Next Article in Journal
The Impact of Socialized Agricultural Machinery Services on the Labor Transfer of Maize Growers
Previous Article in Journal
Sustainable Production of Maize with Grass and Pigeon Pea Intercropping
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022

State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, The Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(6), 1248; https://doi.org/10.3390/agriculture13061248
Submission received: 23 April 2023 / Revised: 29 May 2023 / Accepted: 5 June 2023 / Published: 14 June 2023
(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)

Abstract

:
The change in agricultural soil organic carbon (SOC) at a global scale has a great impact on the soil quality, crop yields, and greenhouse gas concentration in the atmosphere. Plant-derived C input into soil is an effective strategy to increase the SOC; meanwhile, it promotes SOC mineralization. The SOC dynamics after plant-derived C input have received widespread attention in the past 20 years. This bibliometric study was performed to identify the basic characteristics, research output, and knowledge base as well as to understand the research trends and key topics of agricultural SOC mineralization. We collected data from the Web of Science Core Collection databases, with dates ranging from 2000 to 2022. The parameter calculated from the default indicators of bibliometric software tools was used to indicate the contribution of the journal/author/institution/countries. The activity and attractive index were calculated separately to evaluate the relative effort and impact made by a country. The results showed that: (1) the number of articles increased gradually during 2000–2010 and thereafter sharply increased; (2) Soil Biology & Biochemistry was the most representative journal, and agriculture was the most popular subject category; (3) the most productive institution was the Chinese Academy of Sciences, which is based China and cooperates closely with other institutions; (4) although the number of articles from China was the largest, both the cited frequency and activity index were much lower for China than for the USA, which had the highest citation and centrality among countries; and (5) the studies involving agricultural SOC mineralization have primarily investigated the effect of exogenous C and nutrient addition, as well as biotic processes, especially the microbial process. We concluded that there was an increasing trend in research on agricultural SOC mineralization, with a focus on the interaction between SOC and nutrient/microbial communities. The physical processes, such as the association of minerals and occlusion of aggregate and pores, were paid less attention relative to biotic processes despite their importance in SOC mineralization. Through an in-depth analysis of agricultural SOC mineralization research, this study provides a better understanding of development trends that have emerged in this field over the past 22 years. In future studies, more attention should be paid to the physical processes to understand the physical protection mechanism of agricultural SOC mineralization.

1. Introduction

Soil organic carbon (SOC) is the largest C pool in the terrestrial ecosystem [1]. It plays a critical role in soil quality, fertility, and greenhouse gas emissions [2,3]. A slight change in SOC turnover at a global scale would have the potential to influence food and climate security [4]. Labile organic C input (e.g., plant litter or exudates) into soil stimulates the decomposition of SOC, known as the priming effect [5]. The straw return is considered an effective way to increase the SOC; meanwhile, it can induce SOC decomposition in the agricultural ecosystem [6]. An agricultural SOC change has an important impact on the terrestrial carbon cycle [6]. Therefore, SOC mineralization in the agricultural ecosystem has been paid much attention by related researchers around the world [7,8].
The studies investigating SOC mineralization have been increasing since the priming effect was observed by Löhnis (1926), and 70% of priming effect studies have been performed over the last ten years [9]. These studies vary in experimental conditions, soil properties, and the quality and quantity of input C, leading to some inconsistent or incomparable results. Some reviews have been performed to integrate the results of the large body of SOC dynamic studies. For the priming effect, Kuzyakov et al. (2000) overviewed the different potential mechanisms, among which the changes in microbial activity and biomass were the most important [5]. Blagodatskaya et al. (2008) found that the magnitude of the priming effect depended on the quantity and quality of exogenous C, microbial biomass, community composition, enzyme activities, soil pH, and aggregate size [10]. The latest study underlined the abiotic mechanisms controlling SOC mineralization and proposed different scenarios to describe the influence of SOC decomposition on ecosystem services under climate change conditions [9]. Overall, the biotic activities and abiotic processes play an important role in agricultural SOC change [11,12]. Straw input can effectively promote the SOC content, improving the soil quality and crop yield in an agricultural ecosystem. High-throughput technology has been suggested for use in quantitatively estimating the microbial role in the soil C cycle [13]. These reviews can only synthesize the knowledge regarding SOC mineralization for some specific aspects. However, the studies investigating agricultural SOC mineralization are multi-disciplinary, including agricultural, environmental, ecological, and soil science, as well as geosciences, and its development among a large volume of publications has not been quantitatively analyzed.
Bibliometric analysis can qualitatively and quantitatively analyze the bibliometric data (e.g., units of publications and citations) based on mathematical statistics, revealing evolutionary nuances and emerging areas in a specific discipline or field [14]. Scientometrics citation analysis combined with information visualization technology provides researchers with an understanding of the knowledge within a field. A comprehensive overview of the studies involving a certain field can be created by describing the knowledge base, characteristics, and trends after bibliometric analysis. This technique has been widely used in recent years [15]. For example, Pan et al. (2021) conducted a study to investigate the research trends in soil nutrients, analyzing the leading journals, institutions, and countries, as well as identifying the hot topics in this field. Mao et al. (2018) investigated the research trends in contaminated soil remediation and identified the hotspots and developing trends, providing guidance for future research directions [16,17].
This study uses bibliometric analysis and visualization technology to (1) identify the basic characteristics of the literature, such as the number of articles and citations, research subject categories, and representative journals; (2) identify the research power of this field, such as representative countries, institutions, and authors; (3) uncover the research topics and changing trends in research hotspots over time; and (4) identify potential research directions for future research. The results provide a comprehensive insight into the agricultural SOC mineralization for researchers, which is important for the development of their study.

2. Materials and Methods

2.1. Data Collection

The literature was retrieved from the Web of Science Core Collection, which includes more than 12,000 influential academic journals and is widely considered an important database by global researchers. The Web of Science Core Collection is the world’s leading interdisciplinary citation database and can provide the comprehensive data information required by bibliometrics analysis [18]. More importantly, the Web of Science Core Collection covers the authoritative international academic journals that publish literature involving the agricultural SOC dynamic. The indexed keywords and their combination in the title or abstract were “soil organic carbon or soil organic matter”, “mineralization or decomposition or respiration or greenhouse gas”, “input or addition or application”, and “agriculture or cropland or farmland”. The period considered was from January 2000 to November 2022, during which agricultural SOC mineralization received attention from many researchers, and the involving studies were constantly expanding. Literature was included according to the following criteria: (1) the language was English; (2) the study had reported SOC mineralization in an agricultural ecosystem; (3) the literature type was an article; meetings, books and book chapters, online publications, reports, patents, thesis dissertations, abstracts, clinical trials, revisions, and other unspecified types of literature were excluded. A total of 3328 English articles were included from the Web of Science Core Collection and were exported as plain text files in the format of “full record and cited references” for bibliometric analysis (Figure 1).

