development (OECD) and the Food and Agriculture Organization of the United Nations (FAO) shows that meat supply will continue to increase over the next ten years. During this period, it is expected that global per capita meat demand will increase by 2% until 2032, especially, the production of pork and poultry is expected to increase significantly[1]. At present, plant-based meat analogs are continuously expanding their market share, but further exploration of their nutritional functions is needed[2]. Meat and meat products have high nutritional value and unique flavor characteristics, compared with plant-based proteins, animal-derived proteins have higher bioavailability, and their types and proportions of amino acids are closer to human needs[3]. The balanced intake of polyunsaturated fatty acids and saturated fatty acids can maintain the nutritional balance of the body[4]. Therefore, they are more easily absorbed by the human body and meet the nutritional and health needs of consumers. Reasonable intake of meat and meat products is crucial for the growth, development, and health of the body[5]. However, richer nutrients of meat and meat products also cause several safety issues, including foodborne pathogens (bacteria, viruses, parasites), chemical substances (heavy metal elements, illegal additives, etc.)[6]. In addition, the authenticity identification and freshness evaluation of meat are also important owing to growing requirements for meat quality. Therefore, monitoring hazard residues, authenticity, and freshness is necessary to ensure meat safety and quality.

      Meat and meat products are highly susceptible to contamination during processing, transportation, storage, and sale. For small molecule pollutants, traditional detection methods include gas chromatography (GC), high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS)[79]. For microbial contamination, cultivation methods combined with molecular biology techniques or biochemical reactions are adopted[10,11]. Although these methods are of high accuracy, restrictive experimental conditions and long experimental cycles cannot meet the needs of the meat industry[12]. With the continuous development of detection technology, immunological techniques based on specific binding between antigen and antibody, including lateral flow immunochromatography assay (LFIA), enzyme linked immunosorbent assay (ELISA) and electrochemical biosensor technologies using nucleic acids, enzymes, and other recognition elements, are developing rapidly[1315]. In recent years, with the application of chemometrics and machine learning technology, the spectroscopy technology for food safety detection is becoming increasingly widespread, which can achieve the goals of predicting and classifying food samples[16]. Among them, Raman spectroscopy, as a representative technique for detecting trace molecules can quickly achieve non-destructive testing of biological samples, promoting rapid detection in food safety analysis[17]. Raman scattering is inelastic scattering of object molecules under light radiation, in which the frequency of light waves would shift compared with incident light waves. By measuring this deviation, molecular information about the vibration and rotation of relevant molecules can be obtained, thereby achieving the detection and identification of the target. Although Raman spectroscopy technology has achieved simple, rapid, and fingerprinting detection, it still faces problems such as weak Raman signals[18,19]. Researchers have always been committed to enhancing Raman detection signals and exploiting other strengths. Surface-enhanced Raman spectroscopy (SERS) has been emerging as a predominant strategy to solve such problems by virtue of surface plasmon-resonance induced high signal enhancement effects and various enhancement manners[20]. The application of SERS in the detection of meat and meat products is shown in Fig. 1.

      Figure 1. 

      Schematic application of SERS analysis in meat and meat products.

      The complexity of matrices often leads to poor repeatability of Raman signals. To improve the repeatability and sensitivity of this technology, it is necessary to develop SERS substrates with stable plasmonic enhancement. Various SERS substrates have been developed. If classified by substrate properties, they can be divided into noble metal substrates and noble-free metal substrates[21]. From the view of practicability, the existing SERS substrates can be divided into colloidal substrates and solid substrates[22]. Colloidal substrates generally include single or multiple metal nanoparticles[2325], showing better signal stability, while solid substrates exhibit higher signal amplification ability due to good morphology controllability[26]. Common forms of solid substrates include membrane substrate and self-assembled substrate[27,28]. The size, morphology, and material of SERS substrates have a significant impact on the enhancement of Raman signals[29]. For any SERS substrate, the widely accepted mechanisms for SERS enhancement effects are electromagnetic enhancement (EM) and chemical enhancement (CM), as shown in Fig. 2. The EM is excited by the strong electromagnetic field generated by surface plasmon resonance on ultrathin or nanostructured surfaces, thus enhancing the electromagnetic signal. The CM is induced by the formation of charge transfer complexes between adsorbed molecules and metal substrates, thereby achieving enhancement effects[30]. Due to its fast response speed, high sensitivity, and non-destructive detection ability, SERS has been widely applied in fields such as food safety analysis[31], environmental monitoring[32], and material science[33].

