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Preservation and innovation of goji berry germplasm resources

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  • Goji is a significant edible small-fruited shrub and has been a top-grade Chinese medicinal material since ancient times. In comparison to other crop species, very little information is available on goji as an important medicinal plant in terms of genetic resource conservation and development and germplasm improvement strategies. This comprehensive study illustrates the goji species-rich diversity, geographical classification, and domestic and international germplasm repositories, including their distribution and botanical features, all of which highlight the significance of the genetic architecture of this woody tree plant and provide a thorough understanding of the global distribution of goji berry germplasms, particularly in China, which can further facilitate germplasm collection for goji breeding. We also shed light on how goji berry germplasm has been improved by utilizing conventional and modern cutting-edge technologies, future research directions on the preservation and sustainable use of germplasm resources, and advances in genomic breeding strategies. This review will facilitate the development of novel goji germplasm repositories and support the strategic development of genetic resource management by prioritizing the acquisition of underutilized goji berries and advancing ex situ conservation through the application of contemporary gene bank techniques. Critical investigations have revealed gaps that need to be filled by breeders and researchers, such as the identification of wild germplasm and comprehensive genomic approaches, which could provide a basis for rapid breeding and fully utilize the genetic potential of goji berries to improve agronomic and economic traits.
  • Transportation mobility around the globe was significantly hampered by the COVID-19 pandemic, which had unprecedented effects on various aspects of society, including social activities, the economy, and daily lives. This resulted in increased car ownership, inequalities due to unemployment and poverty worldwide. Furthermore, it was found that the ridership of public transit and ride-hailing services decreased by 70%−90% and 60%−70% respectively in major cities around the globe[1]. Hence, the shift towards private vehicles, and active modes of transportation was prominent[2,3]. For this reason, many operators, micro-mobility, and carpooling players halted their services during the pandemic, which directly affected the traditional automotive section that had projected 7.5 million fewer vehicles in 2020[4].

    In the early stages of COVID-19, people strongly responded to the threats imposed by the pandemic and avoided unnecessary travel, which led to the decline of all major transportation uses[5]. Again, the need for travel was noticeably reduced by encouraging work from home, distance education, job dismissals and abandonment of all social gatherings. Since these implications occurred in various phases of the pandemic, the deviations in travel patterns and transport mobility among the phases were prominent, specifically for commuting and social/recreational/leisure trips. In many countries, traffic was reduced dramatically across the weeks and during the lockdown period this volume declined significantly[6]. Therefore, the pandemic has immensely affected how people travel, their mindset, and their modal choices, including the use of private vehicles, public transportation, and active modes. This has also played a delicate role in advocating the decrease of environmental pollution from traveling.

    Although most studies were skewed toward traffic demand and mode choice modeling[7], the logical reasoning, and behavioral changes behind such outcomes and decisions were undermined. Therefore, a comprehensive literature review is crucial to delineate the current understanding and explorations associated with user behaviors in transportation mobility during and after COVID-19 in a global manner. Hence, this study aims to explore the literature gaps and point out behavior change, mobility changes, and their holistic impacts on different study themes through a rigorous literature review. The study has explored previous papers that focused on short-distance mobility and have refrained from long-distance mobility modes.

    The framework for this systematic literature review was prepared considering the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The primary search strategy focused on the keywords: COVID-19, mobility, and transportation. Boolean operators AND and OR were used to combine these keywords for a broader search scope. The study utilized literature from Scopus, a database indexing high-quality, peer-reviewed publications across various topics. The initial search yielded 1,037 articles.

    These articles were screened using the following exclusion criteria: only English-language publications from peer-reviewed journals published between January 1, 2020, and December 31, 2022, were included. Articles containing the keywords COVID-19, public transport, travel behavior, mobility, or their synonyms in the titles, abstracts, or reference lists were also included. All other articles were excluded. This screening process eliminated 562 articles, leaving 475 for further review.

    For the full-text analysis stage, an additional set of exclusion criteria was applied: studies outside the subject areas of social science, engineering, decision science, mathematics, and psychology were excluded. Additionally, irrelevant studies that did not align with the review scope based on title, abstract, key findings, or keyword review were excluded. This process resulted in the exclusion of 379 studies, leaving a final selection of 96 articles for the bibliometric analysis. The PRISMA diagram (2022) for this study is presented in Fig. 1.

    Figure 1.  The three-phased PRISMA (2022) diagram of the literature selection process.

    In the second phase, the three dominant themes were identified by using three distinct screening processes, which are as follows.

    The first step analyzed the abstracts using topic modeling analysis in Python that generated a comparison diagram of the top 50 keywords and their frequencies (Fig. 2), providing the foundational understanding of the overall thematic landscape. This powerful tool is used in bibliographic analysis to uncover and identify thematic patterns.

    Figure 2.  Frequencies of the top 50 most used words in article abstracts.

    The Natural Language Toolkit's (NLTK) Punkt tokenizer was leveraged in Python for sentence splitting. Additionally, a stop word list was employed to clean the textual data from the 96 reviewed papers. Analyzing these high-frequency words provides a glimpse into the main topics discussed across the papers.

    For instance, words like 'public', 'mobility', 'changes', 'urban', and 'travel' appeared frequently. Interestingly, terms related to 'policies', 'sustainability', and 'green' were also used quite often. Notably, the prominence of words associated with 'change', 'sharing', and 'behavior' suggests a focus on public mobility and how urban behavior has changed. Additionally, words like 'transit', 'share', and 'system' indicate discussions on various modes of transportation, including mobility sharing and public transit systems. Similarly, the presence of terms like 'traffic', 'demand', and 'patterns' imply that traffic demand and patterns might have been analyzed for different modes of transportation.

    However, this preliminary analysis offers limited insights. To gain a deeper understanding of the thematic landscape, a Keyword Co-Occurrence analysis was conducted based on the keyword interpretations derived from topic modeling.

    Next, VOSviewer was employed, a text-mining tool, to conduct an in-depth analysis of the two-dimensional co-occurrence patterns of keywords (Fig. 3). Following this analysis, the keywords identified were simplified in the co-occurrence diagram by grouping them into three overarching themes based on their thematic dominance.

    Figure 3.  Keyword Co-Occurrence of 96 papers.

    Figure 3 depicts the co-occurrence of keywords extracted from the 96 reviewed papers, visualized using VOSviewer text mining software. The illustration reveals nine distinct research lines represented by nine colors.

    Thematic analysis of research lines:

    (1) Light blue cluster: This cluster, with the largest area, focuses on the impact of COVID-19 on travel behavior, specifically its effects on micro-mobility, trip purpose, and public transportation.

    (2) Dark blue cluster: While this cluster also touches upon the impact of COVID-19, it has a more specific focus on public transportation. It likely explores the pandemic's unique effects on ridership, service provision, and potential changes within public transportation systems.

    (3) Straw-colored cluster: This cluster explores the relationship between travel behavior changes and broader transportation trends. It examines the influence of travel behavior on public perception shared mobility adoption, and sustainable transportation.

    (4) Green cluster: This cluster investigates the interplay between the pandemic, travel behavior modifications, and transportation policies. It focuses on the pandemic's impact on travel behavior, the resulting traffic congestion patterns, and the effectiveness of lockdown policies.

    (5) Orange cluster: This cluster focuses on the impact of telework and equity on mobility.

    (6) Purple cluster: This cluster explores research related to shared urban mobility during the pandemic.

    (7) Pink cluster: This cluster investigates primarily public transit and congestion.

    (8) Brown cluster: This cluster examines the topic of transport policies.

    (9) Red cluster: This cluster focuses on human mobility habits and their relationship with smartphones.

    While the VOSviewer analysis identifies nine research lines, these can be logically grouped into three overarching themes based on their focus. These are:

    (1) Impact on ride-hailing services

    The light blue, red, straw, and purple clusters touch upon aspects of ride-hailing services (depending on the specific studies within those clusters), their impact on the mobility and change in behavior.

    (2) Impact on mode preference

    This theme could potentially encompass the light blue, dark blue, purple, straw-colored, and pink clusters. These clusters explore various aspects of travel mode selection including:

    • Impact of COVID-19 on public transportation use (light blue, dark blue)

    • Shared mobility options during the pandemic (purple)

    • Influence of travel behavior changes on mode preferences (straw-colored)

    • Public transit and congestion patterns (pink)

    (3) Impact on trip purpose

    This theme could potentially encompass the light blue, green, orange, and brown clusters. These clusters explore the reasons behind travel choices during the pandemic:

    • Impact of COVID-19 on trip purposes (light blue)

    • Travel behavior changes and their link to trip purposes (green)

    • Impact of telework arrangements on travel needs (orange)

    • Effectiveness of transport policies on trip purposes (brown)

    • Impact of mobility habits due to COVID-19 (red)

    This thematic grouping provides a more structured understanding of the diverse research directions. However, it's important to acknowledge that automated analysis using VOSviewer may not perfectly capture the nuances of each study. To address this limitation, manual screening was employed as an additional step.

    In the third phase, four reviewers (the authors) manually screened and verified the three themes based on key findings, research objectives, and abstracts of the 96 selected articles (as depicted in Table 1). This manual verification process helps ensure the accuracy and robustness of the thematic grouping.

    Table 1.  Theme considerations of keywords from different colored clusters.
    Keywords of different colored clusters (Fig. 3) Theme considerations after manual checking
    Telework Impact on Ride Hailing Services:
    In this theme, keywords and topics related to shared modes of transport, ride hailing services obtained via smartphone/tele networks, sustainable transportations used in ride hailing services and smart mobility options were considered.
    Bike sharing
    Transport policy
    Sustainable transportation
    Smart mobility
    Smartphone
    Shared mobility
    Sustainability
    Micro mobility Impact on Mode Preference:
    In this theme, keywords and topics related to different types of modes like public transportation, micromobility options, motorized mobility and mobility habits and choices that affected mode choices were considered.
    Public transit
    Transit
    Mode choice
    Mobility habits
    Public transportation
    Public transport
    Trip purpose Impact on Trip Purpose:
    In this theme, keywords and topics related to travel behavior and public perceptions regarding mobility that affected trip purpose were considered. In addition, the effect of traffic congestion was also taken into account.
    Traffic congestion
    Travel behavior
    Public perceptions
    Urban mobility Common Themes/Search Terms:
    COVID-19 and its synonyms used throughout different literature were taken into consideration. For mobility, its synonyms were also considered.
    Human mobility
    Mobility
    Pandemic
    Lockdown
    Covid-19
    Corona virus
    Transportation
    Sars Cov-2
    Covid-19 pandemic
    Equity Other Items:
    These keywords came out as prominent in different literature.
    Transportation justice
    Machine learning
    Latent class cluster analysis
     | Show Table
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    After identifying the three themes, they were further subdivided into sub-themes through manual screening by reviewers. Subsequently, the selected articles were assigned to the themes and sub-themes, considering and presenting any overlapping themes in Table 2.