2.2. Data Analysis and Visualization

Academic cooperations play a critical role in the development of a research field. The network can show the cooperation relationship between countries/institutions/authors. The keyword analysis, including co-occurrence, cluster, and bursting analysis, can aid in identifying the hot topics and developments of a field. The cooccurrence network can show the relationships between topics and quantify the main research hotpots but may be complex and overlayed among nodes. Thus, clustering analysis was used to simplify the complex network into the relationship among several groups. Bursting keywords are those that show a sharp increase in frequency, indicating topics that were paid particular attention during a specific period and can be found using bursting detection. The bursting keywords can be used to identify research frontiers and predict research trends.
CiteSpace is free software and can be used to analyze the information within the literature, presenting the structure and distribution of the knowledge in a field via bibliometric maps [19]. We used CiteSpace (6.1 version) to remove the duplicates and then analyze the network of countries, institutions and authors, as well as the co-occurrence, cluster and burst analysis of keywords. The parameters in CiteSpace were set as follows: (1) time slicing from 1900 to 2022, years per slice = 1; (2) term source = title, abstract, author keywords; (3) node type = country or institution or author or keyword; (4) the selection uses a modified g-index in each slice. We can include or exclude some nodes through changing the proportional factor. In this study, the proportional factor was set as 5 in the collaboration or co-occurrence analysis to clarify the relationships between nodes in the network. Other parameters, such as links, were set to default. In the network, the size of the node reflects the frequencies of co-occurrence; and the links indicate the co-occurrence relationships between countries/institutions/author. The color of the node and line vary from gray to red as time passes from 2002 to 2021. The centrality was used as an indicator of the importance of countries/institutions/author in the studies of agricultural SOC mineralization. An institute or author is important and has a great influence on the development of a research field when the centrality is greater than 1.
VOSviewer is another free computer program widely used for bibliometric maps [20]. We used VOSviewer (1.6.18 version) to analyze the co-occurrence of Journal, which cannot be analyzed by the CiteSpace version we used. The parameters in the VOSviewer were set as follows: (1) citation: sources; (2) the counting method was set to full counting; (3) the minimum number of journals per document was set at 20 to ensure the clarity of nodes and links. The other parameters were set to default. In the network of journals, a bigger node represents a more important journal, the color represents the cluster of journals, and the lines indicate the link between journals. The total link strength indicates the co-occurrence frequency between one and another journal.
The cooperation and co-occurrence network of countries, institutions and authors, as well as the timeline of keywords, were plotted by CiteSpace. The cooccurrence network of journals was plotted by VOSviewer. Both software tools can present the amount of literature and number of citations from each country. We plotted the graph of the number of articles and the frequency of citations using Origin 2019 and listed the key information of the top 10 items (subject, journal, country, institute and author) in the tables.
To estimate the relative effort and influence made by a country in a given year, we calculated the activity index (AI) (Equation (1)) and the attractive index (AAI) (Equation (2)) [21]. A value of 1 for either index indicates that the research effort or academic influence of a particular country is equivalent to the global average level. An AI above or below 1 indicates that the research effort of a country is higher or lower than the global average research effort. An AAI above or below 1 indicates that the number of citations attracted by a country is higher or lower than the global average citation.
AI = P / P TP / TP
AAI = C / C TC / TC
where AI and AAI indicate the activity and attractive index of a country, respectively, in a given year. P and C represent the number of articles and citation frequency of a country in a year. TP and TC indicate the global number of articles and citation frequency in a year. ∑P and ∑C indicate the total number of articles and cited frequency in a country during 2000–2022. ∑TP and ∑TC indicate the global number of articles and citation frequency during 2000–2022.

3. Results and Discussion

3.1. Quantity of Articles and Citations

The number of English articles on agricultural SOC mineralization was 3328, with an average of 142 per year over the last 22 years based on the Web of Science Core collection (Figure 2). The number of articles increased steadily from 2000 to 2022, with a higher increase rate during 2000–2003 (the average rate = 34%) than during 2011–2021 (the average rate = 9%), while a slight change was observed during 2004–2012. These results suggest that studies investigating SOC mineralization in the agricultural ecosystem are currently in their development stage and have great potential. The number of articles exceeded 200 per year for the first time in 2018. A potential reason could be the pandemic because the pandemic began in 2019, particularly in China, which is one of the countries that contributes the most articles.
The frequency of citations per year changed to a different extent and the cumulative cited frequency was 97,002 over the last 22 years, with a maximum of 5836 (in 2007) and a minimum of 323 (in 2022) (Figure 2). The number of citations sharply decreased after 2017, although that of articles increased. The cited frequency of an article is related to its topic, the time of publication, and the influence of the journal. The decrease in citation frequency after 2017 was most likely attributed to two factors: (1) the delay in citation relative to publication and (2) an increased number of published articles during the COVID-19 pandemic between 2019–2022. These results suggest that the number of articles combined with their cited frequency can serve as a useful indicator of the development of a certain field.

3.2. Subject Categories Analysis

The top 10 subjects were screened and presented in Figure 3. During the selected period (2000–2022), the top three subjects were agriculture, environmental science ecology, and plant sciences, accounting for 23%, 20%, and 16% of the articles, respectively. The remaining seven subjects were chemistry, meteorology atmospheric sciences, biodiversity conservation, science technology other topics, business economics, public environmental occupational health, and biochemistry molecular biology. These results indicate that agricultural SOC mineralization has captured the attention of researchers from various disciplines and fields. Notably, the order of the subjects was not immutable. Agriculture, environmental science ecology, plant science, and chemistry were always among the top four, with the same order between subjects over the past two decades. Biochemistry molecular biology ranked 5th in the first ten years but 10th in the second ten years. Nutrition dietetics and forest only appeared from 2000 to 2010, and meteorology, atmospheric sciences, and business economics only from 2011 to 2022.
The number of articles related to a specific subject indicates the research trend involving agricultural SOC mineralization across different disciplines. Agriculture, environmental science ecology, and plant sciences have paid considerable attention to the research of agricultural SOC mineralization compared to other subjects in the top 10 because of the potential impacts of the SOC dynamic on environmental quality and plant growth [22]. Some new subjects, such as microbiology and business economics, have also focused on agricultural SOC mineralization, likely due to advancements in measuring microbial community. For example, DAN-based stable isotope probing and metagenome help to understand the microbial process involving in SOC dynamic [23]. These changes in subjects over the last 22 years underscore the need for interdisciplinary efforts to improve the research in agricultural SOC mineralization.