      Figure 2. 

      Enhancement mechanisms of SERS[34].

      SERS can be used in combination with various technologies, such as immunochromatography[35], molecular imprinting technology[36], colorimetric technology[37], etc., to improve selectivity, sensitivity, and detection efficiency. General SERS detection strategies are labeled and label-free detection modes in terms of detection of indirect and direct detection of the target. The former can detect Raman signals of targets without labeling or special processing, not only providing the inherent molecular information but also making the detection process simpler. However, it is limited by the concentration and complexity of the detection system[38,39]. The latter can reflect the analyte by strong Raman characteristic signals of SERS tags. With the aid of recognition elements like antibodies[40], aptamers[41], and molecularly imprinted polymers (MIPs)[36], the labeled method can achieve the detection of various targets.

      Different from other spectroscopy techniques, SERS can provide a highly sensitive fingerprint analysis, amplify the Raman signal of the analyte without fluorescence background interference, and match various laser conditions and different types of instruments including large high-resolution workstations and portable devices. Therefore, SERS has now developed into a powerful platform for quickly detecting trace extrinsic or harmful substances in meat and meat products. Compared with previous reviews, this review focuses on two SERS detection modes and their related applications in meat and meat products. SERS detection is divided into labeled detection and label-free detection to compare their advantages and disadvantages. Then, the research progress of SERS in detecting several hazards such as foodborne pathogens and veterinary drug residues are summarized, and the practicability of this technology in identifying meat adulteration and spoilage discussed. Finally, a perspective of SERS to more efficiently and sensitively meet the requirements of rapid and high-throughput detection in the meat industry is provided.

    • In the label-free SERS detection mode, the active substrate of SERS can directly bind to the analyte without additional signal indicators to assist detection[42]. The spectral information provided by this method can not only be used for the detection of the substance under test, but also for analyzing the structural information or fingerprinting of biomolecules[43,44]. Arabi et al.[45] proposed a mussel-inspired surface imprinted capillary sensor that can quickly and sensitively detect proteins. The universal sensor was not limited by pre-processing and operator skills. Xu et al.[46] used iodide-modified Ag nanoparticles (Ag IMNPs) to achieve label-free detection of single stranded DNA molecules. This detection strategy not only significantly improved Raman signals, but also reduced the probability of biological molecule denaturation during the detection process. Wang et al.[47] combined chemometric methods to achieve label-free detection of methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA), which played an important role in the detection of bacterial resistance and identification of resistant strains. To detect antibiotic residues in serum, Wang et al.[48] modified nanoparticles with bromide ions and used peak intensity changes as a basis for distinguishing different antibiotic molecules. This method is of great significance in drug detection. Zhang et al.[49] designed a SERS microfluidic chip for drug detection, providing a new platform for efficient detection of 6-thioguanine (6-TG) in human serum.

      In label-free SERS detection, the binding mode and interaction mechanism between the tested substance and the SERS substrate are worth exploring in depth, which often determines the sensitivity and signal of the detection system[42] The strategies for anchoring the tested molecule mainly include biomolecular recognition[47], non covalent bonding[50], and electrostatic and hydrophobic interactions[51]. Zhang et al.[52] used single-molecule surface-enhanced Raman spectroscopy (SM-SERS) to investigate the phenomenon of signal fluctuations caused by the adsorption and desorption of molecules near hot spots. They utilized active nanoshells to confine and anchor molecules onto the surface of plasmon nanoparticles, significantly improving the sensitivity and reproducibility of single-molecule detection (Fig. 3a). Meanwhile, combining the detected spectral data with chemometrics and machine learning methods enables more effective data analysis[53]. Raman spectroscopy data is rich and complex, with the assistance of machine learning and chemometric methods, data processing, including noise reduction and interference elimination, can be quickly achieved[54,55] (Fig. 3b). There are a wide range of applications in food analysis[56], and biomedicine[57].

      Figure 3. 

      Label-free SERS detection. (a) Schematic diagram for the detection of in-situ encapsulated active shells[52]. (b) Application of machine learning in Raman spectroscopy analysis[55].

    • When the composition of the matrix to be tested is complex or physical characteristics such as temperature and pH need to be monitored, label-free detection has significant limitations compared to labeled detection[58]. The labeled SERS detection method relies on functionalizing Raman reporters with high sensitivity, specificity, and selectivity. By observing the Raman shift and intensity changes of characteristic peaks in the Raman spectrum, the presence and amount of the tested substance can be reflected by Raman reporters[59]. Although the labeled mode cannot reflect rich intrinsic biological information, multiple SERS tags might have a potential in multiplex analysis[34].