    Table 2.  Theme and sub-theme distribution of reviewed literature.
    Major theme Ref. Sub-theme Keywords
    Impact on Ride
    Hailing Services
    [931]

    Overlapped with Major Theme: Impact on Mode Preference − [46, 49, 51]

    Overlapped with Major Theme: Impact on Trip
    Purpose − [69, 97]
    Change of Demand and Usage Anthropogenic air pollution, autonomous public transport, autonomous vehicles, bicycles, bike sharing, bike sharing system, car use, COVID-19, case studies, demand responsive transport, diseases, disease prevention, emerging mobility, epidemic and pandemic, human and behavioral factors, information and communications technology (ICT), instrumental variables, literature review, modal shift dynamics, ordinal logistic regression, public transportation, public transport, ridership, safety perceptions, Seoul, sharing anxiety, smart cities, smart city, social factors, transportation demand, transportation policy, travel behavior, travel characteristics, urban form, urban mobility, urban planning
    Rise of
    Micromobility
    Active travel, bike sharing system, causal inference, cycling, COVID-19, e-scooter sharing system, food purchases, transportation means, spatial coupling, travel behavior, Saudi Arabia, spatiotemporal mean, user perception, lockdown, lockdown citi bike usage, urban greenway, micro-mobility, infrastructure intervention, mobility-as-service, natural experiment, yellow taxi demand, propensity score regression discontinuity
    Shift in service offering and safety measures Accident, car sharing usage, China, COVID-19, discrete choice modeling, generalized regret minimization, Heckman modeling, lockdown, ordered logit model, pandemic times, perception of risk, post-COVID-19 travel behavior, post-COVID-19 mobility public transport, random regret minimization, random utility maximization, ride-sourcing, road safety, shared mobility, sharing mobility, smartphone, sustainability, transport equity, travel behavior, travel mode choice, urban infrastructure, urban mobility, factor analysis, bike sharing motivations, perceived accessibility, sustainable transportation
    Socioeconomic Disparities Causal inference, coronavirus, COVID-19, COVID-19 effects, demand forecasting, discriminative pattern mining, health impacts, high-speed rail, instrumental variables, interpersonal distancing, mobility habits, mobility, multimodality, order-preserving traffic dynamics, public transport, recovery, ride-sharing, smartphone, suburban rail services, sustainable mobility, train capacity, transport equity, transportation, transportation planning, perceived accessibility, public transportation, lifestyle, teleworking, residential location
    Impact on Mode Preference [13,8,3268]

    Overlapped with Major Theme: Impact on Ride
    Hailing Services −
    [10, 12, 17, 21, 29, 31]

    Overlapped with Major Theme: Impact on Trip
    Purpose − [71, 76, 86, 87, 95]
    Personal Vehicles Active travel, anthropogenic air pollution, bluetooth traffic monitoring system, COVID-19, disease prevention, equity, generalized linear mixed effects mode, Google and Apple mobility data, greenhouse gas emissions, healthy cities, Indian cities, mobile device data, mobility, mobility-shift, multi-disciplinary, post-pandemic, prediction, public transport, resilient public transport, smart card data, smart mobility, transport modes, transport policy India, transportation demand, travel behavior, travel modes, university students, transportation, travel behavior, modal share, level of urbanization, lockdown, Slovenia
    Towards Public Transportation and Shared mobility Bicycles, big data analysis, bike sharing motivations, bike-sharing system, biking Barcelona, Bluetooth traffic monitoring system, capacity management, case studies, case study, commuting, coronavirus, COVID-19, diseases, dockless bike-share system, emergency, epidemic and pandemic, factor analysis, food purchases, health impacts, homelessness, human and behavioral factors, inequality, infection fear, lockdown, lockdown CITI bike usage, longitudinal case study, mixed methods, mobility, mobility behavior, mobility change, mobility habits, mode shift, new normal, pandemic, prediction, probabilistic machine learning, propensity score regression discontinuity, public perceptions, public transit, public transport, public transport networks, public transport planning, public transportation, quasi-experimental research, recovery period, resilient transport systems, ridership, rural areas, safety-and-mobility trade-off, sars-cov-2, Seoul, smart card data, smart mobility, social distancing, social equity, social factors, spatial compartmental model, spatial coupling, spatiotemporal, sustainability, sustainable, sustainable mobility, tactical urbanism, teleworking, transit, transport and mobility related inequalities, transport and society, transport policy, transportation, transportation justice, transportation means, transportation planning, travel behavior, urban mobility, work from home, yellow taxi demand, Air quality index, COVID-19 response
    Active Transportation Activity-travel, best-worst scaling, bike-sharing system, biking Barcelona, built environment, central businesses district (CBD), corona, COVID-19, daily commuting, discrete choice, equity, generalized linear mixed effects mode, google and apple mobility data, google mobility report, Indian cities, mobile device data, mobility, modal choice, mode choice, pandemic, passenger transport, person-miles traveled, policy, probabilistic machine learning, public transport, quasi-experimental research, smart city, social impact, structural equation modeling, sustainability, sustainable mobility, tactical urbanism, telecommuting, traffic psychology, transport, transport policy, travel behavior, travel modes, urban mobility, urban planning, working from home, active travel, bike sharing
    Impact on Trip Purpose [6997]
    Overlapped with Major Theme: Impact on Ride
    Hailing Services − [20]

    Overlapped with Major Theme: Impact on Mode Preference −
    [34, 37, 55, 65, 67]
    Mode Choice on
    Trip Purpose
    Activity-travel, activity chain, adaptive travel behavior, Americans with disabilities act (ADA), best-worst scaling, bike sharing systems, car use, causal inference, city periphery, COVID-19, covid-19 effects, COVID-19 strategies, disabled people activities of daily community, discrete choice, discrete choice model, disruptive events, dynamic CGE model, everyday leisure travel, GBDT model, global south, google mobility report, households, hurdle model, intercity bus transport, level of urbanization, lifestyle, lockdown, mobility, mobility patterns under epidemic modal choice, modal share, modal shift dynamics, modal split, non-mandatory activities, older adult, pandemic, paratransit, passenger transport services, people with disabilities, person-miles traveled, policy evaluation, public perceptions, public transit, public transport, public transport networks, public transportation, recovery period, recovery scenarios, residential location, ride-sharing, risk, safety perceptions, service contracting, service quality, Slovenia, social and recreational trips, social distancing, structural equation modeling, sustainable transport, sustainable transportation, telecommuting, teleworking, time-varying, transit, transport, transport and society, transport behavior, transportation equity, travel behavior
    Behavioral and Socioeconomic Effects Activity space, attitude towards teleworking, auctioning, coronavirus, commuting, COVID-19, daily commuting, demand management, equity, greater bay area (GBA), inequality, inflow control, latent class cluster analysis, mobile phone data, mobility, mobility habits, mode choice, movement control order, o–d flow, pandemic, pricing, public transit, public transport, public transportation, recovery, shopping, shopping trips, social exclusion, social inequity, spatial interaction, sustainable mobility, sustainable mobility, teleworking behavior, tradeable permit schemes, train travelers, transportation, travel behavior, travel frequency, travel patterns, trip purpose, work-based trips
     | Show Table
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    Finally, comprehensive review techniques like keyword extraction, key finding analysis, method analysis, etc. were employed to analyze various bibliographic features of the 96 reviewed articles. These features included location (country), study methodology, research timeline, trip purpose, analyzed modes, mode preference, and socioeconomic factors. Word cloud diagrams for the top 50 words were also used to show how the different literature revolved around certain keywords.

    Full-text analysis of the selected literature was then conducted to examine the impact, trends, and behavioral factors influencing transportation mobility within the three identified themes. This analysis also aimed to identify potential recommendations and research gaps. The workflow of the research is presented in Fig. 4.

    Figure 4.  Research workflow.

    The selected 96 articles were published in 36 reputed peer-reviewed journals, where the top three journals were Transport Policy with 21 publications, Sustainability with 13 publications, and Transportation Research Part A: Policy and Practice with 10 publications. All the journal articles are presented in Fig. 5.

    Figure 5.  Articles from different journals considered for detailed review and analysis.

    Among the 475 primary selected papers, 96 papers from 36 academic journals were retained for systematic literature review. 69.8% of the papers conducted research during 2021, followed by 2022, and the least number of papers during 2020. This pattern coincides with the fact that by 2021, the pandemic had its highest infection rate and this started to decrease during 2022[1]. Unfortunately, 216 countries or territories were affected by this disease. Subsequently, in the 96 papers, research was conducted in 35 countries, where the USA was one of the most affected countries, showing the highest numbers of research (16 papers), followed by Spain (seven papers) and India (six papers) in second and third positions respectively. Again, eight papers focused on worldwide coverage, while five concentrated on Europe and other selected countries since lockdowns in countries globally started in March 2020 (except China) owing to the uncontrolled outbreak (Fig. 6). The distribution of papers in different countries around the globe is illustrated in Fig. 7.

    Figure 6.  Lockdown initiation date and origin location of the analyzed articles.
    Figure 7.  Distribution of countries based on research location (highlighting the top 10 countries).

    This dispersal was further analyzed through a Sankey diagram (Fig. 8) to illustrate the distribution of the selected papers across different countries and highlighting their contribution to each focal theme (Table 2). The size and position of the Sankey's segments correspond to the number and significance of papers from each country, where the USA had a key contribution in all the focal themes, followed by Canada and Spain. However, India, Switzerland, Iran, and Sweden, among others, lacked the ride-hailing theme. Furthermore, other countries focused on either a single theme that had a physical effect on their society or was expected to have a foreshadowing effect soon.

    Figure 8.  Sankey diagram showing country of origin of the articles from three focal themes.

    Interestingly, 44.8% of the papers were either interviews, survey-based, or hybrid, whereas the rest of the papers used secondary data for their analysis. In the interview/survey-based papers, 31 pieces of literature collected their data online, and only nine papers physically considered the pandemic situation. Web-based interviews/surveys usually provide a wide range of convenience and respondents even in distant places. However, this could serve as the nesting ground for various biases, including self-reporting and response and non-response biases[8], which decreased the accuracy of the analysis. On the other hand, all these papers conducted their research through general evaluation of reports (highest), model building, standard statistical analysis, case study, and literature reviews presented in Fig. 9.

    Figure 9.  Analysis methodology adopted across 96 articles.

    Out of the 96 papers analyzed, 12 did not mention or analyze any specific transport mode and they discussed mobility in general. The remaining 84 papers focused on various transport modes, collecting and analyzing primary and/or secondary data. Public Transport Systems (PTS) were the most frequently analyzed, mentioned in 59 papers. Private transport was the subject of 35 papers, while both Road Safety Systems (RSS) and pedestrian transport (Foot) were covered in 27 papers, each. Cycle transportation appeared in 25 papers, and motorcycle transport was discussed in nine papers. Less frequently analyzed modes included paratransit and air, each mentioned in three papers, and micro transit, which was the focus of only one paper. Fifty-three papers discussed more than one mode to form a comparison. This distribution indicates the diverse range of research interests and the varying emphasis placed on different transport modes. A graphical representation of this is shown in Fig. 10.

    Figure 10.  Number of papers mentioning the listed transportation modes.

    A word cloud with the top 50 words from keyword analysis depicts the intensity and dynamicity of keywords (Fig. 11), to which indicates the studies mostly revolve around the keywords mobility, public, transport, covid, travel change, research, etc.

    Figure 11.  Word cloud with the top 50 words from keyword analysis.

    Shared-micro mobility services surged in demand to facilitate a disease-resilient transportation system during the pandemic. A study in Singapore found that the total ridership increased by 150%, suggesting that the bike-sharing systems were an important alternative when public transit services became restricted[12]. Furthermore, in Karachi, Pakistan, individuals with more than two family members who traveled less than seven miles likely preferred carpooling[20]. Surprisingly, people with a higher net monthly income continued to generate more shared trips during this time in Dhaka, Bangladesh[13]. In Lisbon, Portugal there was an increase in bike sharing systems which became the most favored mode of mobility while public transport use decreased[69]. Unfortunately, sharing anxiety and willingness to share rides come as a major obstacle[22] in ride-sharing programs. For example, in Seoul, South Korea this decreased bike sharing and rentals drastically[21].

    During the pandemic, a study in India found that for public transit and sharing mobility, the demand dropped by 11% and 2% than the pre-pandemic time[98]. In Taipei and New Taipei of Taiwan there was a decrease in usage of metro and bicycle sharing between 8% and 18%, as well[46]. In Manhattan, USA the use of bicycle sharing was high and its demand surged more than yellow taxi system[51]. These findings correspond with study results that show public transport being the least preferred mode (Fig. 12). After the pandemic, there was a difference in travel demand recovery for different modes. For example, demand recovery was seen faster worldwide in private modes than in public transit or shared mobility[99].

    Figure 12.  Comparison between most preferred and least preferred transportation modes.

    Many of the studies were limited to the data from students[10], and many respondents had cultural differences, where herd behavior and personal space were not taken into account[22]. Limitations to demographic factors[19,30], and socioeconomic factors like high and low-income neighborhoods[31] decreased the accuracy of the models to predict behaviors and mode choice. Hence, factors like socioeconomic and psychological characteristics that affected user behavior in shared mobility went unnoticed in many cases.

    As the impact of the pandemic started to diminish, service offerings in vehicles increased which improved the willingness to use vehicle-sharing services[14]. Users felt safer in this case and understanding user preference provided improved management in recovering demand[9]. For example, in Lisbon, Portugal before the COVID-19 pandemic the motivation to use bike sharing relied on personal well-being, service coverage and quality, this changed during the pandemic and the importance of public transport started to decrease[49]. In addition, a study in China found that travel mode choice shifted towards maximizing utility rather than fear of infection. There was an increase in using ride-hailing services for shopping and recreation activities in China, as well[25]. This might have happened due to the disruption created to the normal economy in China which suggests that individuals had to reassess their spending habits and divert to more cost-effective and convenient options to maximize utility. However, there was a willingness to pay between 19%−41% more for ride-sharing services depending on different trip purposes in Spain[14].

    However, these studies in many instances underrepresented populations, for example, respondents over age 65 referring to the elderly and lower-income households[11]. However, a study found that the disadvantaged group (elderly, low-income, and less tech-savvy people) had the disadvantage of accessible choice such as using virtual platforms and were forced to go outside to fend for daily and social necessities[24]. In addition, survey-based data might be highly conditioned by traumatic experiences that have been caused by socioeconomic uncertainty and health concerns[8]. Hence, further research considering this underrepresented group can be in understanding their ride-hailing services can be done in this regard.

    Along with increased public transit trips, there was a sturdy growth in the number of COVID-19 cases, which indicated a cause-effect relationship[17]. In another study, it was found that the impact of COVID-19 on public transportation at stations situated outside Lisbon municipality and in lower-income zones was lower[23]. This might have happened as areas outside the municipality have fewer users of public transportation and people in lower-income zones were forced to use active modes like walking and cycling. Interestingly a study suggested that cost and convenience which played a crucial role in the mode choice decision was slowly being replaced by the risk of getting infected through different modes which in turn hinted to the increased demand for private modes and active modes of transport[97]. Since higher-income people had alternatives to this type of sharing service, they were exempt from using ride hailing services. In China, during this period, experienced older drivers who were active in duty and were highly respected depended more on ride-sharing services to make a living[18].

    Policy implications based on these studies had specific limitations, for example, lacks causation insights and is limited to an ordinal variable[26]. Artificial intelligence and urban computing get easily influenced by data bias and data transparency[23], raising ethical issues. Overall, studies never explored the long-term effect and recovery strategies for ride-hailing services in a post-pandemic scenario.

    The demand for bikes, private cars, and public transportation trips gradually changed in popularity with the increased health concerns during the pandemic[21]. Because of the lockdown, web-based activities substituted many of these trips[29]. Many people quickly rehabilitated their preferences from public and shared means to foot and private vehicles when the infection rates got worse[10]. For example, in Slovenia when commuting was reduced significantly due to lockdown, private modes like cars remained the main choice of travel, especially in rural areas[95]. Also, in Taipei, Taiwan, there was an increase in motor vehicle ridership[46]. This might have been because of factors like reduced exposure risk, avoidance of crowded spaces, and safe mobility. However, a study in Fuenlabrada, Spain contradicts this as private mobility decreased to 86% of their pre-COVID demand during the pandemic and made a faster recovery than public mobility which decreased to 94% of its pre-COVID-19 demand[48]. A finding in India found that for work trips, share for private modes and non-motorized transport were 10% and 4% higher among respondents after the COVID situation relaxed[100]. Preference for individual modes of transportation in China increased by 8.7%, whereas shared transportation modes decreased by 12%[25]. Similarly, in Greece, the use of public transportation services decreased significantly, dropping from 3.85 times per week to 0.69 times per week[39]. Again, Fig. 12 demonstrates that individual modes like private vehicles, motor bikes, bicycles, walking, etc. were preferred most.

    These findings indicate factors like socioeconomic stability and healthy safety perception play major roles in choosing modes. Notably, in some studies, lower-income people with limited access to the web and modern devices were underrepresented[1,31,44,86]. Furthermore, other studies had limited sample sizes that had spatial and temporal limitations[47,48], and few focused on students only[10,41]. In addition, processes like generalized linear mixed-effects[3] and regression models[1,44,55] being suitable for hierarchical data accounted for random effects of mobility due to COVID. Similarly, Gaussian Process Regressors[48] require a relatively large amount of data to effectively model complex relationships. These methods were employed by utilizing underrepresented lower-income groups and the socioeconomic stability of users, which is a recurring practice in many of the studies under this theme.

    The pandemic situation highlighted the vulnerability of local public transit and the perception of safety[60]. During the pandemic, public transportation usage in Turkey and Spain drastically decreased by 80%[64] and 95%[48] respectively. In addition, because of the lockdown, there was a higher willingness to telework which further decreased public transportation use[36]. However, public transit was a critical mobility option for the homeless or lower-income people[76]. In Washington, USA the lower-educated and lower-income people experienced declines in travel intensity, which affected their travel behavior even after the COVID period[54]. This solidifies the finding of this study that public transportation is the least preferred mode in most of the papers that discussed this topic (Fig. 12) but for people who have no other choice, public transportation played a significant role. However, many countries have already started to bounce back with predictions going for higher travel frequencies related to public transport[98]. Again, a study in Toronto, Canada observed a decrease in the usage frequency of ride-sourcing but a small percentage of respondents showcased an increased ride-sourcing usage, which might have attributed to the increased perseverance to avoid crowded spaces and public transit[11].

    Similarly, a study in Manhattan, USA found that the impact of the shared mobility system was higher than the yellow taxi system, and the demand surged during the pandemic[51]. In Daejeon, Korea, bike-sharing increased both during and after the pandemic[101]. However, a study in Barcelona revealed that the liking to bike sharing decreased during the pandemic[2], which is opposed to the study findings that found mobility sharing as one of the most preferred modes (Fig. 12). Then again, a study suggested that shared micro-mobility had the potential in the future to become a disease-resilient mode of transport[12]. This indicates that certain demographic, socioeconomic, and psychological factors address the choice of shared mobility, which needs to be focused on.

    In North Carolina, USA, individuals preferred walking and driving over public transit during the pandemic[1]. On the other hand, a study in Dhaka, Bangladesh found that non-motorized vehicles were 19.93% more popular[10]. Again, in The Netherlands, measures that encouraged cycling and walking also scored positively[42]. However, in Greece, this effect varied for males and females as parameters like ecological footprint, safety measures, and personal safety mattered most for females. Cycling was more preferred there and 30% of their population already reduced car usage even after the pandemic[67]. In Spain, there was also a slight increase in the usage of active modes of transport[87]. In Shiraz, Iran, the average cycling and biking was still higher for Central Business District users after the pandemic[55].

    A similar case also occurred in many European countries as demand for active modes of transportation continued to increase after the pandemic[32]. These outcomes align with the findings of this study. Active modes of transportation are one of the most preferred modality choices (Fig. 12). However, the majority of the papers that discussed active modes of transportation relied on general evaluation and normal statistical analysis and had data limitations mentioned in the earlier themes. However factors that presented user behavior/personas were sometimes shadowed by traffic demand and policy mapping.

    For rigorous classification, trip purposes were clustered into three distinct types: (1) Mandatory trips, (2) Maintenance trips, and (3) Discretionary trips[91]. At the start of the pandemic in Brazil, there was a substantial reduction in working (Mandatory trips) and non-essential (Discretionary trips) trips. Results indicated that essential workers were nearly three times more likely than the general population to make a mandatory trip during this time. Discretionary trips were more likely to be made by males in comparison to females[77]. Again, in Zurich, Switzerland, maintenance trips like park and grocery visits increased, while discretionary trips decreased during the lockdown period. This observation coincides with the findings of this paper that revealed the occurrence of Maintenance trips the most, with 12 papers focusing on this aspect.

    It is noteworthy that Mandatory trips experienced the most substantial decline during the COVID-19 pandemic. Findings of the study conducted by Rafiq et al.[71] and Pawar et al.[93] concluded that the severity of COVID-19 had a more pronounced impact on workplace visits during the pandemic, which also affected low-income workers. Discretionary trips had lower travel frequency by 92% in comparison to mandatory trips in India. The diverse choices made by users during the COVID-19 pandemic are presented in Fig. 13. In Seattle, USA mandatory trips like medical trips increased drastically and people from lower-income communities highly relied on paratransit[34].

    Figure 13.  Mode choice preference by percentage.

    During the pandemic, discretionary trips were largely canceled due to lockdowns[78]. For people with disabilities, their daily travels were significantly reduced by destination[82]. However, older adults preferred active modes of transportation during and after the pandemic to avoid social constraints and crowds in their trips[55]. In the USA, transit riders with lower incomes had reduced their trips significantly[87]. In King County, Washington, USA people with lower education and lower income also reduced their travel significantly[55]. Again, in Toronto, Canada, people were reliant on private vehicles rather than public transit for non-mandatory trips[91]. Furthermore, there was a significant drop in trips based on travel purposes, infection, fear, occupation, and household[96]. In the USA, public transportation use among lower-income groups decreased by 32%, and among the general population, it declined by 51%[54]. These findings signify changes in travel behavior due to changes in socio-economic characteristics[55,65]. This greatly affects the purpose of trips for different demography of people during the COVID-19 pandemic.

    The objective of this research was to examine the alterations in transportation mobility and travel patterns due to the COVID-19 pandemic. Utilizing a systematic review and bibliometric analysis, 96 papers from the Scopus database were rigorously. These papers were categorized into three major themes: 'Impact on Ride-Hailing Services', 'Impact on Mode Preference', and 'Impact on Trip Purpose'. Text mining techniques were employed to extract key findings from each theme.

    The majority of the research works focused on the year 2021, corresponding with the pandemic's peak. Interestingly, a geographical correlation emerged between the severity of the outbreak and the location of the research. The USA dominated research output, followed by Spain and India. Notably, the USA consistently played a significant role across all themes, while some countries prioritized themes with direct societal impact, potentially reflecting resource limitations or immediate infrastructural needs. This research disparity highlights the need for a more balanced global perspective in future investigations. Increased research focus in regions with initially lower output is crucial for a comprehensive understanding of the pandemic's long-term effects on travel behavior.

    This systematic review identified a dominance of interview/survey-based research (44.8%), often relying on online data (31 papers), which can introduce bias. Future studies should prioritize data triangulation with on-ground surveys and travel data, alongside longitudinal approaches, to gain a more comprehensive picture. Future research should incorporate sensor-based data collection (e.g., travel time estimation from GPS data) and agent-based modeling to simulate travel behavior under different pandemic scenarios. This would allow engineers to test and refine infrastructure modifications and public transportation policies for optimal efficiency and user safety. Significant literature gaps exist in under-represented regions (minimal initial research) and for vulnerable populations, highlighting the need for broader regional coverage and a deeper understanding of the pandemic's impact on diverse demographics and the three themes: 'Impact on Ride-Hailing Services', 'Impact on Mode Preference', and 'Impact on Trip Purpose' of this paper.

    The COVID-19 pandemic exposed significant vulnerabilities in the shared mobility landscape, with ride-hailing services experiencing drastic shifts in demand, usage patterns, service offerings, and safety protocols. Shared-micro mobility also emerged as a crucial alternative during public transport restrictions, particularly in developing regions where usage surged[12], other areas witnessed declines due to concerns about shared surfaces and potential virus transmission. These contrasting trends highlight the multifaceted nature of user behavior in shared mobility and underscore the critical need for in-depth research on the psychological and behavioral factors influencing mode choice within this sector. The co-occurrence diagram of keywords also revealed prominent studies on the effect of travel behavior on shared mobility and sustainable transportation. Such research can be instrumental in developing targeted interventions to foster long-term sustainability for shared mobility models across diverse geographical and socio-economic contexts. In addition, research on the provision of flexible transportation strategies should be given emphasis to prepare for similar pandemic situations in the future.

    For sustainable urban development, multimodal transportation is advocated over reliance on a single mode, with telecommuting being an integral part of sustainable infrastructure strategies[7]. However, during the pandemic a concerning trend has emerged – a rise in private car usage documented across various studies[1,3,10,20,25,46,47,52,60,91,95,97]. Studies have consistently emphasized the importance of bolstering infrastructure for cycling, such as expanding and maintaining dedicated bike lanes and improving route quality and intersection safety for pedestrians[2,35,93]. Similarly, enhancements in walking infrastructure were recommended, focusing on route quality, intersection safety, and the incorporation of green spaces, which positively influence walking utility[35,93,83]. It is seen from above that many studies emphasized infrastructure and policy recommendations that promoted multimodal travel, particularly combinations with active transportation modes. This presents an opportunity for urban planning engineers to re-evaluate existing infrastructure. While the focus on sustainability is commendable, a gap exists in understanding commuter preferences for these combined trips. To address this gap, further research is necessary to explore commuter preferences and the various travel mode combinations they utilize, with a specific focus on informing the development of sustainable infrastructure.

    Public transportation usage by low-income groups persisted during the pandemic[23,34,37,39,40,54,76,77,86,91]. It was also found the modal share of public transportation drastically decreased to less than 10% according to certain authors[95,77]. These findings signify that public transportation systems were one of the least preferred modes of travel during the pandemic and this was the most frequently analyzed, mentioned in 59 papers. This highlights the need for targeted solutions and policy implementations to support these populations. Strategies such as contactless travel, e-tickets, and improved sanitation measures were recommended to mitigate the risk of infection and promote public transit use[41,43,50,67,74,83]. In addition, to better support this population, rigorous research is needed on solutions that promote safe and hygienic public transport travel.

    However, the uneven recovery rates between public transit/transport and private vehicles in different regions suggest a need for context-specific solutions. In areas with limited access to private vehicles, could investments in public transit infrastructure (e.g., improved ventilation systems) and real-time occupancy information displays entice riders back to public transportation? Engineering solutions could involve integrating real-time travel demand data from ride-hailing services with public transportation schedules to dynamically allocate resources during emergencies. Additionally, exploring partnerships between public and private transportation providers could lead to innovative micro transit solutions (e.g., demand-responsive buses) that cater to specific trip purposes and demographics during disruptions.

    Maintenance trips, though reduced, continued to occur during the pandemic. Effective management strategies, such as establishing outdoor sites near residences for daily necessities, were proposed to reduce the frequency of these trips and minimize infection risks[81]. Workplace trips saw the highest decline during the pandemic compared to non-workplace trips. For ride-sharing services, understanding customer willingness to pay more and considering economic factors in service cost calculations were highlighted[8,31]. It was found that customers were willing to pay upwards of 19% for better services[14]. Increasing the number of electric and cargo bikes was suggested to enhance service utility[2,35]. Surprisingly, different studies also talked about the effect on the differently abled population and their behavior shift in using different modes but they were few[82,34]. Among the 96 analyzed papers, 35 studies directly or indirectly addressed the factors influencing trip choice. This highlights the need for further research to analyze the direct and indirect factors influencing trip purpose, with a particular focus on the differently-abled population. Such research is crucial for understanding and addressing sudden changes in mobility behavior.

    In summary, this study synthesizes an extensive array of policies and recommendations, providing valuable insights into the multifaceted approaches adopted by governments and policymakers. While this research offers a comprehensive review of transportation mobility during the COVID-19 pandemic, it also provides recommendations and discusses the potential areas of focus considering future transport mobility. However, the study did not consider the extreme shifts in travel behavior at various pandemic stages and long-distance travel modes like air travel and sea travel. This needs to be addressed in future studies. Researchers should undertake a time-series analysis to evaluate how transportation mobility has evolved throughout the pandemic.

    In addition, the review process might have inadvertently favored published studies with statistically significant findings. Studies with null or negative results may not have been published, potentially skewing the overall interpretation of the data. To mitigate this, studies should include unpublished reports or grey literature (e.g., government reports, conference proceedings) in future reviews. The selection of keywords and databases used for the literature search could have limited the range of studies identified. However, this search bias was kept to a minimum by considering synonyms of the primary keywords and using Boolean operators such as AND and OR to combine the keywords. Selection bias was also reduced by utilizing pre-defined inclusion and exclusion criteria along with a rigorous screening process by four reviewers. By employing four reviewers with diverse perspectives, the influence of the reviewer's own biases on the interpretation and synthesis of the findings from the reviewed studies (also known as synthesis bias) was kept to a minimum.

    The authors confirm contribution to the paper as follows: study conception and design: Bhuiyan MRH; data collection: Basunia A, Muttaqi A, Bhuiyan MRH, Badhon FA; analysis and interpretation of results: Basunia A, Muttaqi A; draft manuscript preparation: Basunia A, Muttaqi A, Badhon FA, Bhuiyan MRH. All authors reviewed the results and approved the final version of the manuscript.

    The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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

  • Supplementary Table S1 Goji berries germplasm resources of all the continents.
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  • Cite this article

    Rehman F, Zeng S, Zhao Y, Zhao J, Qin K, et al. 2024. Preservation and innovation of goji berry germplasm resources. Medicinal Plant Biology 3: e022 doi: 10.48130/mpb-0024-0022
    Rehman F, Zeng S, Zhao Y, Zhao J, Qin K, et al. 2024. Preservation and innovation of goji berry germplasm resources. Medicinal Plant Biology 3: e022 doi: 10.48130/mpb-0024-0022

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Preservation and innovation of goji berry germplasm resources

Medicinal Plant Biology  3 Article number: e022  (2024)  |  Cite this article

Abstract: Goji is a significant edible small-fruited shrub and has been a top-grade Chinese medicinal material since ancient times. In comparison to other crop species, very little information is available on goji as an important medicinal plant in terms of genetic resource conservation and development and germplasm improvement strategies. This comprehensive study illustrates the goji species-rich diversity, geographical classification, and domestic and international germplasm repositories, including their distribution and botanical features, all of which highlight the significance of the genetic architecture of this woody tree plant and provide a thorough understanding of the global distribution of goji berry germplasms, particularly in China, which can further facilitate germplasm collection for goji breeding. We also shed light on how goji berry germplasm has been improved by utilizing conventional and modern cutting-edge technologies, future research directions on the preservation and sustainable use of germplasm resources, and advances in genomic breeding strategies. This review will facilitate the development of novel goji germplasm repositories and support the strategic development of genetic resource management by prioritizing the acquisition of underutilized goji berries and advancing ex situ conservation through the application of contemporary gene bank techniques. Critical investigations have revealed gaps that need to be filled by breeders and researchers, such as the identification of wild germplasm and comprehensive genomic approaches, which could provide a basis for rapid breeding and fully utilize the genetic potential of goji berries to improve agronomic and economic traits.

    • The genus Lycium contains more than 90 species from temperate to subtropical areas of Australia, Eurasia, Southern Africa, North and South America, and other regions of the world[1]. Among them Lycium barbarum L. (宁夏枸杞), L. chinense Mill. (中华枸杞), and L. ruthenicum Murr. (黑果枸杞), are wildly cultivated in China and commonly known as goji berry[2]. Goji berry can be used in both fresh and dried forms; moreover, dry root bark and fruit has functional importance in the medicinal industry particularly as traditional Chinese medicine (TCM). Goji berry's concentrated extracts and infusions with alcohol, utilized as components to manufacture goji beverages; in addition, it is prepared into a sauce as a kind of therapeutic nourishment[3,4]. Dried natural products are popular medicines used for therapeutic purposes and as a useful diet in Asian countries, including Thailand, Vietnam, Japan, Korea, and China[5]. Goji berries contain an abundance of important chemical compounds, such as carotenoids (lutein and zeaxanthin), betaine, Lycium barbarum polysaccharides (LBPs), and flavonoids, which are mainly involved in antioxidant activity and provide a broad range of potential benefits for anti-aging, well-being, neuroprotection, fatigue, metabolism improvement, glucose control in diabetes, immunomodulation, glaucoma, and cytoprotection[6,7]. The consumption of goji berries is largely acknowledged as a tonic that promotes health benefits and ultimately improves the immune system to fight various diseases[8]. Goji berries are also recognized as boxthorns, matrimony berries, and wolfberries. Japanese speakers refer to it as 'kuko', 'red medlar', or 'the Duke of Argyll's tea tree'. Mandarin-speaking Chinese individuals refer to it as 'gouqi' or '枸杞' while Cantonese-speaking Chinese individuals refer to it as 'keitze'. Local Koreans refer to it as 'gugija', Vietnamese people refer to it as 'củkhởi', and Thai people refer to it as 'găogèe'[3]. In East Asia, especially China, L. barbarum and L. chinense are closely related species[9]. L. chinense is widely distributed and cultivated in East and South Asia[10], whereas L. barbarum is extensively cultivated in Northwest China (Ningxia Hui Autonomous Region) and West China (Xinjiang Uygur Autonomous Region). Ningxia as 'Daodi' region of goji production, widely renowned in China. However, owing to recent market demand, goji cultivation areas have extended to new regions over different climatic zones covering from 82° E and 115° E to 30° N and 45° N. In particular, the cultivation of L. barbarum is largely extended to semi-arid temperate continental (Ningxia, Gansu, Inner Mongolia), upland continental (Qinghai), and continental arid climates (Xinjiang)[11]. However, L. chinense is notably confined to temperate monsoon climates, such as Hebei[12]. Both L. chinense and L. barbarum have a history of more than 2,000 years as TCM, with records from the Tang dynasty (1000−1400 AD)[13]. Geographical knowledge is crucial for differentiating goji fruits in terms of composition and factors such as climate, soil type, and cultivation techniques, which directly impact their biological characteristics and usage[14]. For example, growth, phytochemical content, nutritional profile, root development, and organic matter content significantly influence the overall growth and development of berry size, quality, and yield[15,16]. However, the combined effects of these factors shape the ultimate health benefits and economic value of goji berries. Despite their high nutritive value, goji berries exhibit tolerance and adaptability under salinity stress and are planted as halophyte species in Northwest China with high economic returns[17]. Goji berry production has become acclimatized in Northwest China, especially Ningxia (Zhongning County), possibly due to Zhongning's geographical position, which has the improved quality of berries in China, including fruit firmness with longer shelf life, larger berries of bright red color, and sweeter taste[17]. Historically, Qin (221−206 BC), Han (206 BC−220 AD), and Tang (618−907 AD) dynasties had initiated various irrigation projects and provided a way for water passage from the Yellow River to irrigate the farmland in Yinchuan (Ningxia), which provided favorable conditions for the goji berry production in Zhongning's areas[18]. However, during the Ming (1368−1644 AD) and Qing (1644−1912 AD) dynasties, L. barbarum production greatly increased in Zhongning, reaching approximately 200 ha[18,19]. Furthermore, goji berry domestication has been transformed over 600 years with continuous and conscious efforts by growers, including the harvesting of selective plants with large fruits[20]. Several characteristics, including non-shattering of seeds, germination, growth habit, fruit size and coloration, fruit taste (sweetness and bitterness), and fruit edibility, are involved in the domestication program of wild relatives of goji berries to improve cultivars[21]. To date, conventional approaches such as individual plant selection with distinct characteristics and hybridization have been combined to produce key cultivars of the Ningqi series (Ningqi-1 to Ningqi-10)[18,22]. Furthermore, various biotechnological techniques, such as in vitro culture of meristems, anthers, embryos, and endosperms, have been developed and can be used to induce mutations. Genetic transformation of goji berries mediated by Agrobacterium tumefaciens has been established, and the current germplasm of goji berries has been improved for various traits of interest[2325]. Goji berries have already been subjected to molecular breeding and marker-assisted selection (MAS) techniques, as traditional breeding strategies are hampered by intensive labor, cost, and time inefficiency, which impede goji berry cultivar improvement[26]. With the rapid advancement of next-generation sequencing (NGS), high-resolution genetic maps of goji berries have been constructed by integrating single-nucleotide polymorphism (SNP) markers, which provide affordable tools for QTL mapping and MAS[26,2730]. Marker-assisted breeding involves the construction of linkage maps, QTL mapping, positioning and cloning of target genes, and comparative analysis of the genome[31]. The current review provides readers with comprehensive information about the genetic diversity, geographical classification, various known cultivars, germplasm resource preservation and development, global germplasm resources, and botanical descriptions of goji berries. Additionally, we provide a thorough understanding of the goji germplasm generated through conventional breeding, as well as molecular and transgenic breeding of goji berries, with prospects for marker-assisted selection and genome editing in goji berries.

    • The discovery of L. chinense in the southern region of Hebei, China, around 100 BC, is mentioned in the initial records of goji fruits. Whereas L. barbarum was later discovered in semi-arid areas of China, including Ganzhou, Yecheng, Lanzhou, Jiuyuan, and Lingzhou, approximately 600 AC[18]. In 1960, Lycium fruit production spread to other plateau-shaped regions of China under various climatic conditions, including Qinghai, Xinjiang, Ningxia, and Inner Mongolia[11]. In China, Lycium can be found in seven distinct species and three different varieties, including L. cylindricum Kuang and A.M. Lu, L. yunnanense Kuang and A.M. Lu, and L. dasystemum Pojark (L. dasystemum var. rubricaulium), and L. truncatum Y.C. Wang, L. ruthenicum Murray, L. barbarum (L. barbarum var. auranticarpum) and L. chinense Mill. (L. chinense var. potaninii)[1] (Supplementary Table S1). Ningxia goji berries (L. barbarum) from the Northwestern Province and Ningxia Hui Autonomous Region of China have been extensively developed. It has a long flowering and fruiting season that typically lasts from May to October, and its cultivation has since extended to the central and southern regions of the country[5]. L. barbarum var. auranticarpum, a yellow-fruited goji berry that is native to Yinchuan (Ningxia). Chinese goji berries (L. chinense) are grown for medicinal, vegetable, and landscape purposes in northern China, Hebei, Shanxi, Shaanxi, Southern Gansu, and eastern China. Chinese goji berries (L. chinense var. potaninii), somewhat similar to Chinese goji, and is distributed on sunny slopes and valleys in northern Hebei, Shanxi, Shaanxi, Inner Mongolia, Ningxia, western Gansu, eastern Qinghai, and Xinjiang[18]. Yunnan goji berries thrive and spread in the Luquan and Jingdong Counties of Yunnan Province in moist sandlands or in forests at a height of 1,360 to 1,450 m[18]. Black goji berries are distributed throughout Central Asia, northern Shaanxi, Ningxia, Gansu, Qinghai, and Xinjiang. L. dasystemum var. pojarkova is commonly grown on hillsides and beaches throughout Central Asia, including Xinjiang, Gansu, and Qinghai. Another goji berry cultivar (rubricaulium) of L. dasystemum, is widely distributed in Qinghai Province. Cylindricum goji berries are mainly distributed in Xinjiang, and Truncatum goji berries are primarily found along roadsides and hillsides in Shanxi, northern Shaanxi, Inner Mongolia, and Gansu[18]. Moreover, the South African species L. ferocissimum Miers (African boxthorn) has spread to Australia and New Zealand, is involved in the growth of dense woods, and is designated as a weed in Australia's coastal and semi-arid southern regions[1,32]. L. amarum nov. L.Q. Huang, is native to Xizang in southwest China and typically found growing on rocks and alongside roads in a semi-arid, moderate climate. Additionally, it produces bitter fruits that share morphological characteristics with L. chinense, including linear lanceolate leaves, goblets with three lobes, villous rings at the base of the filament, and an adjacent corolla tube[33]. Goji fruits are grown in Europe, Africa, Australia, and North and South America. Interestingly, with an output of 50 tons in 2016, Italy became the European continent's top producer of goji, mostly in the regions of Calabria, Veneto, Puglia, Lazio, and Tuscany. Location and environmental factors, such as temperature, humidity, sunlight, and precipitation, must be known to obtain significant global goji fruit production, as they have a substantial impact on fruit quality, including fruit size and color, taste, and metabolite profile[34]. Several methods and techniques have been developed to distinguish the geographic locations of goji fruits, including near-infrared spectroscopy, principal component analysis, multivariate and linear discriminant analysis, gas chromatography coupled with mass spectroscopy, mass spectroscopy of stable isotopic ratios, stable isotopic ratios coupled with gas chromatography, and high-performance liquid chromatography[35,36].

    • Most of China's northwestern regions considered 'home to goji'. Seven distinct species and three different varieties of Lycium have been discovered in China[1]. Red goji berries (L. barbarum) are the most popular and widely consumed fruits and medicines in China[9]. In contrast, abundant germplasms of red goji berries have been generated through natural selection and hybridization and naturalized in the northwest to central parts of China[37,38]. The yellow-colored goji berry is a distinct type of L. barbarum germplasm resource among goji germplasm. The fresh fruit of yellow goji '黄色宁夏枸杞' tastes sweet and delicious and rich in trace elements including iron, manganese, and zinc content being relatively high[18]. Recent reports have revealed intra-and interspecific crosses of goji berries, which generate and preserve the highest number of individuals with distinguishing agronomic characteristics. These abundant germplasm resources can be utilized to construct high-density genetic maps of goji berries and mine genomic regions corresponding to traits of interest[26,28,29]. The 'National Goji berry Germplasm Resources Garden' was established in 1986 with an area of 13.33 hectometer (hm2) (38°3800 N, 106°90 E), Yinchuan, Ningxia Hui Autonomous region, China. After more than 30 years of dedication, the 'Ningxia Academy of Agricultural and Forestry Sciences (NXAAS)' now boasts the largest collection of goji germplasm resources along with the greatest number of genes kept in vivo, and the most significant strategic resource reserve base[18,39]. The selection criteria for germplasm collection include genetic diversity, phenotypically distinct characteristics, agronomic characteristics, and yield potential at different geographical locations[18]. The L. barbarum germplasm resource nursery of NXAAS has collected more than 2,000 inbred lines of 10 species, three variants, and unique goji germplasm resources at home and abroad, as well as more than 20,000 plants that have been kept ex situ[39]. Furthermore, these resources include 11 goji berry species in China and five species abroad, 16 new varieties, 20 farm varieties, and 350 wild goji berries (primarily from Gansu, Qinghai, Xinjiang, Ningxia, Sichuan, Hubei, Jiangsu, Shandong, and Hebei, among others), 80 new and excellent lines, and 1,700 intermediate breeding materials for the development program[18].

      Figure 1. 

      The conservation and distribution of global genetic resources of goji berries. Different colored icons show number of species across all the continents. Red and green stars indicate origin of goji berries in South America and germplasm resource garden of goji berry in (Northwest Ningxia Province) China also known as the 'home of goji', respectively. North America, more than 20, Central America, five; South America, more than 30; African continents, more than 20; Europe, six; Oceania (Australia), one; Asia, 14.

      The Jinghe County Goji Berry Germplasm Resources Center collected 36 goji strains, including 26 original varieties (lines). Qinghai University and Hebei Science and Technology Teachers College gathered goji germplasm resources[38,40]. A particular project of the State Forestry Administration, 'Introduction of the US wild goji berry germplasm resources, cultivation and utilization technology', hosted by the Gansu Academy of Forestry Sciences, introduced seven varieties of American wild goji from Arizona and other US locations, five of which were successfully propagated and grown[41]. However, the difficulties and success rates associated with growing American wild goji berries are related to problems with seed dormancy, variations in seed viability, and environmental stressors such as drought and vulnerability to pests and illnesses. Furthermore, the genetic makeup of wild goji may result in differences in berry fruiting, growth, and development, complicating conventional cultivation methods[41,42]. Wild L. americana Jacq. can be used as a source of goji germplasm for distant hybridization[42,43]. Notably, the primary areas of focus for goji germplasms in other countries, including the US, are biogeography, reproductive evolution, systematics, and bioorganic chemistry[41,42]. The American wild goji species (L. exsertum A. Gray, L. cooperii A. Gray, and L. brevipes Benth.), including 11 other domestically developed goji species and two wild species, can be split into two groups for further development of unique germplasm resources with distinct characteristics[44,45]. However, L. exsertum was introduced, and 19 unique plants were produced by the National Wolfberry Engineering Research Centre (NWERC) of NXAAS[41,46]. The description specification and data standard of goji germplasm resources and 'new plant varieties' specificity, consistency, and stability testing guidelines for goji berry were developed by the 'National Goji berry Genetic Resource Garden', and provided standard texts for further standardizing the description and records of goji germplasm resources, as well as guidelines for testing new plant varieties. Furthermore, a foundation for the directional breeding of new goji varieties was laid by initially developing a platform for collecting information on germplasm resources that covered more than 200 evaluation indicators and systematically completed a comprehensive evaluation of agronomic, quality, resistance, and other traits of more than 500 goji berry germplasm resources[18,39].

    • Temperate and subtropical climates worldwide encourage the growth of goji berries. Recent statistics on goji berry germplasm conservation reported that there are more than 90 Lycium species, along with six distinct varieties recognized throughout all continents around the globe[1] (Fig. 1, Supplementary Table S1). South America, specifically Argentina and Chile, and North America had the highest concentration of species, totaling 32 and 24, respectively (Fig. 1, Supplementary Table S1). About 24 species have been found in South Africa, 12 in Europe and Asia, two in Africa and Eurasia, one in Australia (L. australe F. Muell), and one in the Pacific Islands (L. sandwicense A. Gray)[1,47]. However, L. carolinianum Walter (Moc. and Sessé ex Dunal) C.L. Hitchc is indigenous to North America and the Pacific Islands (Fig. 1, Supplementary Table S1). Based on the examination of chloroplast DNA sequences and nuclear markers and numerous phylogenetic and biogeographic studies, it was suggested that Lycium originated in Southern and Northern America[48]. Furthermore, these investigations uncovered unique clades that were geographically matched to species found in both North and South America, suggesting that the genus may have originated in these regions before spreading worldwide[48]. A common ancestor of American origin exists for all species in southern Africa, Australia, and Eurasia. L. sandwicense distinguished itself from species in South and North America, and Australian and Eurasian species once descended from a Southern African progenitor. L. barbarum, L. chinense, and L. ruthenicum, were Eurasian species, and therefore associated with L. europaeum L., according to phylogenetic analysis[1]. The Australian species L. australe and the Southern African species L. afrum L., L. cinereum Thunb., L. ferocissimum Miers, L. pilifolium C.H. Wright, L. prunus-spinosa Dunal, L. schizocalyx C.H. Wright, and L. villosum Schinz were closely related to the Eurasian species such as L. intricatum Boiss, L. berlandieri Dunal and L. pallidum Miers[1,49,50]. Species from the Pacific Islands and North or South America were grouped together[48]. About six Lycium species, including L. ruthenicum, L. makranicum Schonebeck-Temesy, L. shawii Roem. and Schult., L. dasystemum, L. edgeworthii Miers, and L. depressum stocks have been identified in the Middle East and South Asia (mainly Pakistan). These plant species are cultivated on a small scale for food and medicinal purposes and are recognized for their distinguishing characteristics[1,51] (Fig. 1, Supplementary Table S1).

    • Plants from the Lycium genus are often thorny shrubs that grow up to 3 m tall, located in plateau areas with arid and semi-arid climates, between 700 and 2,700 m above sea level, and are referred to as 'Boxthorn or Matrimony Vine'. The term 'Boxthorn' most likely originates from the thorny nature of these shrubs; whereas, 'Matrimony Vine' refers to the cultural symbolism associated with the plants with origin in traditional Chinese culture, where goji berries are considered as a symbol of fertility, enduring relationships, and making it symbolically linked to marriage[18,19]. The root system of goji berries consists of primary, lateral, and fibrous roots. It begins with the seed radicle and develops into primary roots as it grows and matures[18]. A lateral root is considered fibrous if it consists of thin branches, whereas it is considered lateral if it has thick branches. The leaves were fleshy and narrowly linear, and the shrubs had overlapping thorny and leafy branches. Tiny flowers have a purple or blue-violet corolla and can grow alone or in clusters of up to 2 cm in length. The first body of the branch, leaf, flower, and other organs is the bud, which starts the shoot, leaves, and flowers during plant growth and development[20]. According to their developmental shape and position, goji buds are classified as normal, adventitious, leaf, or mixed[18]. Bisexual goji berries have flowers with a calyx, petals, stamens, and pistils. The goji flower consists of five stamens, yellowish oblong anthers, uneven filament length, somewhat higher or slightly lower than the stigma, and a campanulate calyx with two lobes. In addition, corolla purple-red with funnel-shaped, apex five-lobed, rarely four or six to seven lobed with elliptical shape, base with ears, superior two-chambered pistil ovary, and green filiform style[18]. Goji berries exhibit a bittersweet taste with a reddish, orange to black color. The exocarp (skin), mesocarp (pulp), and lignified endocarp around the seeds comprise the pericarp walls of the fruit. The fruit is delicate and extremely susceptible to mechanical injury because of its thin exocarp[52]. L. barbarum, L. chinense, and L. ruthenicum are the most frequently mentioned species in the literature with regard to nutritional and phytochemical composition, in vitro and in vivo biological studies, and food, cosmetic, and pharmaceutical applications[1,11,35]. Among the aforementioned species, L. ruthenicum has fruits with brownish seeds and a black-purple color. Black goji berries are perennial shrubs that are photosynthetically active and resistant to drought, cold, salinity, vigorous root tillering, low soil content, and high nutrient content. It is also useful for managing saline-alkaline land, protecting slopes, and preventing soil erosion, with a wide range of economic prospects. Black goji, also known as 'soft gold', has far greater therapeutic and physiological benefits than regular red goji berries[53,54] (Fig. 2). Red goji (L. barbarum) is 1–3 m tall with a vining growth habit. The leaf shape is narrow, oval to ovate, and goji fruit size is 2.5 cm with two or three chambers, fleshy orange to red, juicy sweet to bitter having few or up to 15 seeds per fruit[29]. Yellow-fruited goji (L. barbarum var. auranticarpum), an upright shrub with moderate vigor, thin dark-green lanceolate leaves, and a flat or inverted surface with orange to yellow color[18]. Chinese goji (L. chinense) is a densely branched shrub with single, alternating, or clustered leaves that are oblong and lanceolate. The bright red berries are 1.2 cm in size and oval in shape[29] (Fig. 2). Another variety, Chinese goji (L. chinense var. potaninii) exhibited lance-shaped leaves, sparsely ciliated corolla lobes, and vaguely auriculated basal lobes. Yunnan goji (L. yunnanense Kuang et A.M. Lu) is an erect shrub with a robust and thick trunk, narrowly ovate to lanceolate leaf blades, and berries of spherical shape with a yellowish-red color[18]. Goji dasystemum (L. dasystemum var. pojarkova), a shrub with many greyish yellow branches, lanceolate leaves, and red ovoid or oblong berries. Another cultivar of L. dasystemum var. rubricaulium goji berries differ mainly in their old brownish-red branches, and their corolla lobes are not ciliated. Goji cylindricum (L. cylindricum Kuang et al. Lu), a white or yellowish inflexible branching shrub with sessile leaf blades and a yellowish red ovoid berry. Goji truncatum (L. truncatum Y.C. Wang), a 1.5 m tall shrub with a greyish white or yellow cylindrical branch, single leaves on long shoots, and red oblong berries[18]. L. amarum has linear, lanceolate leaves, goblets with three lobes, a villous ring at the base of the filament, and an adjacent corolla tube[33]. Moreover, goji berries have an indeterminate growth habit, flowering, and continuous fruiting during the growing season and grow well in various soils[55]. Throughout the blossoming period, flowers are produced daily, and flowering can be affected or delayed by low temperatures, high humidity, or cloudy conditions. More flowering can be seen in the afternoon when the day temperature is below 18 °C, and even more in the morning when the temperature increases above 18 °C[18]. In summer, fruit berries bloom from late May to mid-July and last for the entire month of August. However, in autumn, goji fruiting begins in late September to mid-October, which is considered a less vigorous and unproductive season for goji berries[55].

      Figure 2. 

      The black (L. ruthenicum), red (L. barbarum), and Chinese goji berries (L. chinense) plants. The pictures from left to right show flower, unripe and mature fruit, and the whole plant, scale bars for goji flowers and fruits = 1 cm, scale bars for goji whole plant = 5 cm.

    • Goji berries have been domesticated for almost 2,000 years, with its origins mostly in traditional Chinese medicine. The oldest known mentions of goji berries may be found in ancient Chinese records such as the 'Shen Nong Ben Cao Jing' (Divine Farmer's Materia Medica), which was written around 200 CE and emphasizes the virtues of the berries for longevity and energy[7,18,20]. Goji berries were widely grown throughout China during the Tang Dynasty (618–907 CE), especially in Ningxia. During the Ming and Qing dynasties, goji berries were an essential part of traditional Chinese medicine and cuisine, which led to the development of varieties suitable for various climates and purposes[7,18]. It is not known how L. barbarum was naturalized in northwest China and concentrated in Zhongning County, Ningxia. It is possible that Zhongning's geographic location is one reason why the berries of L. barbarum grown in this county had the best quality in terms of fruit size, color, texture, and sweetness. The Yinchuan plains in Ningxia were irrigated with water from the 'Yellow River' as part of one of many irrigation projects in antiquity, which further improved the circumstances for goji berry cultivation in Zhongning as well as across China[18]. Moreover, growers may deliberately remove fully ripe fruits from specific trees and then isolate or store the seeds before replanting them the following year[20]. Plants that have undergone such cautious practices of selective breeding or domestication for thousands of years may have accumulated superior morphological and physiological traits from their wild ancestors[20]. Domestication may be related to several agronomically important traits such as fruit size, berry color, fruit edibility and sweetness, seed retention and germination, and growth habits. Landraces were established as a result of domestication, whereas the existence of landraces in Zhongning was not acknowledged until the 1960s and later discovered ten other landraces along with Damaye, Xiaomaye, Heyemaye, and Baitiaogouqi[56]. 'Damaye' was found in the garden of renowned goji grower 'Zhuohan Zhang' and regarded as the most reliable landrace since it consistently yields huge, uniform fruits with little variation over time[20]. The development and processing industry of goji in China has increased with the progress of hybrid breeding, selection of individuals, chromosome manipulation, biotechnological advances, and the recent use of marker-assisted selection (MAS) studies. Each step of the goji breeding support system made a substantial contribution to expanding production standards and scale.

    • High quality and yield, resilience to both biotic and abiotic stresses, and wide adaptability are desirable qualities of goji cultivars. Large fruits, dried fruits with a polysaccharide content of more than 3%, and carotene concentrations of more than 0.85 mg/kg are other indicators of superior quality. In 1973, NXAAS selected and crossed potential 'Damaye' progeny with fruit-oriented Ningxia cultivars, including Ningqi-1 to Ningqi-5. The clonal variety Ningqi-6 originated from a spontaneous hybrid seedling found in the goji berry germplasm bank of the Ningxia Forestry Research Center in 2003 and was produced by asexual expansion. A solitary plant with promising potential was found in the Ningqi-1 plantation in 2002, and NWERC used it to produce the clone variety Ningqi-7[18]. Ningqi-8 was first introduced by the Ningxia Forestry Research Institute (NFRI) in Xinjiang, Zhongning, and Inner Mongolia. NWERC chose and multiplied Ningqi-9 using unique individuals from L. barbarum crops in Inner Mongolia. The Zhongning Qixin Goji Berry Cooperative Station (ZQGCS) bred Ningqi-10 with Ningqi-5 (females) and Ningqi-4 (males). Damaye line, a clone that was selected and multiplied by potential individuals at the Zhongning goji berry management station[20]. Moreover, Ningnongqi-1 to Ningnongqi-5, Ningnongqi-8, Ningnongqi-10, Keqi-6081, and -6082 were bred at NWERC; whereas, Qixin-3 bearing distinct features of early fruiting, fast growth, stress resistance, self-compatibility, large fruit of even size, and good taste, was bred by ZQGCS. NWERC created a leafy vegetable-oriented variety (Ningqicai-1) that neither blooms nor bears fruit through interspecific hybridization crossing Ningqi-1 and local wild goji. This leafy cultivar is rich in nutrition and health care and accumulates 18 amino acids, crude protein, vitamins, a variety of essential minerals, and trace elements. Another triploid green vegetable variety, Ningqi-9, was developed by NFRI via hybridization and ploidy breeding. The autotetraploid cultivar exhibits a great capacity for branching, immature shoots that grow quickly, sensitive leaves, long blades, and good flavor, and is induced from Ningqi-1 and hybridized with Hebei goji during inbreeding[18,20]. Northeast, northwest, southwest, central, and southern China are heavily populated with wild goji berries. Numerous other variants have been grown and developed using selection and hybridization in several parts of China, including leafy vegetable varieties of goji developed by Hebei Normal University of Science and Technology, Baoqi-1, 2, Changxuan-1, Tiangjing-1, -3, and -8, and fruit-oriented varieties grown in Hebei Province. Three Jingqi-4, -5, and -7 goji cultivars were developed in Jinghe County between 2005 and 2013 by the Jinghe Goji Development Center and Xinjiang Academy of Forestry Sciences. Furthermore, the Qinghai Academy of Agricultural and Forestry Sciences developed Qingqi-1, -2, and Qingheiqi-1, clones of L. ruthenicum, between 2013 and 2015. Mengqi-1 (L. barbarum), a goji cultivar, was created in Inner Mongolia by the Horticultural Institute of the Inner Mongolia Academy of Agriculture and Animal Husbandry in 2005[18].

    • Several biotechnological methods, including meristems, anthers, embryos, endosperms, and in vitro culture materials used to induce mutations, have been established to protect goji berries against biotic and abiotic stresses. For instance, a line resistant to Fusarium graminearum was created using radiation-treated embryonic calluses cultivated in vitro[57]. Similarly, salt-tolerant plants were generated by selecting ethyl methanesulfonate (EMS)-treated embryonic calluses in the presence of NaCl[58]. Moreover, genetic transformation mediated by Agrobacterium tumefaciens has been established in goji berries[2325,59]. A successful regeneration and genetic transformation system for black goji (L. ruthenicum) was recently established, and the fruit weight loci, fw2.2, were characterized using CRISPR/Cas9 genome editing. Transgenic goji plants had nine biallelic mutations and four homozygous mutations in the fw2.2 target gene[24]. Similarly, another study successfully established a goji regeneration system and knocked out LrPDS using CRISPR/Cas9[25]. Five carotenogenic genes from red goji berries were functionally examined in transgenic tobacco (Nicotiana tabacum L.) plants as part of a study on the genetic engineering of specific genes. The results showed that all transgenic tobacco plants constitutively expressed these genes, and the amount of beta-carotene in their leaves and flowers increased[60]. These findings suggest that these genes may be employed to boost β-carotene production in red goji berries. Goji has already been subjected to molecular breeding and marker-assisted selection (MAS). Traditional breeding strategies are hampered by intensive labor, cost, and time inefficiency, which impede goji berry cultivar improvement[26]. With the rapid advancement of next-generation sequencing (NGS), high-resolution genetic mapping and single nucleotide polymorphism (SNP) markers have provided affordable tools for QTL mapping and MAS[27]. A genetic map based on the F1 population provides a reliable source for identifying the linkage between economic traits and DNA markers in perennial fruit crops[61,62]. Recently, several significantly important genetic loci, including stable QTLs corresponding to fruit quality and size/weight-related traits, have been identified in goji berries using ultra-dense linkage mapping[29,63].

      Highly heterozygous mapping populations were successfully developed by interspecific crosses, and F1 individuals were determined using a pseudo-test cross approach, which is widely applicable to perennial trees and forest herbs[64]. Therefore, the first high-density genetic map of L. barbarum was based on an intraspecific F1 population using ddRAD-seq[28] and a goji berry SNP-based genetic map using SLAF-seq based on interspecific F1 populations[28,29]. Next-generation sequencing (NGS)-based resequencing genetic analysis was performed to construct an ultra-dense high-resolution genetic map of goji berries using 200 potential individuals derived from the F1 population (L. barbarum var. Ningqi-1 × L. yunnanense var. Yunnan goji). A high-density linkage map was established with a total genetic length of 2,122.24 cM along with average inter-marker distance of 0.25 cM and 8,507 SNPs. Furthermore, QTL mapping analysis detected 25 stable QTLs in different linkage groups corresponding to agronomic traits, with maximum LOD values of up to 19.37 and PVE percentages of 51.9%. Eighty-two differentially expressed genes (DEGs) underlying these stable QTLs were identified using RNA sequencing analysis[30]. A recent report on goji berry genome establishment provides strong evidence for the evolution, diversification, and distribution patterns of goji berries worldwide. This study analyzed the genomes of L. barbarum and other 12 perennial indigenous species and discovered new gene families with their expansion and contraction within Solanaceae. Moreover, assimilation with other genomes provides strong evidence in favor of a whole-genome triplication-WGT event that occurred soon after the split between Solanaceae and Convolvulaceae and is shared by all previously sequenced solanaceous plants[65]. Together, these collective findings could provide a solid basis for the genetic breeding of goji berries to further improve domestication and crop improvement, corresponding to genetic architecture and yield enhancement.

    • Goji berries are becoming more popular due to their significant medicinal and nutraceutical value. It has been learned through literature goji berries native to South and North America became naturalized in northwest China, where domestication led to the emergence of a significant number of potential landraces. It is necessary to investigate the genetic potential of other Lycium species, notably those from the New World and Africa, with a stronger emphasis on fruit characteristics and important chemical compounds, such as zeaxanthin and antioxidants[18]. As predicted, new cultivars with more desirable features, including leaf-vegetable-oriented cultivars of goji berries, could be generated for industrial production using other species[66]. The canvas of major breeding goals should be expanded to disease and pest resistance, valuable chemical constituents, leaf-related traits, early flowering, plant architecture, and geographical adaptability, instead of fruit- and yield-related traits. However, by focusing on particular genes linked to pest or disease resistance and genes of interest, both conventional and modern breeding techniques such as hybridization, marker-assisted breeding, and CRISPR/Cas9 gene editing tools offer precise ways to enhance resistance corresponding to the desired traits[18,67]. Research must concentrate on the long fruit, thick flesh, hard skin, sweet and excellent flavors, and other characteristics of the fresh-fruit goji berry industry. Owing to the scarcity of resources, the genetic composition of cross-pollinated perennial goji berry plants is extremely complex[18]. Currently, the most commercialized varieties of Chinese goji berries are the Ningxia and black-fruited varieties, with Ningxia goji berry cultivars being the most extensively grown. These varieties lack genetic diversity and have a single genetic base, making it difficult to produce improved goji berry variants. The genetic backgrounds of many resources are unclear, and there are few comprehensive studies on the genetic mechanisms underlying the biological characteristics of these resources. These limitations hinder the development and utilization of specific resources and breeding of new goji berry varieties. Nonetheless, it is imperative to enhance the recognition and evaluation of goji berry germplasm resources and broaden theoretical research on the genetics of goji berries[20,39]. Resources from the germplasm of the goji berry plant serve as both the raw material for germplasm production and the source of genes required for further genetic improvement. To reduce the detrimental effects on local goji berry germplasm resources, building projects, such as new and renovated farmland, water conservation, and transportation, the distribution region, especially the existing sample stations, should be dynamically monitored. Increasing public understanding of science, lessening the severity of naturally scattered population picking, and maintaining the population's relative stability[39]. The extent of resource collection is limited to the national level, and vast categories of domestic wolfberry germplasm resources have been acquired in great quantities. The introduction and collection of foreign wolfberry resources have occurred relatively infrequently. Ex situ preservation is the main technique used to preserve resources, whereas in situ preservation and seed preservation techniques are practically non-existent. Resource availability and quality boost resource banks create comprehensive and extensive resource archives, identify and analyze morphology and molecular biology, and define taxonomic status and genetic history. Develop a comprehensive germplasm resource nursery to lay the groundwork for the preservation, study, advancement, and use of germplasm resources. The multigeneration asexual reproduction of clones of elite varieties such as Ningqi-1 and Ningqi-7 degrades the outstanding qualities of the improved varieties and reduces yield; thus, the improved varieties must be immediately rejuvenated and purified[18]. To satisfy the demands of the ongoing development of traditional Chinese medicine for human health, new varieties of L. barbarum will be generated with high yields, excellent quality, climate resilience, and adaptation to processing or mechanized operations. Fundamental studies on the collection and preservation of goji berry resources, classification and identification, resource chemistry, and resource physiology are limited in resource-based research owing to a lack of professional knowledge. Currently, in vitro preservation is the primary method for resource preservation. More resource collection necessitates the use of in vivo methods and seed preservation, both of which require specific facilities[18,39].

      In light of this, the collection of domestic and exotic goji germplasm resources should be strengthened, particularly through international cooperation, which can expand goji berry resources and significantly accelerate their innovation and utilization. Establishing protection points or protected areas in resource distribution areas, strictly forbidding illegal and excessive digging of wild goji berry plants, encouraging artificial domestication and seedling breeding of wild goji berries, and creating regulations for the protection of wild goji berries are some of the key aspects that can be employed[39]. Ex situ protection should be employed for goji berries that are threatened by extinction or whose habitats have been destroyed. This can be achieved by seed propagation and digging live plants in the field. Goji berry resource innovation and use should be accelerated and expanded by strengthening the identification methods and evaluation of resources using distant hybridization to produce new germplasms, collecting and processing data based on the characteristics of resources to create databases, and establishing a shared technology platform for a variety of resource uses[39,41]. The genetic material required to investigate genetic traits should be created using high-purity inbred lines, hybridization, and backcross offspring. Additionally, understanding the biological aspects of goji berry reproduction is essential, as plants primarily pass on genetic information to the next generation through reproduction[20,56]. The goji leaf, sometimes referred to as 'Tianjing grass', is a prominent medicinal plant, useful vegetable, and great tea, encouraging the development of goji leaves for use as a vegetable and medication[66]. L. chinense, a wild type goji berry with bigger, oblong leaves, might be regarded as a vegetable species of the Lycium genus, as well as Ningqicai-1 and Ningqi-9 leaf vegetable-oriented varieties of goji berries successfully cultivated in Ningxia province[18]. Interestingly, significant changes in leaf size were observed among the F1 individuals of interspecific populations, particularly in terms of leaf length, diameter, and area, which could be important crossing materials for generating vegetable-oriented cultivars of goji berries[26,29].

    • Although traditional methods of breeding goji berries are, to some extent, effective, there is a need to advance the use of marker-assisted breeding (MAB) for goji berries to incorporate effective production and development under genetic breeding. Transgenic breeding involves genetic alterations in crop plants. On the other hand, transgenic breeding offers a rapid method for combining genes from various genetic backgrounds[59,68]. The breeding of elite cultivars, as well as the cultivation and preservation of new genetic resources, could thus be facilitated by research on various attributes using MAB. Abundant worldwide resources of Lycium can offer a wide range of germplasm resources for the cultivation and breeding of goji berries[1]. Crossing distinctive plants yields offspring with considerable genetic variants, such as varying fruit colors, flower terminal shoots, and larger fruits with multi-locule formation, compared to typical small goji berries bearing one or two locule numbers, which forms the basis of marker-assisted breeding. The production of new germplasms with advanced breeding objectives may be facilitated by these genetic modifications[68]. Studies on the genetic resources of goji berries have lagged behind those of other Solanaceae crops, such as tomato, potato, and pepper, in terms of systematic and in-depth examination of genomic analysis and a varied range of traits[56]. Genomic regions or quantitative trait loci (QTLs) identified through genotyping and phenotyping offer a wealth of DNA polymorphisms and raise the possibility of selecting elite cultivars coupled with a particular trait of interest[69]. The fruit size of goji berries differs greatly; for example, the fruit of L. barbarum is approximately 2 cm in diameter, with two to three locules in the indigenous cultivars, which is slightly larger than the fruits of L. chinense and L. ruthenicum. Remarkably, substantial variations were observed in the locule number of the Ningqi series cultivars (Ningqi-1, -5), Zhongkeluchuan-1 (ZKLC1), and offspring of the interspecific hybrid F1 population, with an average locule number of 2.564[29] (Fig. 3).

      Figure 3. 

      Red goji berries (L. barbarum var. ZKLC1 and Ningqi-1, 5), black goji berries (L. ruthenicum), and locule number variations in different cultivars and wild germplasms, scale bars = 1 cm.

      It is assumed that larger fruit size cultivars with greater locule numbers in the goji berry industry will be a major breakthrough in expanding cultivation and production. Several major QTL/genes are responsible for fruit size variations in tomatoes, including LOCULE NUMBER (LC), FASCIATED (FAS), and CLAVATA3 (CLV3), which increase the locule number, fruit diameter, and eventually fruit size[67,70,71]. Topless/Topless-related (TPL/TPR) proteins are involved in a number of signalling pathways in higher plants, including biotic stress, meristem maintenance, floral induction, hormone-signaling pathways, and circadian oscillator mechanisms[72]. SlTPL1 and SlTPL4 were found to be highly expressed in vegetative tissues (roots, stems, and leaves) as well as in developing flowers (buds and anthesis), but with reduced expression in ripening fruits. In contrast, SlTPL3 expression is constant and high during fruit ripening[72]. SlTPL3 and SlWUS control locule development in tomatoes and SlTPL3 RNAi lines have shown that an increase in carpel number is the primary driver of multiple locule formation[73]. Likewise, mechanical harvesting is challenging because of the indeterminate growth habit of goji berries, with the simultaneous existence of ripe, immature fruits and blooms on the same branch[74]. Goji berry harvesting in China now makes extensive use of labor, which leads to labor-intensive and costly picking. New cultivars with determinate growth habits and synchronous fruiting are needed to overcome the difficulties of mechanical harvesting of goji berries[75]. The tomato self-pruning (SP) homologue gene of centroradialis (CEN) from Antirrhinum, which has determinate growth characteristics, has been found in separate studies[76,77]. Several studies have employed CRISPR/Cas9 gene editing to disrupt the SP gene in tomato and other solanaceous crops, leading to a determinate growth pattern with terminal flowers at the top of the branch[7880]. Interestingly, significant numbers of flower terminal and non-terminal plants have been collected for transcriptomic data analysis to identify candidate genes for the regulation of terminal and early flowering, and efforts are already underway to knock out SP-like genes to generate determinate growth habits with terminal-flowering shoots under efficient genetic improvement of goji berries (unpublished). Nevertheless, the direct breeding of compatible red goji berry variations, functional characterization of potential genes, construction of genetic maps, and development of molecular markers all contribute to an insightful theoretical and practical foundation.

    • The ultimate goal of resource studies is to hasten variety breeding and enhance the quality and quantity of goji berries. It is becoming increasingly crucial to protect the genetic diversity of goji berries owing to their rising global demand. This diversity must be preserved, and effective conservation efforts combining in situ and ex situ methods are essential to lay the groundwork for subsequent breeding initiatives. Recently, it has been witnessed that goji breeding has made enormous strides in China, the development of breeding technology has advanced significantly. Goji berry has an abundance of resources, and through germplasm innovation and conventional methods like distant hybridization, new germplasms are developed; in addition, the genetic basis for breeding is expanded under next generation sequencing approaches, and the breakthrough in goji breeding is achieved. The value of germplasm resources is becoming increasingly evident in light of the rapid advancement of science and technology, as well as various challenges. The primary objective of agricultural development is to expedite the collection, development, and usage of genetic resources while simultaneously offering technical assistance for speeding up rural rehabilitation. The genomic studies including goji berry domestication and genetic breeding would help in comprehending the potential of goji berry's extensive genetic background and enhancing the current goji berry cultivars including disease resistance, fruit quality and acclimatization using CRISPR-based gene editing system. By adopting these strategies, goji berry cultivation may become more resilient and sustainable, ensuring a steady output and protecting the genetic resources necessary for future breeding endeavors. However, breeders and legislators are required to bridge the gap between traditional methods of resource conservation and state-of-the-art breeding techniques, interdisciplinary support, and the proper utilization of goji berry genetic potential for sustainable agriculture and food security.

    • The authors confirm contribution to the paper as follows: conceptualization, visualization, writing - review & editing: Rehman F, Wang Y, Huang H, Zeng S, Yang C; writing - manuscript preparation: Rehman F; goji germplasm resources data: Zhao J, Zhao Y, Qin K, Rehman F, Wang Y; investigation and formal analysis: Wang Y, Huang H, Rehman F, Zeng S, Yang C; supervision, funding acquisition, project administration: Wang Y. All authors have reviewed the final version and agreed for the submission.

    • Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

      • This research was supported by the National Natural Science Foundation of China (Grant No. 32170389), Guangdong Science and Technology Plan Project (Grant No. 2023B1212060046), and the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA24030502).

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

      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. 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/.
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    Rehman F, Zeng S, Zhao Y, Zhao J, Qin K, et al. 2024. Preservation and innovation of goji berry germplasm resources. Medicinal Plant Biology 3: e022 doi: 10.48130/mpb-0024-0022
    Rehman F, Zeng S, Zhao Y, Zhao J, Qin K, et al. 2024. Preservation and innovation of goji berry germplasm resources. Medicinal Plant Biology 3: e022 doi: 10.48130/mpb-0024-0022

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