3.3. The Related Journal Analysis

The articles related to agricultural SOC mineralization appeared in 411 journals, and the top 10 were listed in Table 1 based on the number of articles. Soil Biology & Biochemistry ranked first in the number of articles, total link strength and citations, while Science of the Total Environment ranked first in updated and average impact factor in five years and CiteScore. Taken together, considering the total link strength, citation, and impact factor, Soil Biology & Biochemistry plays an important role in scientific communication related to agricultural SOC mineralization.
The citation-source network consists of 11 clusters and 37 notes (Figure 4). Soil Biology & Biochemistry acted as an intermediary that linked 10 journals such as Soil Science Society of American; Soil & Tillage Research, and Agriculture, Ecosystems & Environment. Soil & Tillage Research linked seven journals such as Field Crops Research and the Journal of Environmental Management and Pedosphere, with a primary focus on the effects of soil tillage on SOC dynamic in the field. The influential factor (IF) of a journal represents its role and status in certain scientific communication and were shown in Table 1. Thus, taken together, Soil Biology & Biochemistry is the most important journal in the field of agricultural SOC mineralization. The reason is that Soil Biology & Biochemistry published articles describing and elucidating biological processes occurring in the soil. In addition, it is an established journal that is widely recognized by experts in soil science worldwide.

3.4. The Development of Agricultural SOC Mineralization Research in the Top 10 Countries

There were 129 countries involved in the study involving agricultural SOC mineralization. The top 10 countries (the corresponding number of articles in the brackets) were China (820), the USA (659), Germany (311), Australia (226), India (209), Canada (205), Spain (160), France (151), Brazil (136) and Italy (131) (Figure 5a). The number of articles from China and the USA accounted for 45% of the number of total articles from all countries. China published more articles but had fewer citations than the USA, which had the highest average citation frequency per article in the last 22 years (Figure 5b). These results indicated the USA has a greater academic influence on the world due to its early development of soil science and its numerous high-level institutions and researchers. In contrast with the USA, China is a developing country, in which institutions and researchers face high economic and work pressure. The pressure may limit the investment of money or energy into research, leading to lower academic output and influence. These results also indicate that the studies involving agricultural SOC mineralization mainly concentrate in Asia, Europe, America, and Oceania.
The number of articles from the top 10 countries increased over time during the last 22 years (Figure 5c,d). The USA was always the largest source of articles before 2015, after which China was. The number of articles per year from China ranged from 2 to 18 before 2014, thereafter sharply increased, ranging from 32 to 137. China became the country that published the most articles at the fastest rate after 2015. The reasons for this are mainly as follows: (1) the greater financial and researcher’s support in China, (2) the increased number of researchers and graduate students in China, (e.g., 326,687 Ph.D. in 2015 vs. 460,000 Ph.D. in 2020 in schools), (3) the creation of new international journals in the last 10 years. Meanwhile, the number of articles published by the remaining five countries in the top 10 fluctuated over time but showed and increasing trend overall.
The activity and attractive indexes changed over time and across countries, ranging from 0 to 2 except the attractive index of Braza in 2000 and 2001 year and of Canada in 2000 and 2001 year (Figure 6). Among the top 10 countries, the two indexes increased continuously over time only in China, with a similar rate between the two indexes, and were greater than 1 only after the 2016. The two indexes of the other nine countries changed to a different extent over time, ranging from 0 to 1. The activity index of China, Australia, Spain, and Italy was higher than their attractive indexes in most years (more than 11 years). Conversely, the activity index of India, France, and Brazil was higher than their attractive indexes in 11 years, while that of the USA, Germany, Canada was lower than their attractive indexes only in several years (less than 11 years). Moreover, the activity index of the USA fluctuated and was greater than 1 during 2000–2004 and in 2005, 2006, 2010, and 2011. The attractive index of the USA was always greater than 1 during 2001–2018 but less than 1 during 2018–2022.

3.5. The Academic Cooperation Relationship between Countries or Institutes

The cooperation network of countries consisted of 92 nodes and 612 links (Figure 7a). Among all countries, the USA and Germany had the highest centrality (0.24); followed by China (0.19); Australia (0.14); England (0.12); Switzerland (0.10); Italy, the Netherlands and Japan (0.08); and Belgium (0.07). China, which was the largest source of articles, had cooperated with 41 countries and had the closest relationship with Japan. The USA had established close cooperation with almost all the countries such as China, Germany, India, the Netherlands, and Russia. These results indicated that China contributed the most to the number of articles but had less influence in collaborative networks.
For the institutions, the Chinese Academy of Sciences published the most articles (395), accounting for 12.0% of the total amount of articles (Table 2). The other institutions in the top 10 were listed in Table 2. Five institutions in the top 10 were from China and published 19.7% of the number of articles, while three institutions were from the USA, publishing 4.7% of the number of articles. The remaining institution was from Spain, only publishing 1.2% of the number of articles.
The network of institutions consisted of 195 nodes and 416 links (Figure 7b). The first principal institution was led by the Chinese Academy of Sciences, with the highest centrality (0.43) among the top 10 productive institutions. The top 10 institutions in terms of centrality were the Chinese Academy of Sciences, Agriculture & Agri-Food Canada, INRA, Colorado State University, China Agricultural University, Rothamsted Research, Bangor University, Aberdeen University, and Katholieke University Leuven. Zhejiang University ranked in the top 10 in the number of articles, but its centrality was lower than some institutes that produced more articles such as Colorado State University. The Chinese Academy of Sciences cooperated with many institutions, such as the University of California Davis and Colorado in the USA, the University of Adelaide and Queensland in Australia, the University of Paris Saclay in Paris, and Peaking University in China.

3.6. Authors Analysis and Their Academic Cooperation

A total of 12,977 authors participated in the study involving agricultural SOC mineralization. The top 10 authors in the number of articles were listed in Table 3. Ge Tida, Wu Jingshui, and Zhu Zhenke were from China, with Ge Tida working at the University of Ningbo and the latter two authors at the University of Chinese Academy of Sciences. Kuzyakov Yakov and Joergensen Rainer Georg came from the University of Göttingen and Kassel in Germany. Six John and Castellano Michael J. were from the University of Colorado State and Iowa State in the USA. OK Yong Silk and Jones Davey L. were from the University of Sejong in South Korea and the University of Western Australia in Australia, respectively.
The network of authors consisted of 245 nodes and 168 collaborative links. Among the top 10 most productive authors (Table 3), Yuzyakov Yakov and Chang Scott X. ranked in the top two in terms of centrality. The main cooperation of authors was mainly after 2015 (Figure 8). Kuzyakov Yakov had the strongest cooperation relationship with 20 authors such as Gunina Anna, Blagodatskaya Evgenia, and Wu Jingshui. Their cooperating work mainly focused on the effect of cropping systems and land use and C input on SOC stock [24,25], the processes of SOC formation and transformation, and the decomposition of SOC following organic C input [10,26,27]. Both Ge Tida and Wu Jinshui cooperated with Zhu Zhenke, Guggenberger Georg, and Kuzyakov Yakov, mainly focusing on the SOC mineralization and sequestration in the paddy and the microbial and abiotic mechanisms [28,29,30]. Chang Scott X. showed no links in the network, focusing on the soil N mineralization and its relationship with SOC change and the effect of biochar amendment on SOC storage [31,32,33].