      SERS tags need to have ultra-high sensitivity, specificity, and photostability[60]. Typically, SERS tags consist of four parts: plasmonic nanoparticles, Raman reporters, coating layers, and targeting ligands[61] (Fig. 4a). As SERS substrates, plasmonic nanoparticles are activated by localized surface plasmon resonance (LSPR) to enhance the signal. Raman reporters with excellent properties are adsorbed on the surface of the SERS substrate, and then encapsulated with a protective layer to make the particles more stable. Finally, targeting ligands such as antibodies and aptamers are connected to form SERS tags[62]. Raman reporters can be mainly divided into three categories, specifically including dye molecules containing nitrogen or sulfur-like crystal violet (CV)[63] (Fig. 4b & c), thiol molecules like 4-mercaptobenzoic acid (4-MBA)[64], and 4-mercaptophenylboronic acid (4-MPBA)[65]. Alkyne molecules possessing unique peaks in Raman silent regions that attract emerging attention on SERS due to largely reduced background interference[66]. To enhance the stability and signal strength of SERS tags, dual signal molecules for the detection of biomolecules are used[67]. The dual signal method can not only reduce the influence of external interference and improve the repeatability of detection but is also suitable for the detection of low concentration analytes in complex samples[68]. In terms of dual signal, one serves as an internal standard signal and the other as a response signal, which can reduce detection errors and have higher detection accuracy compared with single signal systems. Tan et al.[69] used 5,5'-dithiobis (2-nitrobenzoic acid) (DTNB) as the internal standard signal, 6-carboxyl-Xrhodamine (ROX) as the response signal, and the double signal based SERS sensor detected the miR-21 of human serum samples, with a detection limit of 0.046 pM. It has broad application prospects in the early diagnosis of breast cancer.

      Figure 4. 

      Labeled SERS detection. (a) The structure of SERS tags[74]. (b) Capsules encoded with malachite green (MG), crystal violet (CV), Nile blue (NB), Astra blue (AB), and methylene blue (MB)[75]. (c) Raman spectra of reporters[75].

      Liu et al.[70] combined SERS with LFIA and proposed a biosensor for detecting anti-SARS-CoV-2 IgM/IgG. This sensor used DTNB as a Raman reporter modified on silica nanosphere coated with an Ag shell, to provide a sensitive detection strategy for rapid screening of SARS-CoV-2 infection. Jiang et al.[71] synthesized Fe3O4@TiO2-based SERS tags using DTNB as the Raman reporter, achieving in situ detection of exosomal miRNAs. Zhu et al.[72] embedded 4,4'- dipyridyl (DP) into AuNPs and silica shell to prepare SERS probes with excellent stability and specificity, achieving ultrasensitive detection of E. coli O157:H7. Combined with hybridization chain reaction (HCR), Peng et al.[73] used 4-ethynylbenzaldehyde (EBA) and two different structures of HCR sequences as SERS tags, developing a novel SERS sensing method and achieving sensitive detection of hepatitis C virus (HCV) nucleic acid.

    • According to statistics from the World Health Organization (WHO), approximately 600 million people are infected with foodborne diseases[76], largely increasing the burden on the healthcare system. Meat and meat products are important sources of high-quality protein for the human body, and due to its rich nutritional content, meat is often contaminated by foodborne pathogens and bacteria[77]. The bacteria pollution sources of meat products can be divided into two categories: endogenous and exogenous pollution. The former usually refers to pollution caused by microorganisms carried by livestock and poultry, while the latter often refers to microbial pollution present in the processing and circulation process[78]. Common foodborne pathogenic bacteria in meat and meat products include L. monocytogenes, Salmonella, E. coli, etc.[79]. Consuming meat contaminated with foodborne pathogenic bacteria poses a serious threat to human life and health. Therefore, to control the occurrence of foodborne diseases and protect the development of the meat industry, it is crucial to establish sensitive and rapid methods for detection.

      At present, foodborne pathogenic bacteria can be detected through the following three strategies. Physiological and biochemical testing can indicate the presence of pathogens through chemical signals, such as the ATP bioluminescence method[80]. Immunological testing is based on specific binding of bacterial antigens followed by signal amplification, such as ELISA[81]. Molecular testing relies on nucleic acid-based hybrid and amplification, such as PCR[82]. Compared with traditional plate culture methods, these methods have achieved sensitive and accurate detection of pathogens, however, they still face several drawbacks including slower detection speed, longer detection cycles, and more operation steps[83]. Due to the multiple advantages of SERS, the technology has been widely used to detect foodborne pathogens. Yang et al.[84] reported a surface cell imprinting (SCIS) method to capture the target pathogens followed by SERS mapping detection with a nanosilver modified by 4-MPBA (4-MPBA@AgNPs) as the SERS tag. It has achieved specific and quantitative determination of E. coli in chicken breast samples, with a linear range of 102−108 CFU/mL and a detection limit as low as 1.35 CFU/mL. By changing the bacterial cell imprinting substrate, this platform can also be used for the detection of other bacteria. Cho et al.[85] proposed using membrane filtration and immunomagnetic separation techniques to capture and enrich target bacteria. Using 4-MBA modified AgNPs as SERS tags, 10 CFU/mL of E. coli O157:H7 was detected in ground beef within 1 h. In label-free detection mode, the Raman signal of the analyte mainly comes from the surface chemical composition and metabolites, but some bacteria have similar cell wall components, resulting in high similarity in their SERS fingerprint spectra. On the other hand, the amount of spectral information data is too complex to distinguish. In this case, mathematical-statistical analysis methods and chemometrics methods should be combined to eliminate signal interference during the detection process and achieve efficient detection of foodborne pathogens[86,87]. Leong et al.[88] used a SERS-based surface chemistry classification method, in combination with machine learning, to classify six types of bacteria by layering surface charges, biochemical features, and the types and quantities of functional groups. The accuracy was up to 98%, and the relationship between bacterial extracellular matrices (ECMs) surface features and SERS fingerprint spectra were successfully made. Eady et al.[89] compared traditional plate culture and PCR methods and confirmed that combining SERS with support vector machine (SVM) could realize rapid detection and accurate classification of Salmonella typhimurium in chicken rinse. In addition, Zheng et al.[90] utilized python assisted SERS chips to achieve photothermal inactivation of Salmonella typhimurium and Staphylococcus aureus in blood samples, avoiding the problem of secondary contamination during the detection process (Fig. 5). The related analytical peformances of these methods were compared in Table 1.

      Figure 5. 

      Schematic diagram of capturing, detecting, and inactivating bacteria[90].

    • Foodborne viruses that exist in various foods might cause diseases such as viral gastroenteritis and hepatitis in humans. Patients often suffer from acute vomiting and diarrhea due to ingestion of contaminated water or food[91]. Common foodborne viruses in meat and meat products include avian influenza virus, norovirus, hepatitis E virus, and rotavirus[92]. PCR is a classical technique for virus infection identification with high sensitivity and accuracy but requires complex sample pretreatment and expensive equipment[93]. In addition to PCR, immunological methods such as ELISA are also commonly used for virus detection[94]. However, the sensitivity and accuracy of this method are not as good as nucleic acid amplification technology[95]. Therefore, SERS-based methods were developed for the efficient detection of foodborne viruses. H5N1 is a highly pathogenic and deadly subtype of avian influenza virus[96]. Wang et al.[97] used an unlabeled SERS method, using AgNPs as the substrate, to achieve rapid detection of influenza A (H5N1) subtype influenza virus in chicken embryos, by forming specific sandwich immunocomplexes, with high accuracy and strong specificity. This provided a reference basis for the simple and rapid detection of various infectious viruses. Sun et al.[98] proposed a magnetic immunosensor labeled with 4-MBA for the detection of avian influenza virus H3N2. The sensor had the advantages of high sensitivity and rapid detection. Therefore, this method had the potential to be applied to the detection of avian influenza virus in other real biological samples. Wang et al.[99] designed and synthesized a novel magnetic tag with excellent signal amplification performance. The SERS-LFIA system was used to detect HAdV and H1N1, and it was found that this method had high sensitivity with detection limits of 10 and 50 PFU/mL, respectively, and could be used in real biological samples such as human whole blood, serum, and sputum. The related analytical peformances of these methods were compared in Table 1.