3.7. Keywords Co-Occurrence, Clusters, and Evolution Analysis

There are 10,677 keywords occurring in the articles involving agricultural SOC mineralization, among which 112 keywords had a frequency of more than 16. The top 10 keywords in terms of the occurrence frequency were organic matter (760), nitrogen (689), decomposition (671), carbon (607), microbial biome (587), mineralization (538), dynamics (492), management (473), matter (330), and sequestration (300).
The top five clusters in terms of size are listed in Table 4. The main keywords included in the cluster of “Carbon sequestration” were organic matter, soil enzyme activity, nitrogen use efficiency, mineralization rate, and soil fertility. In this cluster, researchers mainly focused on the effect of nutrition and C addition on SOC mineralization and microbial activity. Nutrition addition has been demonstrated to increase the SOC during long-term field experiments [34]. Moreover, split N and P application has been demonstrated to decrease SOC mineralization compared with full N and P application using an incubation experiment [35]. The effect of nutrient addition on SOC mineralization was related to the increased microbial biomass, enzyme activity, and microbial use efficiency [36,37]. The main keywords in the “soil organic carbon” cluster were organic carbon, microbial biomass, carbon isotopes, soil constraints, and N uptake. In this cluster, researchers mainly investigated how soil stoichiometry influences SOC change through a changing microbial biomass and N limitation using the stable isotope method [38,39]. The SOC concentration and pH were the key constraining factors of SOC turnover [40] because pH may regulate the soil microbial community composition and the SOC was an important C and nutrient resource of microbes [41,42]. The main keywords in the cluster of “system” were organic carbon, dynamics, system, total nitrogen, and cover change straw. The researchers mainly investigated the effect of straw return or cover on SOC and N dynamics, depending on returning modes and soils [43,44]. For example, straw returning increased more straw-derived C sequestration in the subsurface soil than in surface soil [45]. The main keywords in the cluster of “enzyme activity” and “microbial biomass” were microbial biomass, growth-promoting rhizobacteria, plant yield, soil food web and ecological significance, microbial biomass, soil quality, conservation agriculture, microbial respiration, and free-living nematode. The researchers in the two clusters mainly focused on the biotic processes in soil, especially the role of microbes and nematodes, and other small animals in SOC mineralization [46,47]. The microbial community composition and their C use efficiency and growth rate were the drivers of SOC change [48]. Compared with bacteria, fungi have an advantage in utilizing recalcitrant SOC due to its high C:N and mycelia [49]. The microbes with high C use efficiency and growth rate may produce more enzymes and necromass, influencing SOC decomposition and formation [50,51].
The timeline of keywords showed that sequestration, dynamics, mineralization, decomposition, and organic C were predominant topics of agricultural SOC mineralization during 2000–2005 (Figure 9). Additionally, the researchers focused on the SOC dynamic and sequestration under different methods of soil management and tillage and identified microbial regulations. In the last 7 years, more attention was paid to the decomposition of SOC and its mechanisms, such as the effect of nutrition on microbial decomposition of SOC.
The bursting keywords in the last five years (2018–2022) along with their strength and occurrence timespan were shown in Table 5. The studies involving CO2 efflux, China, C sequestration and storage, addition, black C, soil moisture, sensitivity, manure application, and straw incorporation emerged as active topics in recent five years. The increased CO2 concentration in the atmosphere enhanced the primary production of plants and accelerated the SOC cycle through the input of plant-derived C into soils [52,53]. Straw is often used as the simulation of exogenous C to investigate the effect of plant-derived C on SOC change [54]. The studies investigating CO2 flux within the plant–atmosphere–soil system benefit the understanding of SOC change and its feedback on the climate. China has developed quickly in economics, culture, and technology, attended the Paris climate agreement in 2016, and paid more attention to the research on SOC mineralization in recent years [55]. The sequestration of atmospheric CO2 into SOC is an effective strategy to reduce the CO2 concentration in the atmosphere, with the potential to mitigate climate change [4].

3.8. Articles Analysis with High Cited Frequency

Of the top 5 articles in terms of the average cited frequency per year (Table 6), three were published in Soil Biology & Biochemistry, and the other two were published in Plant and Soil and Agriculture, Ecosystem & Environment. The result was consistent with the results of a network of journals, indicating that Soil Biology & Biochemistry is the representative journal in the field of agricultural SOC mineralization research. The top five articles were from five different developed countries, indicating that the developed countries have a greater impact effect.
Four articles of the top five in the cited frequency per year were involved in soil C or N changes after biochar amendment. For example, the top article had an annual citation frequency of 89 times. This study investigated the interaction of pyrogenic C and SOC using an incubation experiment over more than one year. Biochar addition increased or decreased the CO2 emissions (positive or negative priming effect) in soils compared with unamended soils. The biochar produced at low temperatures induced a greater positive priming effect, especially in low-C soils. The high average cited frequency of the three studies indicates a growing interest in biochar as a method for increasing the soil fertility and sequestering atmospheric carbon over the last 10 years, along with the investigation of SOC changes after the biochar amendment. The fourth top article was cited 38 times annually. This study indicated that the effect of no-tillage on SOC sequestration was greatly dependent on the cropping system and the increased cropping frequency could benefit increasing the efficiency of SOC sequestration via a meta-analysis. These results suggest that the effect of biochar on the soil C cycle and its mechanisms have been the SOC research hotspot in recent years. The physical protection mechanism is an important potential mechanism inhabiting SOC mineralization and should be paid more attention in future studies.
Although this study has identified the basic characteristics, research output and knowledge base as well as the research trends regarding agricultural SOC mineralization, it had the following shortcomings. First, we investigated the research trend of agricultural SOC mineralization by using bibliometric analysis, which is a quantitative approach that focused on publication and citation data. Thus, this study may not capture the full breadth or quality of agricultural SOC mineralization research and may overlook important qualitative aspects such as study design, data collection methods, and the impact on policy or practice. The qualitative aspects could be obtained by meta-analysis in future studies. Second, we only included the studies involving agricultural SOC mineralization during 2000–2022. Although the chosen databases and period did not include all periods, introducing a bias in the sample and favoring certain types of studies or topics, the studies involving agriculture SOC mineralization are mainly in the last 20 years and the selected databases (Web of Science Core Collection) included high-level studies recognized by global researchers.

4. Conclusions

This study provides a unique snapshot of the knowledge domain involved in agricultural SOC mineralization based on the data source from the Web of Science Core Collection. The number of articles continuously increased from 2000 to 2022, especially in the last seven years. The top three subject categories are Agriculture, Environmental Sciences Ecology, and Plant Sciences. Soil Biology & Biochemistry is the top journal in terms of its influential effect. The USA is the main cooperation center among countries. The number of articles from China sharply increased after 2018 and far more than that of other countries; thus, China was able to play an important role in the evolution of agricultural SOC mineralization research. The top five articles in terms of the citation frequency were involved in SOC dynamics following biochar addition and the effect of no-tillage on SOC, which would become hotspots in recent years. Physical protection is an important way to stabilize SOC, which benefits alleviating greenhouse gas emission. However, the mechanisms of physical protection of agricultural SOC mineralization remain largely unexplored. The effects of soil mineral composition and activity and their interaction with the microbial community on SOC change should be explored in future research.

Author Contributions

F.Z.: conceptualization, data curation, methodology, software, writing—original draft. Y.Z.: supervision, writing—review. Y.Z. and Y.L.: writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of China [NO. 42177284].

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data available on request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Scharlemann, J.P.W.; Tanner, E.V.J.; Hiederer, R.; Kapos, V. Global soil carbon: Understanding and managing the largest terrestrial carbon pool. Carbon Manag. 2014, 5, 81–91. [Google Scholar] [CrossRef]
  2. Melillo, J.M.; Frey, S.D.; DeAngelis, K.M.; Werner, W.J.; Bernard, M.J.; Bowles, F.P.; Pold, G.; Knorr, M.A.; Grandy, A.S. Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world. Science 2017, 358, 101–104. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Meier, I.C.; Finzi, A.C.; Phillips, R.P. Root exudates increase N availability by stimulating microbial turnover of fast-cycling N pools. Soil Biol. Biochem. 2017, 106, 119–128. [Google Scholar] [CrossRef] [Green Version]
  4. Rumpel, C.; Chabbi, A. Managing soil organic carbon for mitigating climate change and increasing food security. Agronomy 2021, 11, 1553. [Google Scholar] [CrossRef]
  5. Kuzyakov, Y.; Friedel, J.K.; Stahr, K. Review of mechanisms and quantification of priming effects. Soil Biol. Biochem. 2000, 32, 1485–1498. [Google Scholar] [CrossRef]
  6. Dhaliwal, S.S.; Naresh, R.K.; Gupta, R.K.; Panwar, A.S.; Mahajan, N.C.; Singh, R.; Mandal, A. Effect of tillage and straw return on carbon footprints, soil organic carbon fractions and soil microbial community in different textured soils under rice-wheat rotation: A review. Rev. Environ. Sci. Bio/Technol. 2020, 19, 103–115. [Google Scholar] [CrossRef]
  7. Chen, B.; Liu, E.; Tian, Q.; Yan, C.; Zhang, Y. Soil nitrogen dynamics and crop residues. A review. Agron. Sustain. Dev. 2014, 34, 429–442. [Google Scholar] [CrossRef] [Green Version]
  8. Lal, R. Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Glob. Chang. Biol. 2018, 24, 3285–3301. [Google Scholar] [CrossRef]
  9. Bernard, L.; Basile-Doelsch, I.; Derrien, D.; Fanin, N.; Fontaine, S.; Guenet, B.; Karimi, B.; Marsden, C.; Maron, P.A. Advancing the mechanistic understanding of the priming effect on soil organic matter. Funct. Ecol. 2022, 36, 1355–1377. [Google Scholar] [CrossRef]
  10. Blagodatskaya, E.; Kuzyakov, Y. Mechanisms of real and apparent priming effects and their dependence on soil microbial biomass and community structure: Critical review. Biol. Fertil. Soils 2008, 45, 115–131. [Google Scholar] [CrossRef]
  11. Dignac, M.-F.; Derrien, D.; Barre, P.; Barot, S.; Cecillon, L.; Chenu, C.; Chevallier, T.; Freschet, G.T.; Garnier, P.; Guenet, B.; et al. Increasing soil carbon storage: Mechanisms, effects of agricultural practices and proxies. A review. Agron. Sustain. Dev. 2017, 37, 14. [Google Scholar] [CrossRef] [Green Version]
  12. Gougoulias, C.; Clark, J.M.; Shaw, L.J. The role of soil microbes in the global carbon cycle: Tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems. J. Sci. Food Agric. 2014, 94, 2362–2371. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Liu, C.; Lu, M.; Cui, J.; Li, B.; Fang, C. Effects of straw carbon input on carbon dynamics in agricultural soils: A meta-analysis. Glob. Chang. Biol. 2014, 20, 1366–1381. [Google Scholar] [CrossRef] [PubMed]
  14. Donthu, N.; Kumar, S.; Mukherjee, D.; Pandey, N.; Lim, W. How to conduct a bibliometric analysis: An overview and guidelines. J. Bus. Res. 2021, 133, 285–296. [Google Scholar] [CrossRef]
  15. Kumar, S.; Sureka, R.; Lim, W.M.; Mangla, S.K.; Goyal, N. What do we know about business strategy and environmental research? Insights from Business Strategy and the Environment. Bus. Strateg. Environ. 2021, 30, 3454–3469. [Google Scholar] [CrossRef]
  16. Pan, X.; Lv, J.; Dyck, M.; He, H.J.A. Bibliometric analysis of soil nutrient research between 1992 and 2020. Agriculture 2021, 11, 223. [Google Scholar] [CrossRef]
  17. Mao, G.; Shi, T.; Zhang, S.; Crittenden, J.; Guo, S.; Du, H. Bibliometric analysis of insights into soil remediation. J. Soils Sed. 2018, 18, 2520–2534. [Google Scholar] [CrossRef]
  18. Birkle, C.; Pendlebury, D.A.; Schnell, J.; Adams, J. Web of Science as a data source for research on scientific and scholarly activity. Quant. Sci. Stud. 2020, 1, 363–376. [Google Scholar] [CrossRef]
  19. van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010, 84, 523–538. [Google Scholar] [CrossRef] [Green Version]
  20. Moral-Muñoz, J.A.; Herrera-Viedma, E.; Santisteban-Espejo, A.; Cobo, M.J. Software tools for conducting bibliometric analysis in science: An up-to-date review. Prof. Inform. 2020, 29, e290103. [Google Scholar] [CrossRef] [Green Version]
  21. Chen, K.; Guan, J. A bibliometric investigation of research performance in emerging nanobiopharmaceuticals. J. Informetr. 2011, 5, 233–247. [Google Scholar] [CrossRef]
  22. Stockmann, U.; Adams, M.A.; Crawford, J.W.; Field, D.J.; Henakaarchchi, N.; Jenkins, M.; Minasny, B.; McBratney, A.B.; de Courcelles, V.D.R.; Singh, K.; et al. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agric. Ecosyst. Environ. 2013, 164, 80–99. [Google Scholar] [CrossRef]