    • To prevent and control animal diseases, veterinary drugs, mainly include antibiotics, antiparasitic, and antifungal drugs, hormones, and anti-inflammatory drugs, have long been applied during livestock feeding[100]. The use of veterinary drugs often bring profits to animal producers and reduce losses. However, residual veterinary drugs in animal bodies may have many negative impacts on the animals themselves and consumers who consume them, including the development of drug resistance in both animal and human bodies, affecting the functioning of the immune system and the diversity of gut microbiota[101]. Before detecting veterinary drug residues, it is necessary to perform sample pretreatment to reduce external interference, which is closely related to the accuracy and precision of the detection[102]. Currently, common methods such as solid-phase extraction (SPE) and solid-phase microextraction (SPME) are used to separate the analyte from the complex sample matrices[103,104]. Even so, the sample solution after enrichment is still so complex as to direct detection and identification, thus gas/liquid chromatography (GC/LC) followed by mass spectrometry (MS) is necessary.

      It is worth mentioning that SERS has outstanding potential in detecting residual harmful chemical components. Peng et al.[105] used AuNPs as substrates to detect benzylpenicillin potassium (PG) and explored the effects of Au substrates and reporter adsorption on SERS intensity. Finally, the established method was applied to the detection of PG in duck meat. Zhao et al.[106] used OTR202 (AuNPs) and OTR103 (gold colloid enhancement reagent) as SERS substrates, combined with adaptive iteratively reweighted penalized least squares (air-PLS) to remove fluorescence and background signals, and the detection limit was down to 1.120 mg/L, achieving rapid detection of tetracycline residues in duck meat. Zhao et al.[107] established a method for determining marbofloxacin using SERS based on β-cyclodextrin-modified silver nanoparticles (β-CD-AgNPs) with a detection limit of 1.7 nmol/L. In chicken and duck samples, the spiked recovery rate of marbofloxacin ranged from 101.3% to 103.1%, providing a solution for reliable on-site detection in the future. To reduce spectral interference from other substances in food matrices, combining SERS with other separation techniques is a good choice. Shi et al.[108] used thin-layer chromatography combined with SERS, namely TLC-SERS, to achieve simultaneous and rapid (< 10 min) detection of 14 nitroimidazole compounds in pork with a detection limit of 0.1 mg/L. Based on the magnetic SERS-LFA system, Tu et al.[109] synthesized SERS tags using DTNB and 4-MBA as dual Raman reporters, combined with specific antibodies. They utilized the dual signal amplification effect of numerous stable hotspots and magnetic enrichment to detect the residues of four veterinary drugs in pork. This method achieved trace detection at the pg/mL level within 35 min, effectively improving the sample detection signal and sensitivity, and had great prospects in the detection of harmful small molecules (Fig. 6). The related analytical peformances were compared in Table 1.

      Figure 6. 

      Schematic diagram of using the SERS-LFA system to detect multiple veterinary drugs[109].

    • Food additives are artificially synthesized or natural substances that can improve the sensory characteristics and quality of food. The application of food additives has played a great role in the development of the food industry. To improve the flavor, texture, nutrition, and extend the shelf life of meat products, several food additives include antioxidants, preservatives, colorants, and acidity regulators are applied during meat processing and storage[110]. However, unscrupulous retailers, in pursuit of commercial interests, abuse food additives, and even engage in the illegal use of preservatives, colorants, and other substances with maximum amount limits in meat product production, such as the abuse of nitrite, composite phosphates, and sodium benzoate. Unreasonable uses of food additives have also brought about a series of food safety issues, posing a great threat to the life and property safety of consumers[111]. At present, the main detection methods for food additives include spectroscopy[112], chromatography[113], and electroanalysis[114]. Meanwhile, the sampling and pretreatment steps have a considerable effect on detection accuracy[115].

      For several common food additives, SERS also exhibits satisfactory potential[116]. Nitrite, as an essential food additive in meat processing, is often used as a preservative and coloring agent, but it might cause certain health risks, thus being necessary to develop a rapid SERS detection method[117]. Zhang et al.[118] enhanced the SERS signal of nitrite by introducing 4-aminothiopenol capped AgNPs decorated halloysite nanotubes (HNTs-AgNPs4−ATP), thereby achieving the detection of nitrite ions in sausages and pork luncheon meat. This method achieved in-situ derivatization and selective determination of nitrite ions in meat products through labeled SERS. The effective dispersion and deposition of metal nanoparticles play an important role in maintaining substrate stability and improving SERS performance[119]. Zhang et al.[120] developed a SERS platform for the rapid detection of nitrite using electrospinning-assisted electrospray technology. The use of this technology is of great significance for the effective deposition of certain shaped metal nanoparticles into SERS layers. The platform had good selectivity, stability, and anti-interference ability, and the detection limit was about 15.29 ng/L, realizing the detection of nitrite in chicken sausage, canned pork, bacon, and ham. Liang et al.[121] combined hydrogel materials with SERS technology to prepare a sensor for detecting the concentration of sodium nitrite, and introduced machine learning to analyze data and predict results. The minimum detection limit reaches 3.75 mg/kg, realizing the quantitative determination of sodium nitrite in the extracts of bacon, lunch meat, and ham slices. The analytical peformances were compared in Table 1.

    • In recent years, food safety accidents caused by illegal additives have aroused public attention to food quality and safety. Compared with the abuse of food additives, illegal additives have more serious implications owing to their severe toxicity to both livestock and the human body. Illegal additives mainly include melamine[122], malachite green[123], receptor agonist[124], and other substances, which are usually used to fraudulently increase nutrient content or preserve freshness[23]. The most common illegal additives in meat and meat products include β-adrenergic receptor agonists (clenbuterol hydrochloride[123], ractopamine[125], etc.) in pork, beef, mutton, and animal liver, nitrofuran drugs in pork and poultry[126], and synthetic pigments such as acid orange in meat products[127]. At present, commonly used detection methods for illegal additives include gas chromatography[128], mass spectrometry[129], ELISA[130], etc. With the continuous development of SERS substrates, Yan et al.[131] prepared transparent SERS substrates using anodic aluminum oxide (AAO) template method for direct detection of residual ractopamine on pork without the need for pretreatment. This method achieved the detection of trace amounts of ractopamine in meat samples with a detection limit of 10−8 M, and also opened up a new way for the direct measurement of other trace chemical substances on the surface of food. The uniform core-shell structure of nanomaterials significantly improves the SERS performance in signal enhancement and stability by increasing loading and reducing aggregation, which can improve detection efficiency and reliability[132,133]. Su et al.[134] designed a core-shell structure as a multifunctional tag and used the dual model colorimetric/SERS-LFIA for the detection of clenbuterol. This method increased the sensitivity of the detection system and stronger colorimetric reaction through antigen antibody specific binding, achieving quantitative detection of clenbuterol in pork, chicken, and sausages with a detection limit as low as 0.05 ng/mL. Xie et al.[127] realized the rapid detection of acid orange II in braised pork by synthesizing new core-shell nanomaterials including SERS substrates of Fe3O4@Au. In combination with machine learning methods, they verified the correctness of the detection results and compared with the results of HPLC, showing that this method can be used as an alternative to conventional HPLC methods for the detection and analysis of acid orange in food. The related analytical peformances of these methods were compared in Table 1.

    • Biotoxins are a class of toxic substances produced by various organisms such as Clostridium, E. coli, Staphylococcus aureus, and the common biotoxins in meat and meat products are botulinum toxin and shiga toxin. Biotoxins often cause acute or chronic poisoning in the human body and have become a major threat in fields such as food and medicine[135]. The detection of food biotoxins typically involves quantitative analysis using ELISA[136], MS[137], and HPLC[138]. Nowadays, biosensors based on SERS have become an important analytical method for biotoxin detection. Subekin et al.[139] developed an aptasensor based on silver nanoislands as a SERS substrate for rapid detection of type A botulinum toxin. Due to its ability to recognize molecules and serve as Raman tags, the sensor has high specificity and good reproducibility, with a detection limit of 2.4 ng/mL, and can achieve rapid detection of botulinum toxin in complex matrices. Kim et al.[140] synthesized three-dimensional magnetic beads modified with gold nanoparticles and developed a SERS-based magnetic immunoassay for rapid and sensitive detection of botulinum toxin. The detection limit of this technology for type A and type B botulinum toxin reached 5.7 ng/mL (type A) and 1.3 ng/mL (type B). The proposed method is a low-cost and efficient detection technology for botulinum toxin and promising for other trace biotoxin detection in meat. Jia et al.[141] developed a biosensor with SiO2@Au/DTNB as the SERS tag that can simultaneously detect ricin, staphylococcal enterotoxin B (SEB), and type A botulinum toxin (BoNT/A) by combining SERS with LFIA. This technology achieved rapid on-site detection of three toxins with good repeatability and specificity, and was capable of application in clinical medicine. The analytical peformances were compared in Table 1.

      Table 1.  Applications of SERS in detection of meat hazards and additives.

      Detection object SERS substrate Method LOD Ref.
      Foodborne pathogens
      E. coli O157:H7 AgNPs SERS-SCIS 1.35 CFU/mL [84]
      E. coli O157:H7 AuNPs SERS 10 CFU/mL [85]
      Salmonella typhimurium AgNPs SERS-SVM / [89]
      Salmonella typhimurium and Staphylococcus aureus pAu/G SERS-Python / [90]
      Foodborne viruses
      H5N1 AgNPs SERS 5.0 × 10−6 TCID50/mL [97]
      H3N2 AuNPs SERS 102 TCID50/mL [98]
      HAdV, H1N1 AgNPs SERS-LFIA 10, 50 PFU/mL [99]
      Veterinary drug residues
      Benzylpenicillin potassium AuNPs SERS / [105]
      Tetracycline OTR202-OTR103 SERS-air PLS 1.120 mg/L [106]
      Marbofloxacin AgNPs SERS 1.7 nmol/L [107]
      Nitroimidazoles AuNPs SERS-TLC 0.1 mg/L [108]
      Multiple veterinary drugs Au@AgNPs SERS-LFA 0.52–6.2 pg/mL [109]
      Food additives
      Nitrite ions AgNPs SERS 0.51 μg/L [118]
      Nitrite AgNPs SERS 15.29 ng/L [120]
      Sodium nitrite AuNPs SERS 3.75–8.11 mg/kg [121]
      Illegal additives
      Acid orange II AuNPs SERS-DFT 1 μg/mL [127]
      Ractopamine AgNPs SERS 10−8 mol/L [131]
      Clenbuterol Au/AuNS SERS-LFIA 0.05 ng/mL [134]
      Biotoxin
      Botulinum neurotoxin type A AgNPs SERS 2.4 ng/mL [139]
      Botulinum toxins A and B AuNPs SERS 5.7 ng/mL (A), 1.3 ng/mL (B) [140]
      BoNT/A AuNPs SERS-LFIA 0.1 ng/mL [141]
    • Meat adulteration is a fraudulent behavior of unscrupulous merchants who mix low-quality meat or non-meat substances into high-priced meat or its products to seek extra profits. Such behavior usually includes species or variety adulteration, production source adulteration, and production process adulteration[142,143]. Meat adulteration might be related to the changes in supply and demand, as well as the cost of animal husbandry and processing. However, this trickery has had a serious negative effect on the meat industry and hidden unknown safety issues. The food safety issues caused by meat adulteration are worrying. The adulterated meat might contain unknown species, pathogens, and veterinary drugs, which may not only directly affect the life and property safety of consumers but also involve religious issues and affect market stability[144,145]. The existing detection methods for meat adulteration mainly include nucleic acid detection technology[146], biosensors[147], spectroscopic detection technology[148], immunological detection technology[149], and mass spectrometry technology[150]. Currently, the detection methods for meat adulteration can be divided into non-destructive and destructive testing[151]. Non-destructive testing techniques include near-infrared spectroscopy[152], hyperspectral imaging[153], etc. Destructive testing techniques include detection based on nucleic acid[154], and protein[155]. As a non-destructive detection method, SERS has been applied in meat fraud detection. Liu et al.[156] proposed a novel detection strategy mediated by CRISPR/Cas12a followed by SERS, which could convert the target nucleic acid concentration into a visual signal for meat adulteration detection, achieving the detection of low adulteration rate samples in complex food matrices. Khalil et al.[157] designed an ultrasensitive dual nano platform SERS biosensor, namely the graphene oxide gold nanorod (GO AuNR) and gold nanoparticles (AuNPs), which could qualitatively and quantitatively detect DNA from any source. This sensor could replace traditional pork DNA detection methods, helping to more efficiently address the issues of authenticity and species origin in meat products. Khalil et al.[158] also developed a DNA biosensor for SERS that could quantitatively detect two types of meat simultaneously. The detection principle lies in the covalent conjugation between the signal probe and the capture probe. When the target sequences of two species are fixed simultaneously, the hybridization between the probe and the target achieves signal enhancement. This sensor used a SERS activity dual platform to increase detection sensitivity, with strong selectivity and specificity. As an emerging technology, SERS is still lacking in research on meat adulteration detection.

      Existing research mainly focus on the detection of species sources, and further development is needed for cases of determining the authenticity of production areas and processes. To fully explore Raman spectrometry, new data mining technologies such as machine learning should be introduced to identify adulteration. Besides, the development of portable detection devices to achieve real-time on-site assessment is another future research trend.

    • Meat contains abundant nutrients, making it an ideal place for microbial reproduction. The presence of microorganisms and some endogenous enzymes often leads to a decrease in the freshness of meat and eventual spoilage. The decrease in freshness of meat can be judged by changes in color, which not only leads to the disposal of meat and resource waste but also poses health risks such as pathogens and toxins[159,160]. With the improvement in disposable income, consumers are paying increasing attention to the freshness of foods. The traditional methods for determining freshness include sensory evaluation, chemical index detection, and microbial detection[161]. However, these methods all have some limitations. Sensory evaluation methods require specialized evaluators and the judgment results are always subjective. For chemical indicators such as total volatile base nitrogen (TVBN) and microbial detection, the detection methods are cumbersome and time-consuming, and cannot meet the needs of contemporary food industry[162]. Therefore, it is crucial to develop an efficient and sensitive non-destructive testing method that can measure the freshness of products. At present, several advanced methods for determining freshness include fluorescence spectroscopy[163], near-infrared spectroscopy[164], and visual intelligent packaging technology[165]. Notably, food freshness detection technology based on SERS has been widely reported. Qu et al.[166] achieved the detection of volatile organic compounds (VOCs) in chicken samples, including bacterial metabolites, H2S, aldehydes, and biogenic amines, by integrating array sensors and combining machine learning, thereby achieving real-time determination of their freshness (Fig. 7). Given that cadaverine and putrescine are toxic biogenic amines produced by microorganisms, posing a significant threat to human health and food security, Sun et al.[167] utilized p-MBA functionalized SERS substrates to capture the analyte molecules through amide reactions, enabling trace detection of amine substances in pork samples, which is of great significance for detecting the degree of food spoilage. Kim et al.[168] designed a SERS paper platform coated with a metal-organic framework (MOF) that could effectively recognize volatile amine molecules, and this paper's sensory has been successfully applied to the freshness determination of chicken, beef, and pork samples.

      Figure 7. 

      Schematic diagram of a scalable plasma array gas sensor for multi-dimensional SERS recognition[166].

    • With the rise in public awareness of food safety and human health, meat safety, and quality have received unprecedented attention. SERS, as an ultrasensitive detection technique, can achieve trace analysis of target analytes. Besides, the rapid and high-resolution detection characteristics of SERS make it suitable for on-site detection and multiplex analysis. This review focused on the development of the application of SERS technology in safety detection and quality assessment of meat and meat products. First, both label-free and labeled SERS detection modes were summarized, and labeled mode was predominant owing to higher sensitivity and various forms. Then, the application of SERS in foodborne pathogens, veterinary drug residues, food additive abuse, illegal additive use, and detection of biotoxin in meat and meat products were introduced. Meanwhile, the progress of SERS-based meat adulteration and freshness identification were discussed. However, SERS also faced some existing problems, such as poor reproducibility of detection results, weak resistance to external interference, and difficulty in enriching analytes. For future research, the following points can be underlined to promote the further development and application of SERS technology in the detection of meat and meat products: (1) Combining SERS with other technologies. SERS, as a sensitive detection method, relies on appropriate pretreatment operations to improve the accuracy and precision of detection; (2) Expanding SERS research on heavy metal ion pollution detection in meat and meat products by combining elemental analysis techniques, and boosting research on adulteration identification and freshness detection of meat and meat products; (3) Combining machine learning and chemometrics methods to mining Raman spectroscopy data and improving automatic detection and smart sensing. With the continuous development of material and data science, researchers will further study novel SERS substrates, SERS tags, and SERS instruments to improve the stability and repeatability of this technology, paving the foundation for safety and quality assessment in the meat and food industry.

      • This review was funded by the National Natural Science Foundation of China (22327804 and 22004064).

      • The authors confirm contribution to the paper as follows: study conception: Wu M, He H; draft manuscript preparation: Wu M; manuscript revision: He H. Both the authors read and approved the final manuscript.

      • Data sharing is not applicable to this article as no new data were created or analyzed in this study.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press on behalf of Nanjing Agricultural University. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (7)  Table (1) References (168)
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    Wu M, He H. 2024. Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products. Food Materials Research 4: e029 doi: 10.48130/fmr-0024-0018
    Wu M, He H. 2024. Recent advances on surface enhanced Raman spectroscopy in safety assessment and quality control of meat and meat products. Food Materials Research 4: e029 doi: 10.48130/fmr-0024-0018

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