  23. Radajewski, S.; McDonald, I.R.; Murrell, J.C. Stable-isotope probing of nucleic acids: A window to the function of uncultured microorganisms. Curr. Opin. Biotechnol. 2003, 14, 296–302. [Google Scholar] [CrossRef] [PubMed]
  24. Zheng, S.; Xia, Y.; Hu, Y.; Chen, X.; Rui, Y.; Gunina, A.; He, X.; Ge, T.; Wu, J.; Su, Y.; et al. Stoichiometry of carbon, nitrogen, and phosphorus in soil: Effects of agricultural land use and climate at a continental scale. Soil Till. Res. 2021, 209, 104903. [Google Scholar] [CrossRef]
  25. Yan, Z.; Zhou, J.; Yang, L.; Gunina, A.; Yang, Y.; Peixoto, L.; Zeng, Z.; Zang, H.; Kuzyakov, Y. Diversified cropping systems benefit soil carbon and nitrogen stocks by increasing aggregate stability: Results of three fractionation methods. Sci. Total Environ. 2022, 824, 153878. [Google Scholar] [CrossRef]
  26. Luo, Y.; Zang, H.; Yu, Z.; Chen, Z.; Gunina, A.; Kuzyakov, Y.; Xu, J.; Zhang, K.; Brookes, P.C. Priming effects in biochar enriched soils using a three-source-partitioning approach: C-14 labelling and C-13 natural abundance. Soil Biol. Biochem. 2017, 106, 28–35. [Google Scholar] [CrossRef] [Green Version]
  27. Gunina, A.; Kuzyakov, Y. From energy to (soil organic) matter. Glob. Chang. Biol. 2022, 28, 2169–2182. [Google Scholar] [CrossRef]
  28. Qiu, H.; Liu, J.; Chen, X.; Hu, Y.; Su, Y.; Ge, T.; Li, D.; Wu, J. Rice straw carbon mineralization is affected by the timing of exogenous glucose addition in flooded paddy soil. Appl. Soil Ecol. 2022, 173, 104374. [Google Scholar] [CrossRef]
  29. Qiu, H.; Ge, T.; Liu, J.; Chen, X.; Hu, Y.; Wu, J.; Su, Y.; Kuzyakov, Y. Effects of biotic and abiotic factors on soil organic matter mineralization: Experiments and structural modeling analysis. Eur. J. Soil Biol. 2018, 84, 27–34. [Google Scholar] [CrossRef]
  30. Jian, Y.; Zhu, Z.; Xiao, M.; Yuan, H.; Wang, J.; Zou, D.; Ge, T.; Wu, J. Microbial assimilation of atmospheric CO2 into soil organic matter revealed by the incubation of paddy soils under 14C-CO2 atmosphere. Arch. Agron. Soil Sci. 2016, 62, 1678–1685. [Google Scholar] [CrossRef]
  31. Elrys, A.S.; Ali, A.; Zhang, H.; Cheng, Y.; Zhang, J.; Cai, Z.-C.; Muller, C.; Chang, S.X. Patterns and drivers of global gross nitrogen mineralization in soils. Glob. Chang. Biol. 2021, 27, 5950–5962. [Google Scholar] [CrossRef] [PubMed]
  32. Li, Y.; Li, Y.; Chang, S.X.; Xu, Q.; Guo, Z.; Gao, Q.; Qin, Z.; Yang, Y.; Chen, J.; Liang, X. Bamboo invasion of broadleaf forests altered soil fungal community closely linked to changes in soil organic C chemical composition and mineral N production. Plant Soil 2017, 418, 507–521. [Google Scholar] [CrossRef]
  33. Qi, L.; Pokharel, P.; Chang, S.X.; Zhou, P.; Niu, H.; He, X.; Wang, Z.; Gao, M. Biochar application increased methane emission, soil carbon storage and net ecosystem carbon budget in a 2-year vegetable-rice rotation. Agric. Ecosyst. Environ. 2020, 292, 106831. [Google Scholar] [CrossRef]
  34. Ding, F.; Ji, D.; Yan, K.; Dijkstra, F.A.; Bao, X.; Li, S.; Kuzyakov, Y.; Wang, J. Increased soil organic matter after 28 years of nitrogen fertilization only with plastic film mulching is controlled by maize root biomass. Sci. Total Environ. 2022, 810, 152244. [Google Scholar] [CrossRef] [PubMed]
  35. Wang, D.; Zhu, Z.; Shahbaz, M.; Chen, L.; Liu, S.; Inubushi, K.; Wu, J.; Ge, T. Split N and P addition decreases straw mineralization and the priming effect of a paddy soil: A 100-day incubation experiment. Biol. Fertil. Soils 2019, 55, 701–712. [Google Scholar] [CrossRef]
  36. Ma, Q.; Wen, Y.; Wang, D.; Sun, X.; Hill, P.W.; Macdonald, A.; Chadwick, D.R.; Wu, L.; Jones, D.L. Farmyard manure applications stimulate soil carbon and nitrogen cycling by boosting microbial biomass rather than changing its community composition. Soil Biol. Biochem. 2020, 144, 107760. [Google Scholar] [CrossRef]
  37. Li, S.; Wang, S.; Fan, M.; Wu, Y.; Shangguan, Z. Interactions between biochar and nitrogen impact soil carbon mineralization and the microbial community. Soil Till. Res. 2020, 196, 104437. [Google Scholar] [CrossRef]
  38. Fang, Y.; Singh, B.P.; Collins, D.; Armstrong, R.; Van Zwieten, L.; Tavakkoli, E. Nutrient stoichiometry and labile carbon content of organic amendments control microbial biomass and carbon-use efficiency in a poorly structured sodic-subsoil. Biol. Fertil. Soils 2020, 56, 219–233. [Google Scholar] [CrossRef]
  39. Nottingham, A.T.; Turner, B.L.; Stott, A.W.; Tanner, E.V.J. Nitrogen and phosphorus constrain labile and stable carbon turnover in lowland tropical forest soils. Soil Biol. Biochem. 2015, 80, 26–33. [Google Scholar] [CrossRef]
  40. Don, A.; Roedenbeck, C.; Gleixner, G. Unexpected control of soil carbon turnover by soil carbon concentration. Environ. Chem. Lett. 2013, 11, 407–413. [Google Scholar] [CrossRef]
  41. Rousk, J.; Baath, E.; Brookes, P.C.; Lauber, C.L.; Lozupone, C.; Caporaso, J.G.; Knight, R.; Fierer, N. Soil bacterial and fungal communities across a pH gradient in an arable soil. ISME J. 2010, 4, 1340–1351. [Google Scholar] [CrossRef] [PubMed]
  42. Zhang, S.; Fang, Y.; Luo, Y.; Li, Y.; Ge, T.; Wang, Y.; Wang, H.; Yu, B.; Song, X.; Chen, J.; et al. Linking soil carbon availability, microbial community composition and enzyme activities to organic carbon mineralization of a bamboo forest soil amended with pyrogenic and fresh organic matter. Sci. Total Environ. 2021, 801, 149717. [Google Scholar] [CrossRef] [PubMed]
  43. de Souza, R.F.; de Figueiredo, C.C.; Madeira, N.R.; de Alcantara, F.A. Effect of management systems and cover crops on organic matter dynamics of soil under vegetables. Rev. Bras. Cienc. Solo 2014, 38, 923–933. [Google Scholar] [CrossRef] [Green Version]
  44. Balota, E.L.; Colozzi, A.; Andrade, D.S.; Dick, R.P. Long-term tillage and crop rotation effects on microbial biomass and C and N mineralization in a Brazilian Oxisol. Soil Till. Res. 2004, 77, 137–145. [Google Scholar] [CrossRef]
  45. Wang, S.; Lu, C.; Huai, S.; Yan, Z.; Wang, J.; Sun, J.; Raza, S. Straw burial depth and manure application affect the straw-C and N sequestration: Evidence from C-13 & N-15-tracing. Soil Till. Res. 2021, 208, 104884. [Google Scholar]
  46. Su, L.; Bai, T.; Qin, X.; Yu, H.; Wu, G.; Zhao, Q.; Tan, L. Organic manure induced soil food web of microbes and nematodes drive soil organic matter under jackfruit planting. Appl. Soil Ecol. 2021, 166, 103994. [Google Scholar] [CrossRef]
  47. Guan, P.; Zhang, X.; Yu, J.; Cheng, Y.; Li, Q.; Andriuzzi, W.S.; Liang, W. Soil microbial food web channels associated with biological soil crusts in desertification restoration: The carbon flow from microbes to nematodes. Soil Biol. Biochem. 2018, 116, 82–90. [Google Scholar] [CrossRef]
  48. Schimel, J.P.; Schaeffer, S.M. Microbial control over carbon cycling in soil. Front. Microbiol. 2012, 3, 348. [Google Scholar] [CrossRef] [Green Version]
  49. Fontaine, S.; Henault, C.; Aamor, A.; Bdioui, N.; Bloor, J.M.G.; Maire, V.; Mary, B.; Revaillot, S.; Maron, P.A. Fungi mediate long term sequestration of carbon and nitrogen in soil through their priming effect. Soil Biol. Biochem. 2011, 43, 86–96. [Google Scholar] [CrossRef]
  50. Kallenbach, C.M.; Grandy, A.S.; Frey, S.D.; Diefendorf, A.F. Microbial physiology and necromass regulate agricultural soil carbon accumulation. Soil Biol. Biochem. 2015, 91, 279–290. [Google Scholar] [CrossRef] [Green Version]
  51. Mehnaz, K.R.; Corneo, P.E.; Keitel, C.; Dijkstra, F.A. Carbon and phosphorus addition effects on microbial carbon use efficiency, soil organic matter priming, gross nitrogen mineralization and nitrous oxide emission from soil. Soil Biol. Biochem. 2019, 134, 175–186. [Google Scholar] [CrossRef]
  52. Schimel, D.; Stephens, B.B.; Fisher, J.B. Effect of increasing CO2 on the terrestrial carbon cycle. Proc. Natl. Acad. Sci. USA 2015, 112, 436–441. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Kuzyakov, Y.; Horwath, W.R.; Dorodnikov, M.; Blagodatskaya, E. Review and synthesis of the effects of elevated atmospheric CO2 on soil processes: No changes in pools, but increased fluxes and accelerated cycles. Soil Biol. Biochem. 2019, 128, 66–78. [Google Scholar] [CrossRef]
  54. Palansooriya, K.N.; Ok, Y.S.; Awad, Y.M.; Lee, S.S.; Sung, J.-K.; Koutsospyros, A.; Moon, D.H. Impacts of biochar application on upland agriculture: A review. J. Environ. Manag. 2019, 234, 52–64. [Google Scholar] [CrossRef]
  55. Heggelund, G.M. China’s climate and energy policy: At a turning point? Int. Environ. Agreem. 2021, 21, 9–23. [Google Scholar] [CrossRef]
Figure 1. Flow chart of literature screening.
Figure 1. Flow chart of literature screening.
Agriculture 13 01248 g001
Figure 2. Trends in the number of articles and cited times identified by the Web of Science core dataset.
Figure 2. Trends in the number of articles and cited times identified by the Web of Science core dataset.
Agriculture 13 01248 g002
Figure 3. The percentage of the number of articles in a subject relative to the total amount of articles in the top 10 subjects during the last 22 years (a) and the first decade (b) and second decade (c).
Figure 3. The percentage of the number of articles in a subject relative to the total amount of articles in the top 10 subjects during the last 22 years (a) and the first decade (b) and second decade (c).
Agriculture 13 01248 g003
Figure 4. Network of journals including articles involving agricultural SOC mineralization. The bigger node represents that a journal is more important. The color indicates the cluster of journals. The lines indicate the link between journals.
Figure 4. Network of journals including articles involving agricultural SOC mineralization. The bigger node represents that a journal is more important. The color indicates the cluster of journals. The lines indicate the link between journals.
Agriculture 13 01248 g004
Figure 5. The number of articles and their cited frequency (a), the average citation frequency (b) from the top 10 countries, and the change in the number of articles per year from the top 5 and top 6–10 countries over time (c,d).
Figure 5. The number of articles and their cited frequency (a), the average citation frequency (b) from the top 10 countries, and the change in the number of articles per year from the top 5 and top 6–10 countries over time (c,d).
Agriculture 13 01248 g005
Figure 6. The activity and attractive index of the top 10 countries. The dotted line y = 1 represented that the research effort and academic influence of a country are the same as that of the global average.
Figure 6. The activity and attractive index of the top 10 countries. The dotted line y = 1 represented that the research effort and academic influence of a country are the same as that of the global average.
Agriculture 13 01248 g006
Figure 7. The network of countries (a) and institutions (b). The size of the country’s/institution’s name reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships of countries/institutions. The color of the nodes and lines varied from gray to red as shown in the legend, from 2000 to 2022. The wider lines represent stronger cooperation of authors.
Figure 7. The network of countries (a) and institutions (b). The size of the country’s/institution’s name reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships of countries/institutions. The color of the nodes and lines varied from gray to red as shown in the legend, from 2000 to 2022. The wider lines represent stronger cooperation of authors.
Agriculture 13 01248 g007
Figure 8. The cooperation network of authors. The size of the author’s name reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships of authors. The color of the node and line varied from gray to red as time passes from 2000 to 2022. The wider lines represent stronger cooperation of authors.
Figure 8. The cooperation network of authors. The size of the author’s name reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships of authors. The color of the node and line varied from gray to red as time passes from 2000 to 2022. The wider lines represent stronger cooperation of authors.
Agriculture 13 01248 g008
Figure 9. The timelines of keywords involving the study of agricultural SOC mineralization in five clusters. The size of the node reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships between keywords, with a color representing a cluster of keywords. The keywords on or above straight lines listed from left to right according to time (from 2000 to 2022).
Figure 9. The timelines of keywords involving the study of agricultural SOC mineralization in five clusters. The size of the node reflects the co-occurrence frequencies. The links indicate the co-occurrence relationships between keywords, with a color representing a cluster of keywords. The keywords on or above straight lines listed from left to right according to time (from 2000 to 2022).
Agriculture 13 01248 g009
Table 1. The top 10 journals related to the study of agricultural SOC mineralization, along with the number of articles and the key parameters used to estimate each journal.
Table 1. The top 10 journals related to the study of agricultural SOC mineralization, along with the number of articles and the key parameters used to estimate each journal.
RankJournalNumber of
Articles
Total Link
Strength
Cited
Frequency
Average IF
in Five Years
Citation
Indicator in 2021
1Soil Biology & Biochemistry17888110,5659.9561.9
2Agriculture, Ecosystems & Environment15567066067.0891.7
3Soil & Tillage Research12353150747.8291.59
4Geoderma15452440427.4441.66
5Biology and Fertility of Soils10041338007.1161.5
6Applied Soil Ecology11240334515.6781.16
7Plant and Soil10939733405.4401.3
8Soil Science Society of America Journal9939041223.5640.65
9Nutrient Cycling in Agroecosystems9124520744.5040.8
10Science of the Total Environment98245175910.2371.77
The total link strength indicates the co-occurrence frequency of one and another journal. IF, influential factor.
Table 2. The top 10 institutes related to the study of agricultural SOC mineralization and their key information.
Table 2. The top 10 institutes related to the study of agricultural SOC mineralization and their key information.
RankInstituteArticlesPercentageCentrality Country
1Chinese Academy of Sciences39512.0%0.43China
2Chinese Academy of Agricultural Sciences882.6%0.04China
3USDA-agricultural research service792.4%0.07USA
4Northwest A&F University of China752.2%0.04China
5Agriculture & Agri-Food Canada722.1%0.09Canada
6China Agricultural University621.8%0.07China
7Iowa State University411.2%0.02USA
8Spanish National Research Council (CSIC)401.2%0.04Spain
9University of California Davis391.1%0.04USA
10Zhejiang University381.1%0.01China
The centrality is an indicator representing the importance of an institute in a research field. An institute is important and has a great influence on the development of a research field when the centrality is greater than 1.
Table 3. The top 10 authors in terms of related studies and their key information.
Table 3. The top 10 authors in terms of related studies and their key information.
RankAuthorInstitutionCountryArticlesCentrality
1Kuzyakov YakovUniversity of GöttingenGermany360.01
2Ge TidaNingbo UniversityChina210.00
3Wu JinshuiInstitute of Subtropical Agriculture, Chinese Academy of SciencesChina120.00
4Joergensen Rainer GeorgUniversity of KasselGermany80.00
5Zhu ZhenkeInstitute of Subtropical Agriculture, Chinese Academy of SciencesChina80.00
6Chang Scott X.University of AlbertaCanada80.01
7Ok Yong SikUniversity of SejongSouth Korea80.00
8Six JohnUniversity of Colorado StateUSA80.00
9Castellano Michael J.Iowa State UniversityUSA70.00
10Jones Davey L.University of Western AustraliaAustralia70.00
The centrality is an indicator representing the importance of an author in a research field. An author is important and has a great influence on the development of a research field when the centrality is greater than 1.
Table 4. The top 5 clusters of the keywords and the included keywords of the top 5.
Table 4. The top 5 clusters of the keywords and the included keywords of the top 5.
IDCluster NameSizeMain Keywords (Top 5)
0Carbon sequestration46organic matter; soil enzyme activity; nitrogen use efficiency; mineralization rates; soil fertility;
1Soil organic carbon41organic carbon; microbial biomass; carbon isotopes; soil constraints; N uptake
2System38organic carbon; dynamics; system; total nitrogen; cover change straw;
3Enzyme activity29microbial biomass; growth-promoting rhizobacteria; plant yield; soil food web; ecological significance
4Microbial biomass20microbial biomass; soil quality; conservation agriculture; microbial respiration; free-living nematodes
Table 5. Top 10 keywords with the strongest citation bursts and their key information.
Table 5. Top 10 keywords with the strongest citation bursts and their key information.
IDKeywordsYearStrengthBeginEnd20182019202020212022
1CO2 efflux20183.1320182019Agriculture 13 01248 i001
2China20182.7820182019Agriculture 13 01248 i001
3Carbon sequestration20182.4320182019Agriculture 13 01248 i001
4Carbon storage20182.4320182019Agriculture 13 01248 i001
5Addition20182.4320182019Agriculture 13 01248 i001
6Black carbon20182.1020182019Agriculture 13 01248 i001
7Soil moisture20192.6820192020Agriculture 13 01248 i002
8Sensitivity20192.4120192020Agriculture 13 01248 i002
9Manure application20192.1520192020Agriculture 13 01248 i002
10Straw incorporation20202.2620202022Agriculture 13 01248 i003
Blue and red lines indicate the time interval and the period of a bursting keyword from beginning to end.
Table 6. The top 10 articles related to the study of agricultural SOC mineralization.
Table 6. The top 10 articles related to the study of agricultural SOC mineralization.
RankAverage Cited Frequency per YearTitleAuthors
(Year)
CountryJournal
189Positive and negative carbon mineralization priming effects among a variety of biochar-amended soilsZimmerman et al. (2011)FranceSoil Biology & Biochemistry
265Biochar-mediated changes in soil quality and plant growth in a three-year field trialJones et al.
(2012)
UKSoil Biology & Biochemistry
341Decreased soil microbial biomass and nitrogen mineralization with Eucalyptus biochar addition to a coarse textured soilDempster et al. (2012)AustraliaPlant and Soil
438Can no-tillage stimulate carbon sequestration in agricultural soils? A meta-analysis of paired experimentsLuo et al.
(2010)
ChinaAgriculture, Ecosystems & Environment
536Life in the ‘charosphere’—Does biochar in agricultural soil provide a significant habitat for microorganisms?Quilliam et al. (2013)ScotlandSoil Biology & Biochemistry
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, F.; Liu, Y.; Zhang, Y. Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022. Agriculture 2023, 13, 1248. https://doi.org/10.3390/agriculture13061248

AMA Style

Zhang F, Liu Y, Zhang Y. Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022. Agriculture. 2023; 13(6):1248. https://doi.org/10.3390/agriculture13061248

Chicago/Turabian Style

Zhang, Futao, Yuedong Liu, and Yueling Zhang. 2023. "Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022" Agriculture 13, no. 6: 1248. https://doi.org/10.3390/agriculture13061248

APA Style

Zhang, F., Liu, Y., & Zhang, Y. (2023). Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022. Agriculture, 13(6), 1248. https://doi.org/10.3390/agriculture13061248

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop