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Literature Review for Accounting/Auditing

Main Objectives, Procedures & Resources

What is a literature review and what is the purpose?

A literature review consists of simply a summary of key sources, and it usually combines both summary and synthesis, often within specific conceptual categories. A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that tells how you are planning to investigate a research problem.

A literature review is conducted during the first phase of the research process (in the exploration stage). The purpose of a literature review is to:

• To survey the current state of knowledge in the area of inquiry (concerning the research questions and/or related topics)
• To identify key authors, articles, theories, and findings in that area
• To identify gaps in knowledge in the research area

In this document, we will focus on the steps to follow in doing a literature search on a topic or author. While the steps below are listed in numerical order, some steps may need to be repeated, revisited, and/or skipped as you go through the process.

• Consider a topic for the research question and determine the breadth and depth of your topic that is manageable in scope - hence preferably, not too wide nor too narrow.  For instance, the topic - Audits and IPOs – could be a good one in this regard.  
• Audits > Auditor, auditors, auditing …
• IPOs  >  IPOs, Initial Public Offerings …

     Thus, we can change our original topic - Audits AND IPOs – into a new search statement as below:

• (Audit * ) AND (IPOs OR Initial Public Offerings)
• AND -- this narrows a search by telling the database that ALL keywords used must appear in the same records/results.
• OR -- this broadens a search by telling the database that ANY of the words it connects are acceptable in the search results.
• * -- this asterisk is a wildcard character , so using: Audit * = the search results may contain Audit, Audit s, Audit or, Audit ing
• Link 1 - Results   - Getting Search Results:  182 (as of 10/16/23)
• Link 2 Results   - Getting Search Results:  498 (as of 10/16/23)
• Audit risk issues
• Financial statements  
• Management structure or corporate governance
• Compliance  
• Mergers or Acquisitions
• Now, with the help of Boolean operator “ AND ” we can easily combine theses three concepts/keywords, thus forming some seemingly intricate, yet more promising search statements as below.  That way, we could be able to pull out more meaningful, focused, and relevant results from a huge databases:
• (Audit * ) AND (IPO * OR Initial Public Offerings) AND ( Risk * ) > Results from EBSCO
• (Audit * ) AND (IPO * OR Initial Public Offerings) AND ( Financial statements ) > Results from EBSCO
• (Audit * ) AND (IPO * OR Initial Public Offerings) AND ( management structure or corporate governance ) > Results from EBSCO
• (Audit * ) AND (IPO * OR Initial Public Offerings) AND ( compliance ) > Results from EBSCO
• Su (Audit * ) AND Ti (IPO * OR Initial Public Offerings) AND Su (merger * OR acquisition * OR m&a * ) > Results from EBSCO

Please note: (1) Following each of the search statements above, there is a link to results from our library subscription databases - EBSCOhost .    EBSCOhost is one of our recommendation databases for any literature review as it is the largest databases for journals/articles coverage we subscribe to so far, and Business Source Complete ls just one of them. (2) #5 above is different from other in that the Fields - Su and Ti Fields - have been added and used in the search statement.  Why Fields search will be discussed in the next Step (Step 5).     

• With the power of computing and databases, more often than not, users would get  overwhelming results from whatever keywords used.  How to overcome that? You can reduce the overwhelming number of results, and in the meantime not sacrifice any relevant and high-quality results by taking advantage of the content-related fields in structured databases – the fields that is already build-in with almost all databases, such as EBSCOhost .  We are particularly interested in the following content-related fields:
• Title  - TI field
• Subject - SU field
• Abstract  - AB field 

As a result of using fields, you are actually limiting (forcing) the keywords of selection only appear in certain fields you’ve specified.  Think about this: if in a title of an article, there is a word XYZ, the chances are content of the article is pretty much about XYZ.  The same applies to the fields of subject and abstract.

• au (Raman, K) AND ab (audit*) =  60 results > Results from ProQuest
• au (Raman, K) AND su (audit*)   = 42 results > Results from ProQuest
• au (Raman, k) AND litigation = 18 results > Results from ProQuest
• As the search results are returned, it is best to preview the results by looking for articles that are relevant to your specific research questions. Try to pay attention to words around the highlighted keywords (it may reveal why a particular article has been pulled out), skim the abstract and the introduction section, even try to read the literature review sections of these articles. This will help to determine the suitability of that article for a further review.
• Overall, a well conducted literature review should indicate whether the initial research question or topics have already been addressed in the literature, whether there are newer or more interest research questions available, and whether the original research question should be modified or changed in light of findings of the literature review.  
• Last but not least, it is highly recommended to search the following UTSA subscription databases considering these databases’ coverage and relevancy to your academic discipline.  Certainly, you can use the techniques and procedure we’ve discussed above within all of the databases below. 
• Academic Search Complete  is a flagship of EBSCOhost
• Business Source Complete – another sub-database of EBSCOhost —that also c overs Working Papers
• including ABI/INFORM Collection and 
• Accounting, Tax & Banking Collection  
• NBER Working Papers
• Provides access to books and journals in accounting and finance, economics, and more
• Last Updated: Oct 16, 2023 9:40 AM
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Adaptation of Life Cycle Costing Practices to Financial Performance Analysis in Transitional Economies: The Experience of Russian Manufacturing Firms

• Published: 09 May 2024

Cite this article

• Vasilii Erokhin   ORCID: orcid.org/0000-0002-3745-5469 1 ,
• Alexey Bobryshev   ORCID: orcid.org/0000-0001-5039-507X 2 ,
• Inna Manzhosova   ORCID: orcid.org/0000-0002-0342-2511 2 ,
• Alexandr Frolov   ORCID: orcid.org/0000-0003-3535-2957 2 ,
• Svetlana Shamrina   ORCID: orcid.org/0000-0001-9986-2011 2 &
• Nelly Agafonova   ORCID: orcid.org/0000-0001-7729-624X 2  

In today’s business environments driven increasingly by knowledge, the efficient use of resources largely depends on how well entrepreneurs apply innovations in managing them. Among the knowledge-based sources for increasing performance are accounting-related practices of cost management. However, there is a lack of models for constructing accounting records based on the stages of the product’s life cycle cost (LCC), methods for calculating the total cost of the LCC in relation to specific industries, and methods for identifying the stages of the LCC. Although many studies have focused on adapting to the LCC system strategically and studying its effectiveness and cost structure at different stages of the life cycle, few have considered the methodological aspects of establishing a costing system. This paper presents a comparative analysis of the most commonly used accounting and calculation methods used in manufacturing companies in Russia. The study is based on questionnaires collected in a survey of seven companies specializing in the manufacture of boilers for centralized and autonomous heating systems. In addition to interviewing experts, accounting documents were also analyzed. For the manufacturing sector, the authors proposed an accounting model based on the stages of a product’s life cycle. They also developed methods for calculating and identifying costs by stage of the product’s life cycle. These approaches could be useful for accounting and analytical staff when setting up knowledge-based accounting systems for analyzing business information, particularly for creating recordkeeping systems for LCC calculations. Additionally, these approaches could enhance the knowledge support systems for making managerial decisions.

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Erokhin, V., Bobryshev, A., Manzhosova, I. et al. Adaptation of Life Cycle Costing Practices to Financial Performance Analysis in Transitional Economies: The Experience of Russian Manufacturing Firms. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-02051-3

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Research Article

Cover crops support the climate change mitigation potential of agroecosystems

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation Weihenstephan-Triesdorf University of Applied Sciences, Triesdorf, Germany

Roles Funding acquisition, Methodology, Writing – original draft, Writing – review & editing

Affiliation Institute of Earth System Science, Section Soil Science, Leibniz Universität Hannover, Hannover, Germany

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

• Jonas Schön, 
• Norman Gentsch, 
• Peter Breunig

• Published: May 8, 2024
• https://doi.org/10.1371/journal.pone.0302139
• Peer Review
• Reader Comments

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize ( Zea maize L .) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO 2 e ha -1 a -1 . We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO 2 e a -1 , which is equivalent to 13.0% of the EU’s agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Citation: Schön J, Gentsch N, Breunig P (2024) Cover crops support the climate change mitigation potential of agroecosystems. PLoS ONE 19(5): e0302139. https://doi.org/10.1371/journal.pone.0302139

Editor: Abhay Omprakash Shirale, IISS: Indian Institute of Soil Science, INDIA

Received: November 29, 2023; Accepted: March 28, 2024; Published: May 8, 2024

Copyright: © 2024 Schön et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The research was funded by the German Federal Ministry of Education and Research within the Project "CATCHY", project number: 031B1060C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Mitigating climate change through measures in agriculture and food systems is essential for achieving the 1.50° and 2.00°C climate change targets of the Paris Agreement [ 1 ]. Worldwide, agriculture and food production systems are responsible for about one-third of global anthropogenic greenhouse gas (GHG) emissions, of which 40.0% are caused by agricultural production and 32.0% by land use and land use change [ 2 ]. However, agricultural systems also offer opportunities for climate change mitigation. Agroecosystems have significant potential to reduce global net emissions [ 3 ] and could even act as a net carbon sink [ 4 ]. To achieve these emission reduction and carbon sequestration opportunities, a transformation of agricultural systems is required. An essential component of climate-smart agricultural systems is planting cover crops. Cover crops are plants or plant mixtures that are not harvested for revenue, but are grown for the purpose of soil nutrient management, organic matter input, soil protection, and soil health improvement [ 5 ]. Cover crops are associated with multiple ecosystem services, such as closer nutrient cycling [ 5 , 6 ], activation of soil biology, biodiversity improvement [ 7 ], soil water management, and restoration of soil structures [ 8 ]. In addition, the mentioned effects of cover crops could mitigate climate change by soil carbon sequestration [ 9 ], biomass carbon storage, or reduced fertilizer losses to aquatic ecosystems. Recent studies show that these effects can lead to agronomic benefits that translate into higher yields and reduced agricultural input [ 10 ].

Despite these benefits, there exists a knowledge gap. The research problem addressed in this article is that there are no complete climate impact assessments of the cultivation of cover crops that also fully include land use effects. Cover crops reduces land use requirements by increasing yields of the subsequent crop. As land use change is still the largest carbon emissions source in the agri-food-system, yield increasing measures can be considered as a climate change mitigation option. According to Searchinger et al. [ 11 ], these carbon land benefits can be calculated as a “carbon opportunity cost,” which is the foregone carbon storage potential from natural vegetation to produce a certain agricultural product in kg CO 2 e kg -1 . When yields rise on one piece of land, this carbon storage potential can be maintained or restored on other locations since land use change is prevented or reverted. Kovak et al. [ 12 ] used this approach to quantify the climate change mitigation potential of a yield increase based on genetic modified crops. This is the first study to include carbon opportunity cost in the evaluation of the climate impact of cover cropping. As an additional climate benefit, cover crops remove carbon from the atmosphere during their growth while their residues and rhizodeposits are transformed to stable soil organic matter by retaining soil moisture. Further climate benefits of cover crops can be attributed to the supply of nutrients to the subsequent crop, which allows for fertilizer savings [ 13 ], reduced N 2 O emissions due to less nitrogen leaching, reduced solar radiation due to plant growth [ 14 ], and reduced soil erosion [ 15 ]. We define all factors above as “climate benefits”.

While cultivating cover crops can accrue these climate benefits, it can also generate GHG emissions that we refer as “climate costs”. The cultivation of cover crops can increase N 2 O emissions in periods of anaerobic microbial conversion of cover crop decomposition products [ 16 ]. Emissions are also generated in the production of cover crop seeds through a number of avenues, such as the land required for seed production and the production process of the seeds. In addition, produced seeds need to be packed and delivered, which also generates emissions[ 17 ]. Lastly, tilling, seeding, and termination of cover crops requires the use of GHG emitting machinery and resources [ 18 ]. Both climate benefits and climate costs of cover crops need to be carefully considered to calculate the NCCMI.

This article addresses the research problem by developing a comprehensive framework to quantify the NCCMI of cover crops including land use effects based on a systematic literature review. Using selected keywords, a systematic search was conducted in “Web of Science” and “Google Scholar” and resulted in 1269 publications. We define a list of relevant climate benefits and climate costs from which the NCCMI of cover crops is derived. We apply the framework to cover crops for maize in the European Union (EU-27, which is all EU Member States excluding the United Kingdom) to quantify its total NCCMI.

The following analyses are based on a typical Central European crop rotation, namely winter cover crops that are incorporated into the soil and maize as a cash crop following the cover crops in the spring. To quantify the impact of cover crop cultivation on the climate mitigation potential, a systematic literature review was conducted. The research platforms "Web of Science" and "Google Scholar" were used to explore the literature. Based on the initial research, we defined five factors that support climate change mitigation (“climate benefits”) and five factors leading to additional GHG emissions (“climate costs”) due to cover cropping ( Table 1 ). The individual research terms of the individual impact factors are described below in detail.

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https://doi.org/10.1371/journal.pone.0302139.t001

To calculate the NCCMI of cover crops, the values of all impact factors were converted to the same unit, namely megagram of CO 2 equivalents per hectare and year (Mg CO 2 e ha -1 a -1 ). From the values in the literature, a weighted average value that takes into account the number of measurements in the specific study was calculated. Only data from the literature that indicated the number of measurement points were considered in the calculation of the NCCMI. Thus, the climate benefits and climate costs could be added together in each case before subtracting the costs from the benefits. This resulted in a value for the NCCMI per hectare of cover crops given in Mg CO 2 e ha -1 a -1 . The 95% confidence interval was calculated from all study means and presents a range of estimates. To extrapolate the results to the EU-27 maize area the respective impact factors and the climate balances were subsequently multiplied with the maize acreage in the EU-27. The result was then divided by the total emissions from agriculture in the EU-27. This calculation resulted in the share of the NCCMI of cover crops before maize relative to all EU-27 agricultural emissions. The average maize acreage in 22 of the EU-27 countries was calculated as an average based on the years 2011 to 2022 (five of the EU-27 countries do not grow relevant quantities of maize and were thus not considered.)

The following search terms were used in Web of Science:

Cover crop & albedo, Cover crop & C sequestration, Cover crop & Yield corn, Cover crop & Yield maize, Cover crop & life cycle assessment, Cover crop & N-fixation, Cover crop & N-leaching, Fertilizer & Greenhouse gas emissions, Greenhouse gas emissions & fertilizer production, Cover crop & N 2 O, Catch crop & N 2 O. To enable a phrase search, all search terms were used with quotation marks to obtain search results exactly in this word order.

A total of 883 publications were extracted and checked for their suitability. Criteria for the required data were an absolute value from the respective study and the number of measurements. Only 44 articles met these criteria and were finally included in the review. In addition, we used 31 publications from Google Scholar and data from 26 other Internet sources that were selected based on the above criteria. In selecting sources, cover crops were considered both consisting of individual components and mixtures, overwintering as well as freezing, and legumes as well as non-legumes. All data sources are presented in the supplemental material ( S1 File ) and sorted based on the subsections below.

2.1. Carbon land benefit based on yield gain

2.2. Carbon sequestration

Carbon sequestration through cover crops is usually provided in units of soil organic carbon. This value was multiplied by a factor of 3.667 (i.e., the ratio of molar masses of CO 2 and C) to obtain the value of CO 2 stored per ha land.

2.3. Nitrogen fertilizer savings

For nutrient savings, we considered only the main nutrient, namely nitrogen since its production is highly energy intensive. To quantify fertilizer savings, we only considered emissions of mineral fertilizers and not that of organic fertilizers. The overall nitrogen fertilizer savings were quantified as the sum of the mean literature values on nitrogen scavenging and the mean literature values of nitrogen fixation from cover crops.

2.4. Reduced indirect N 2 O emissions due to less leaching

Reducing nitrogen leaching due to cover crops leads to lower indirect N 2 O emissions since less nitrogen is deposited to rivers and other water bodies. To quantify this effect, we use the approach suggested in the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: The amount of nitrogen leaching reduction is multiplied by the emission factor EF 5 of 0.0075 [ 20 ] to obtain the reduction in indirect N 2 O emissions per hectare. This value is then converted from kg N 2 O-N ha -1 to kg CO 2 -eq ha -1 using the conversion factor 273 and divided by 1000 to obtain the unit Mg CO 2 -eq ha -1 [ 21 ].

2.5 Albedo change

The reduced adsorption and thus increased reflection of solar radiation by cover crops’ plant cover compared to fallow land leads to a climate change mitigation effect. We found, however, only two studies evaluating the impact of albedo change from cover crops (Kaye and Quemada [ 22 ] and another by Carrer et al. [ 14 ]).

2.6. Nitrous oxide emissions

In the case of nitrous oxide emissions, the cumulative emissions that occur during the period of fallow or the period from sowing to incorporation of cover crops are considered. The values with the unit kg N 2 O-N ha -1 were multiplied by a factor of 273 and 1000 to obtain the unit in Mg CO 2 e ha -1 .

2.7. Foregone benefits due to cover crop seed land use

Table 2 shows the mean input values derived from the literature for the land use requirements for cover crop seeds.

https://doi.org/10.1371/journal.pone.0302139.t002

2.8. Production emissions for cover crop seed production, dispatch and additional machinery costs

Product emissions for cover crop seed production are not available in literature and therefore derived from maize, rapeseed, and spring wheat seed production. This is a conservative assumption since the nitrogen input and machinery operations as key drivers of emissions are usually higher in these crops than in cover crops. Emissions data is collected from the literature in kg CO 2 e kg -1 of seed and is multiplied with the seeding rate of cover crops. This results in an emissions value per hectare.

Emissions for processing, packaging, and transporting cover crop seeds are also not available and derived from maize seed production emissions and are expressed in kg CO 2 e kg -1 of seed. This is again a conservative assumption since maize seed has to fulfill much higher quality standards than cover crop seed.

The emissions of additional machinery operations for tillage, seeding, and mechanical termination of cover crops were included only in terms of additional diesel fuel usage. Average diesel fuel consumption of all additional operations was calculated and multiplied by the average GHG emissions of diesel fuel.

The impact of all analyzed factors on the NCCMI of cover crops is summarized in Table 3 . The results refer to a typical European crop rotation using a winter cover crop and maize as the following crop in spring. Individual impact factors are described in the following sections.

https://doi.org/10.1371/journal.pone.0302139.t003

3.1. Carbon land benefit based on yield gain

The literature review on the impact of winter cover crop on maize yields revealed that yield effects are highly dependent on the cover crop species or the composition of the cover crop mixture. The yield effect of cover crops on the following crop is also highly dependent on the type of land management. The lower the tillage intensity, the higher the yield increase [ 18 ]. The yield increase effect is also much higher in organic farming than in conventional systems. Marcillo and Miguez [ 24 ] find a yield increase of 8.0% for a conventional intensive tillage system, while for an organic reduced tillage system, yields increased by 61.0% when cover cropping was implemented. In summary, the considered studies showed a weighted mean maize yield gain due to cover cropping of 8.8% (95% CI, 2.9, 14.8).

Fig 1 shows the included yield effect results, confidence intervals and the pooled effect. If more than one result is shown from one study in Fig 1 this literature showed results from multiple experiments.

https://doi.org/10.1371/journal.pone.0302139.g001

Multiplying the weighted mean yield gain with the average EU-27 maize yield and the carbon opportunity cost factor for maize (2.10 kg CO 2 e kg -1 maize [ 11 ]) results in a mean carbon land benefit increase of 1.46 Mg CO 2 e ha -1 .

3.2. Carbon sequestration

Cover crops have a positive impact on soil organic carbon sequestration in arable soils. The literature research revealed two meta-analyses with 139 and 1195 studies included. In addition, 26 studies that were not included in the above-mentioned meta-analyses were also included in our calculations. Up to 12.0% of carbon from cover crop biomass can be sequestered as soil organic carbon [ 13 ]. Similar to the crop yield effects shown above, the potential of soil organic carbon stock increases depending on the type of cover crop. For example, a soil organic carbon increase of 0.26 Mg CO 2 e ha -1 a -1 has been found for a winter vetch cover crop [ 13 ]. A much larger increase in soil carbon of 5.12 Mg CO 2 e ha -1 a -1 was found by Abdalla et al. [ 25 ] for non-legume cover crops. The weighted mean of all studies investigated shows an average sequestration of 1.43 Mg CO 2 e ha -1 a -1 (95% CI, 0.86, 2.01). Based on the included studies, grass cover crops lead to a 2.3-times higher soil organic carbon sequestration than legume cover crops. Cover crop mixtures of grasses, legumes, and various other species are in the middle of the field in sequestration performance [ 26 ].

Fig 2 shows the included carbon sequestration results, confidence intervals and the pooled effect. If more than one result is shown from one study in Fig 2 this literature showed results from multiple experiments.

https://doi.org/10.1371/journal.pone.0302139.g002

3.3. Nitrogen fixation

Legume cover crops are able to fix atmospheric nitrogen and transfer it to the rhizosphere or utilize it for their own biomass. The decay of nitrogen-rich legume litter or rhizosphere products contribute to soil nitrogen fertilization and plant nutrition of the crop following the cover crop [ 13 ]. The amount of nitrogen fixed depends on the legume species and/or the companion crop species in the mixture. For example, red clover fixes 29.00 kg N ha -1 as a single species cover crop, but 52.00 kg N ha -1 in a mixture with ryegrass [ 13 ]. The same was observed with winter vetch, which fixes 85.00 kg N ha -1 as single species and 113.00 kg N ha -1 in a mixture with winter rye [ 27 ]. A much wider range from 50.00 kg N ha -1 to 300.00 kg N ha -1 was found by Kaye and Quemada [ 22 ]. Wittwer et al. [ 18 ] showed that legumes as a single species cover crop can increase nitrogen uptake of maize by 32.00 kg N ha -1 and as part of cover crop mixtures by 28.00 kg N ha -1 . The summarized literature resulted in a weighted mean of 52.49 kg N ha -1 (95% CI, 32.06, 72.92) that can be contributed by legumes from nitrogen fixation.

3.4. Reduced nitrogen leaching

Cover crops prevent nutrient leaching over winter, especially of mineral nitrogen (N min ) that otherwise would be leached from the soil profile. However, this leaching reduction strongly depends on the timing of when cover crop are planted and type of cover crop. Early sown oil radish reduces leaching in the fall and winter months [ 28 ]. Rye as an over-wintering cover crop can better protect nitrogen from leaching in the spring [ 28 ]. Non-legume cover crops and mixtures can protect up to 100.00 kg N ha -1 from leaching, while pure legumes can protect between 60.00 to 70.00 kg N ha -1 [ 6 , 22 ]. Abdalla et al. [ 25 ] show that legume cover crops prevent 18.00 kg N ha -1 from leaching, non-legume cover crops 38.00 kg N ha -1 , and cover crop mixtures 19.00 kg N ha -1 . A study by McCracken et al. [ 29 ] resulted in an average leaching reduction of 35.80 kg N ha -1 . The amount of scavenged nitrogen depends heavily on water availability and soil type. Early sowing and sufficient precipitation enable cover crops to develop faster, establish more biomass, and absorb more nitrogen in the fall. The tillage system also affects the amount of scavenged nitorgen. The faster mineralization in conventional tillage systems in autumn resulted in higher N min stocks and higher nitrogen uptake from cover crops than in no-till systems [ 30 ]. Literature research resulted in a weighted mean value of 38.82 kg N ha -1 (95% CI, 19.13, 58.51) of scavenged nitrogen available to the crop following the cover crop.

3.5. Fertilizer emissions

Nitrogen fertilizer emissions are caused by different factors and vary between fertilizer types. About half of the CO 2 e emissions of nitrogen fertilizer is N 2 O emissions from soil after application and about one-third of all emissions occur during the production process of fertilizer itself. The remaining emissions are divided into N 2 O emissions from NH 4 + and NO 3 - losses and CO 2 from lime [ 31 ]. Total emissions per kg of nitrogen also vary between fertilizer types and the literature. For example, Hasler et al. [ 32 ] reported 8.69 kg CO 2 e kg -1 N for urea fertilizer to 11.64 kg CO 2 e kg -1 N for CaH 4 N 4 O 9 fertilizer. A much higher emission factor of 15.00 to 31.00 kg CO 2 e kg -1 N is used by Kahrl et al. [ 33 ]. The mean value of all studies considered was 11.23 kg CO 2 e kg -1 N (95% CI, 9.02, 13.43). Emissions from organic fertilizers were not considered.

3.6. Reduced indirect N 2 O emissions due to less leaching

Leached nitrogen is deposited into aquatic ecosystems and represents a globally significant source of N 2 O through indirect emissions. These emissions can be calculated using the IPCC emission factor EF 5 , which incorporates three components: EF 5g (groundwater and surface drainage), EF 5r (rivers) and EF 5e (estuaries) [ 34 ].

The IPCC emission factor EF 5 amounts to 0.0075 and is the sum of EF 5g , EF 5r and EF 5e with a value of 0.0025 each. Tian et al. [ 34 ] suggest a higher emission factor for EF 5g of 0.0060, the other two factors are almost the same as those suggested by IPCC in 2006. Here, we use the mean of two results: One using the IPPC factor which results in 0.08 Mg CO 2 -eq ha -1 and the other one using the factor of Tian et al. [ 34 ] which results in 0.12 Mg CO 2 -eq ha -1 . The mean of both values leads to an average climate benefit caused by reduced indirect N 2 O emissions due to less leaching of 0.10 Mg CO 2 -eq ha -1 (95% CI, -0.15, 0.35).

3.7. Albedo change

When soil is covered with cover crops, less solar radiation reaches the soil surface compared to fallow land. Thus, the albedo value of plants is higher than that of fallow soil. Due to this reduced net radiation, there is a cooling effect that impacts the global climate. However, the albedo value of fallow soil strongly depends on soil type and condition. In particular, the color and moisture content of the soil play important roles. Dark and moist soils have a lower albedo than light dry soils, so there is a wide variation in the albedo value of fallow land. Since there is often a high soil moisture level during the growth period of cover crops (in fall and winter) the albedo effect of covering the soil with cover crops is stronger than for the yearly average [ 14 ]. Unfortunately, research on albedo effects of cover crops is in its infancy and only two adequate publications were found. The albedo effect of cover crops ranges from -4.00 to 10.00 W m -2 was calculated by Kaye and Quemada [ 22 ]. Converted to CO 2 e, this corresponds to a climate benefit of 0.25 Mg CO 2 e ha -1 a -1 . Carrer et al. [ 14 ] show that three months of cover cropping in Europe results in a climate benefit of 0.16 Mg CO 2 e ha -1 a -1 . Similarly, this study found that longer time periods with cover cropping would increase the mitigation potential by 27.0%. Overall, a mean climate benefit of 0.20 Mg CO 2 e ha -1 a -1 (95% CI, -0.37, 0.78) was identified in the considered literature for the albedo change of cover crops.

3.8. Nitrous oxide emissions

Cover cropping can increase N 2 O emissions under certain weather conditions compared to fallow land depending on the fertilizer N rate, soil incorporation, and the period of measurement and rainfall [ 35 ].There are many factors that influence the level of N 2 O emissions which leads to high variability from this GHG emission source. A prerequisite for cover crops is high soil moisture and water saturation, or at least water saturation of the upper soil layers. Another factor is the C/N ratio of the cover crop, which influences how fast cover crop residues decompose. Cover crops with low C/N ratios emit more N 2 O than cover crops with high C/N ratios [ 36 , 37 ]. Another factor influencing N 2 O emissions is the treatment of cover crop residues. Incorporating residues into the soil leads to higher N 2 O emissions as compared to leaving cover crop residues decaying on the soil surface [ 36 ]. Air temperature also effects N 2 O emissions. As temperatures increase, N 2 O emissions from cover crops also increase. Overall, air temperature accounts for 22.0% of the variability in N 2 O emissions [ 38 ]. In a meta-analysis, Basche et al. [ 35 ] found that N 2 O emissions increased in 60.0% and decreased in 40.0% of the publications when cover cropping was practiced. The overall conclusion of the meta-analysis is that cover cropping increases N 2 O emissions only to a very small extent and that the variability is very large. For example, compared to a chemical fallow system, Olofsson and Ernfors [ 39 ] identified the highest value with 1.80 kg N 2 O-N ha -1 for oilseed radish, whereas Preza-Fontes et al. [ 40 ] identified the lowest emissions with -0.54 kg N 2 O-N ha -1 for a sorghum-sudan-grass-mixture. The result of our calculation based on a systematic literature search also shows only a very small increase in N 2 O emissions from cover cropping. The determined weighted mean value of emissions, as displayed in Table 2 , is 0.13 kg N 2 O-N ha -1 , which is equivalent to 0.04 Mg CO 2 e ha -1 (95% CI, -0.02, 0.09).

3.9. Foregone benefits due to cover crop seed land use

Land use for producing seeds for cover crops was calculated for the species phacelia, mustard, clover, and oat as representatives of the most important plant families used as cover crops. Their average was used for further calculations. The average land use requirement to produce one ha of cover crop seeds was calculated as 0.02 ha (95% CI, 0.00, 0.04).

We assume that the land used for the production of cover crop seeds would otherwise be used for wheat production. Wheat production on land in the EU offers a carbon benefit that consists of: (1) the opportunity that the wheat output enables storing carbon elsewhere (yield × carbon opportunity cost); and (2) savings in global production emissions due to lower production emissions in the EU compared to the global average (here, the difference between Swedish and global wheat production emissions is based on Searchinger et al. [ 11 ]). Other factors, like changes in soil organic carbon or bioenergy benefits are not considered here. The climate benefit of wheat consisting of factors (1) and (2) is forgone due to land requirements for cover crops’ seed requirements and can be quantified accordingly to a mean value of 0.28 Mg CO 2 e ha -1 (95% CI, 0.27, 0.29).

3.10. Production emissions for cover crop seed production

Since no specific literature sources for seed production emissions could be found for typical cover crop species, emissions from corn, spring wheat, and canola seed production are used in this study. Hybrid corn seed production in China leads to emissions of 1,459.00 kg CO 2 e Mg -1 , whereas in the U.S. it causes 2,250.50 kg CO 2 e Mg -1 [ 17 , 41 ] of emissions. Seed production of rapeseed in Poland causes slightly lower emissions of 1,014.00 kg CO 2 e Mg -1 [ 42 ]. In contrast, for spring wheat, it is only 580.00 kg CO 2 e Mg -1 in Southwest Finland and 680.00 kg CO 2 e Mg -1 in Northern Savonia (Finland) [ 43 ]. These emissions mostly depend on the amount of fertilizer used since fertilization is responsible for the majority of production emissions, especially the production and application of nitrogen fertilizers [ 17 ]. The weighted average value used for our calculation is 1,066.26 kg CO 2 e Mg -1 (95% CI, 219.56, 1912.95). For the emissions of processing, packaging, and transporting cover crop seeds, only one literature source for corn seed could be found. The emissions here are 213.00 kg CO 2 e Mg -1 [ 44 ].

3.11. Additional machinery operations for cover crop establishment

We assume that cover crop establishment requires either tillage with a plow or cultivator followed by seeding. In addition, it is assumed that the only relevant emission from these machinery operations is from burning fossil diesel fuel. Based on data of an internet database from KTBL [ 45 ], plowing plus seeding is estimated at 55.00 liter diesel fuel ha -1 , while cultivator tillage and seeding is estimated at 45.00 liter diesel fuel ha -1 . The variability of the machinery operation intensity and corresponding fuel consumption was analyzed by Wittwer et al. [ 18 ]. In this study, diesel fuel consumption ranges from 22.00 l ha -1 for no-till systems to 61.00 l ha -1 for conventional intensive tillage systems. In organic farming, diesel fuel consumption ranges from 32.00 l ha -1 for reduced tillage to 55.00 l ha -1 for intensive tillage. The average diesel fuel consumption used in this study was calculated as 45.29 l ha -1 (95% CI, 32.43, 58.13).

The emission factor per liter of diesel fuel ranges from 3.00 kg CO 2 e l -1 [ 44 ] to 3.31 kg CO 2 e l -1 [ 46 ]. The average emissions were calculated as 3.13 kg CO 2 e l -1 (95% CI, 2.92, 3.34) diesel fuel. The additional machinery operations thus cause emissions of 0.14 Mg CO 2 e ha -1 (95% CI, 0.10, 0.18).

3.12. A factor not considered: Erosion reduction

According to Lugato et al. [ 47 ], soil erosion can lead to a loss of soil carbon, lowering the carbon sink capacity of soils. Additionally, soil erosion can disturb the soil structure and reduce soil fertility, which disconnects soil element cycles and further contributes to GHG emissions. However, the extent to which soil erosion leads to higher carbon fluxes out of the system depends on the specific context and interplay of many factors [ 48 ].

Cover crops protect soil erosion during the fall and winter and also after the establishment of the following crop, such as maize, due to remaining cover crop residues [ 49 ]. According to Laloy and Bielders [ 49 ] and Gentsch et al. [ 6 ], Cover crops increase the infiltration rate and improve soil structure, allowing the soil to absorb more water without eroding. According to Panagos et al. [ 15 ], cover crops reduce soil erosion by at least 20.0% in Europe and the United Kingdom. Machiwal et al. [ 50 ] found a reduction in soil loss of 33.0% to 77.0%, depending on the cover crop type for India. The reduction in soil erosion is highly dependent on the slope and management of the land. In addition, the soil type also plays a major role.

Given the uncertainty between soil erosion and fluxes from the soil system as well as the varying factors leading to soil erosion, we have not included climate benefits of soil erosion prevention from cover crops in our calculations.

3.13. Net climate change mitigation impact (NCCMI) of cover crops

We calculate the summary of all climate benefits from cover crops as 4.23 Mg CO 2 e ha -1 a -1 (95%CI, 1.25, 7.49) and all climate costs from cover crops as 0.93 Mg CO 2 -eq ha -1 a -1 (95% CI 0.51, 1.34). The NCCMI of cover crops was calculated as 3.30 Mg CO 2 e ha -1 a -1 ( Table 3 ). The NCCMI was then extrapolated to the maize harvest area for all EU-27 countries. Here, we assume a scenario in which cover crops are grown before maize on all of the EU-27’s harvested maize areas, which is 15,092 x 10 6 ha, on average [ 23 ]. Based on this calculation, planting cover crops before maize in the EU-27 results in a climate change mitigation potential of 49.80 million Mg CO 2 e a -1 . This is equivalent to 13.0% of the EU-27’s agricultural GHG emissions [ 51 ].

3.14 Sensitivity analysis based NCCMI scenarios

The impact factors “carbon land benefit based on yield gain” and “carbon sequestration” have a high impact on NCCMI but also show a high uncertainty. To address this uncertainty, we use four scenarios for NCCMI to analyze the sensitivity of the results:

A) Base scenario as shown in section 3.13

B) Base scenario less carbon land benefit based on yield gain

C) Base scenario less carbon sequestration

D) Base scenario less carbon land benefit based on yield gain and less carbon sequestration

4. Discussion

4.1. review of results.

The results of this study indicate that the climate benefits of cover crops significantly exceed their climate costs. This resulted in a positive NCCMI of 3.30 Mg CO 2 e ha -1 a -1 that can be achieved if cover crops were incorporated in crop rotations of maize production. The major contributor to climate benefits is through carbon land benefits based on yield gain for maize following a cover crop, which alone contributed to 33.8% of all climate benefits. Several meta studies [ 9 , 10 ] showed that cover crops increase soil organic carbon stocks, with an average organic carbon sequestration rate of 1.43 Mg ha -1 a -1 . The most important mechanism behind this is the stimulation of microbial activity from cover crops’ organic matter input. Litter from shoots and roots, rhizodeposits, and the transport of photoassimilate to the rhizosphere during the growth of cover crops results in a higher and more active microbial biomass [ 52 ]. These processes resulted in microbial derived organic substances that are key to build up mineral associated organic matter fractions with prolonged turnover times [ 53 ]. The activation of microbial cycling that derived from higher organic matter input rates is therefore a strong indirect factor of the climate benefits from cover crops. Carbon sequestration was the second largest contributor (34.5%) to climate benefits. The results indicate a maize yield increase of 8.8% by following a cover crop. Since maize yield gains are higher following legume cover crops and in organic systems, it can be assumed that increased nutrient availability is one of the key factors driving crop yield gains from cover crops. Cover crops might help in closing the yield gap between organic and conventional systems, as well as in improving the resilience of arable production under climate change. However, yield benefits depend on the quality of cover crop residues and reach its maximum at litter C/N ratios <25 [ 54 ]. Closer nutrient cycling and reduction of leaching losses resulted in another 24.3% of cover crops’ climate benefits, including nitrogen fixation of legume cover crops. The highest maize yield gains were found for legume-based cover crops while graminoid cover crops showed only minor effects. For example, Marcillo and Miguez [ 24 ] found that a grass cover crop has no influence on maize yield. In the same study, a legume-only mixture shows up to a 21.0% yield gain in the maize crop following the cover crop. Wittwer et al. [ 18 ] confirmed that a legume-free cover crop mixture leads to only a 3.0% increase in maize yield. Mixtures of legumes and grasses as cover crops enable yield gains from 1.3% [ 55 ] to 21.0% [ 56 ], respectively. However, cover crops can also have negative effects on the subsequent maize yield. Hunter et al. [ 57 ] showed that a high carbon to nitrogen (C/N) ratio in spring cover crops resulted in a lower yield of silage maize. Nutrient use efficiency has been demonstrated to increase through cover crops that are in crop rotations for several crops, including maize [ 58 – 60 ]. The inclusion of legumes increases cover crops’ litter quality and crop yield benefits; however, pure legume stands are less effective to prevent nitrogen leaching over the winter [ 6 ]. The inclusion of cover crops in crop rotations, therefore, requires a high degree of management by selection of suitable cover crop species or mixtures to maximize their green manure and environmental benefits.

Cover crops are able to change the amount of incoming shortwave radiation that is reflected back to the atmosphere and thereby mitigate warming [ 22 ]. Albedo change through cover crops’ land cover has the smallest contribution (4.5%) to the climate benefits from cover crops. The systematic literature search resulted in only two publications that analyze albedo change through cover crops. Both found a slight climate change mitigating effect through radiative forcing changes induced by an increase in surface albedo.

Climate costs of cover crops were nearly six times lower than climate benefits and are mainly dominated by cover crops’ seed production emissions and foregone benefits due to cover crops’ seed land use (accounting for 41.9% and 30.1%, respectively, of the total climate costs of cover crops). Interestingly, additional machinery operations and N 2 O emissions from cover crops’ decomposition contributed minorly to climate costs (15.0% and 4.3%, respectively). Emissions of N 2 O have a 280 times higher global warming potential compared to CO 2 . Therefore, the latest studies were alarmed about the emission potential that can appear from decomposition of cover crop residues [ 35 ]. However, N 2 O emissions are of episodic nature and depend on extended precipitation events. Despite this, N 2 O emissions from cover crops’ decomposition can be further reduced if cover crop residues were not incorporated into the soil [ 35 ]. With this respect, no-till operations would further reduce the N 2 O emissions factor.

We created four scenarios where we assumed that not all positive impacts of cover cropping might be present at the same time. We removed the major contributors: C sequestration (B) and yield gain (C) or both together (D). All scenarios kept a positive NCCMI ( Fig 3 ). Therefore, we conclude that positive aspects of cover cropping always superimpose the negative impacts.

Numbers are given as Mg CO 2 e ha -1 .

https://doi.org/10.1371/journal.pone.0302139.g003

All scenarios show a positive NCCMI.

4.2. Comparing overall results to existing literature

In contrast to Kaye and Quemada [ 22 ], this study is first to include land use effects based on the yield gain caused by cover crops. Furthermore, our study uses a systematic literature review and quantifies the climate change mitigation impact for all of EU-27, which demonstrates the magnitude of climate change mitigation opportunities of cover crops. So far no other literature has extrapolated the climate change mitigation impact of cover crops to a country or region. Overall, Kaye and Quemada [ 22 ] found a climate change mitigation effect of 1.16–1.35 Mg CO 2 e ha -1 a -1 from cover crops, which is lower than that calculated in this study. This discrepancy is a result of different analyzed literature and the inclusion of land use effects in our research. In addition, Abdalla et al. [ 25 ] showed a slightly lower climate change mitigation impact from cover crops compared to our results of 2.06 Mg CO 2 e ha −1 a −1 (95% CI -0.04, 4.16). The study, however, does not consider land use change effects (1.51 Mg CO 2 e ha -1 a -1 in our study), albedo change, emissions for cover crop seed production, and additional machinery operations. If the study would have considered these factors, their results would be more comparable to those in our study.

4.3. Limitations

A limitation of this study is that we did not include erosion reduction of cover crops as a climate benefit due to the high data variability and uncertainty of its climate impact. Furthermore, the use of carbon opportunity cost as suggested by Searchinger at al. [ 11 ] is criticized by some authors for separating supply and demand side efficiencies and including supply and demand side interactions [ 61 , 62 ]. Despite this criticism, carbon opportunity cost is a widely used approach to quantify changes in efficiency of land use for mitigating climate change. Given that land use change is still the highest source of emissions in the global agri-food sector [ 2 ], carbon opportunity cost based on Searchinger at al. [ 11 ] is an adequate land use change quantification approach for changes in maize yield.

For the climate impact of land use for cover crop seed production, we use the forgone climate benefit of wheat based on Searchinger et al. [ 11 ]. Here, the same arguments discussed above for using carbon opportunity costs are relevant. We assume wheat as the displaced crop when cover crop seeds are produced since wheat is the crop with the largest acreage in the European Union [ 23 ]. For additional machinery operations to establish cover crops, we only consider diesel fuel emissions. There are also emissions for producing, maintaining, and repairing agricultural machinery, but in the majority of cases, existing machinery is used for cover crop establishment, i.e., no additional machinery is produced to establish cover crops. In this study, we only evaluated maize as the crop to follow cover crops. Maize is the largest spring crop by acreage in the European Union [ 23 ] and the most investigated crop in the scientific literature with a good data base. Despite this, other spring crops like oats, spring barley, sunflower, or sugar beet are investigated for the benefits of winter cover crops in the European Union. More data is needed to complete the view on climate benefits of cover crops based on different main crops.

4.4. Conclusion and policy recommendations

This is the first study to include all relevant climate change impacting effects of cover crops in a comprehensive calculation and to extrapolate the NCCMI of cover crops to the whole maize cropping area of the EU-27. We show that cover crops are powerful tools to mitigate climate change impacts from European agriculture, which make our findings very relevant for political decisions in the EU. If all maize cropping acreage in the EU-27 were to include cover crops, GHG emissions from EU-27 agriculture could be reduced by 13.0%. Based on this result, we recommend that the Common Agricultural Policy (CAP) of the European Union should continue to accelerate the integration of cover crops into farming. The current CAP (2023–2027) does not include regulations that make cover crops before spring crops mandatory or provide incentives so the area devoted to cover crops in the EU is maximized. There are conditionality requirements, such as obligatory soil cover in the winter for 80% of a farm’s arable land. Therefore, if a farm has 80% winter crops and 20% spring crops in its rotation, there is no requirement to grow cover crops under the current CAP for this farm [ 63 ].

Our results recommend a stronger commitment from the EU’s agricultural policy to make cover crops before spring crops a common practice on all farms. This will not only help to achieve the EU’s climate protection goals, but also global targets in the Paris Agreement.

5. Statistics

The weighted mean was calculated from study values using the number of observations as the weighting factor. Mean values are followed by the 95% confidence intervals (CI) and are shown in brackets (lower CI limit, upper CI limit). All data collected from the literature as well as the calculations shown in Table 3 are provided as supplementary material ( S1 File ).

Forest plots were produced with the R package [ 64 ] with R version 4.3.2 [ 65 ]. Detailed description of the statistic parameters are outlined in [ 66 ].

Supporting information

S1 file. calculations..

https://doi.org/10.1371/journal.pone.0302139.s001

S2 File. Included literature.

https://doi.org/10.1371/journal.pone.0302139.s002

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Article publication date: 14 December 2021

Issue publication date: 29 November 2022

The purpose of the paper is to perform a review and analyze the literature on lean accounting (LA) to develop insights into how LA research is developing, offering a critique of the research to date and underlining future research opportunities.

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Acknowledgements

Disclosure statement : No potential conflict of interest was reported by the authors.

Alves, R.F. , Vieira Neto, J. , de Mattos Nascimento, D.L. , de Andrade, F.E. , Tortorella, G.L. and Garza-Reyes, J.A. (2022), "Lean accounting: a structured literature review", The TQM Journal , Vol. 34 No. 6, pp. 1547-1571. https://doi.org/10.1108/TQM-06-2021-0185

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A giant peripheral ossifying fibroma of the maxilla with extreme difficulty in clinical differentiation from malignancy: a case report and review of the literature

• Ryo Takagi 1 ,
• Kosei Mori 1 ,
• Takashi Koike 1 ,
• Sayumi Tsuyuguchi 1 ,
• Kengo Kanai 1 ,
• Yoshihiro Watanabe 1 ,
• Mitsuhiro Okano 1 ,
• Yoshihiro Noguchi 1 ,
• Aya Tanaka 2 ,
• Kinue Kurihara 2 ,
• Kazumichi Sato 2 ,
• Ken Ishizaki 2 ,
• Yuichiro Hayashi 3 &
• Yorihisa Imanishi   ORCID: orcid.org/0000-0003-0047-7987 1  

Journal of Medical Case Reports volume  18 , Article number:  220 ( 2024 ) Cite this article

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Peripheral ossifying fibroma is a nonneoplastic inflammatory hyperplasia that originates in the periodontal ligament or periosteum in response to chronic mechanical irritation. Peripheral ossifying fibroma develops more commonly in young females as a solitary, slow-growing, exophytic nodular mass of the gingiva, no more than 2 cm in diameter. While various synonyms have been used to refer to peripheral ossifying fibroma, very similar names have also been applied to neoplastic diseases that are pathologically distinct from peripheral ossifying fibroma, causing considerable nomenclatural confusion. Herein, we report our experience with an unusual giant peripheral ossifying fibroma with a differential diagnostic challenge in distinguishing it from a malignancy.

Case presentation

A 68-year-old Japanese male was referred to our department with a suspected gingival malignancy presenting with an elastic hard, pedunculated, exophytic mass 60 mm in diameter in the right maxillary gingiva. In addition to computed tomography showing extensive bone destruction in the right maxillary alveolus, positron emission tomography with computed tomography revealed fluorodeoxyglucose hyperaccumulation in the gingival lesion. Although these clinical findings were highly suggestive of malignancy, repeated preoperative biopsies showed no evidence of malignancy. Since even intraoperative frozen histological examination revealed no malignancy, surgical resection was performed in the form of partial maxillectomy for benign disease, followed by thorough curettage of the surrounding granulation tissue and alveolar bone. Histologically, the excised mass consisted primarily of a fibrous component with sparse proliferation of atypical fibroblast-like cells, partly comprising ossification, leading to a final diagnosis of peripheral ossifying fibroma. No relapse was observed at the 10-month follow-up.

Conclusions

The clinical presentation of giant peripheral ossifying fibromas can make the differential diagnosis from malignancy difficult. Proper diagnosis relies on recognition of the characteristic histopathology and identification of the underlying chronic mechanical stimuli, while successful treatment mandates complete excision of the lesion and optimization of oral hygiene. Complicated terminological issues associated with peripheral ossifying fibroma require appropriate interpretation and sufficient awareness of the disease names to avoid diagnostic confusion and provide optimal management.

Peer Review reports

Peripheral ossifying fibroma (POF) is a nonneoplastic inflammatory hyperplasia, that is, a reactive proliferative lesion that arises in the superficial or periapical gingiva, induced by diverse chronic mechanical irritations such as dental calculus, bacterial plaque, orthodontic appliances, ill-fitting crowns and dentures, and improper restorations [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. POF is believed to originate from pluripotent cells of the periodontal ligament or periosteum that can be metaplastically transformed into osteoblasts, cementoblasts, or fibroblasts in response to the aforementioned chronic stimuli [ 1 , 5 , 7 , 9 ]. The histopathology is characterized by fibrous connective tissue with varying numbers of fibroblasts associated with the formation of variable amounts of mineralized products consisting of bone components (woven and lamellar bones), cementum-like material, dystrophic calcification, or a combination thereof [ 1 , 2 , 3 , 4 , 5 , 6 , 8 , 10 ]. Although the immunohistochemical profile of POF has been sparsely documented, spindle-shaped cells in POF have been shown to be positive for smooth muscle actin (SMA) in most cases, suggesting a myofibroblastic nature of the lesion [ 8 , 11 ].

Clinically, POF usually presents as a painless, solitary, slow-growing, relatively well-defined, pedunculated or sessile, exophytic nodular mass of the gingiva [ 2 , 4 , 5 , 6 , 7 , 8 , 9 , 12 , 13 , 14 ]. Epidemiologically, POF develops more commonly in females than in males, mainly during the second to third decades of life, and is predominantly located in the anterior maxilla, especially in the interdental papilla of the incisors [ 1 , 2 , 4 , 5 , 6 , 7 , 8 , 13 ]. Regarding the size, most cases are no more than 2 cm in diameter [ 2 , 5 , 6 , 7 , 8 , 9 , 12 , 13 , 14 , 15 ]; however, very rare cases of POF with unusually marked enlargement (≥ 6 cm) have been reported [ 11 , 16 , 17 , 18 , 19 ], which often require careful differential diagnosis to distinguish them from malignancy.

In clinical practice, there have been nomenclature problems wherein various synonyms have been used to refer to POF, while very similar names also have been applied to neoplastic diseases pathologically distinct from POF, causing considerable confusion among the relevant physicians [ 2 , 4 , 5 , 6 , 10 , 12 , 13 , 20 ].

Here, we report our experience with an unusual giant POF of the maxillary gingiva with a differential diagnostic challenge by reviewing its clinical course and discussing the issues of terminology that should be considered to properly recognize the disease concept of POF.

A 68-year-old Japanese male presented to our department with an exophytic mass on the right side of the maxillary gingiva that appeared 6 months earlier and had rapidly increased in size. He reported that, although he had upper and lower dentures made by a local dentist approximately 3 years ago, he gave up wearing the upper denture after approximately 6 months because it gradually became ill-fitting. His medical history included high blood pressure and hyperuricemia with orally administered regular medications. He smoked 20 cigarettes per day for more than 35 years and drank 500 mL of beer per day on average for more than 35 years.

Intraoral inspection revealed an elastic hard, seemingly well-defined, nonhemorrhagic, and almost pedunculated exophytic mass, approximately 60 mm in maximal diameter, extending medially from the hard palate, posteriorly to the retromolar trigone, and laterally to the buccal mucosa, which surrounded the right maxillary gingiva, including the right upper molars (teeth 16 and 17) (Fig.  1 A, B). The lesion was painless, and its surface appeared superficially multilobulated and slightly roughened, with some erosions and shallow ulcerations. More than half of the permanent teeth were missing in both the upper and lower jaws, resulting in only five healthy teeth (parts of the maxillary incisors, and the mandibular incisors and cuspids) (Fig.  1 C). Cervical palpation found lymphadenopathy of approximately 15 mm in size in the right submandibular region.

Intraoral and panorama-radiographic findings. A and B An elastic hard, seemingly well-defined, pedunculated exophytic tumor-like mass with a maximal diameter of approximately 60 mm was observed surrounding the right upper gingiva, including the right upper molars, extending medially from the hard palate, posteriorly to the retromolar trigone, and laterally to the buccal mucosa. C Orthopantomogram showing that all the remaining molars and premolars, including those surrounded by the right upper gingival mass, had severe alveolar bone resorption, indicating severe chronic periodontitis

An orthopantomogram revealed that, except for the aforementioned healthy teeth, all the remaining molars and premolars, including the molars surrounded by the right upper gingival mass, had severe alveolar bone resorption, indicating that the patient had severe chronic periodontitis (Fig.  1 C). Contrast-enhanced computed tomography (CT) revealed extensive bone destruction on the lateral side of the right maxillary alveolus along the medial side of the mass lesion, together with small calcifications anteriorly within the mass (Fig.  2 A, B). Multiple enlarged lymph nodes, nearly 20 mm in diameter, were also found in the level I–II region of the right side of the neck (Fig.  2 C). Positron emission tomography with CT (PET/CT) revealed noticeable fluorodeoxyglucose (FDG) accumulation (maximum standardized uptake value [SUVmax] 14.81) in the area consistent with the right maxillary gingival mass containing chronic periodontitis (Fig.  2 D, E), whereas the right cervical level I–II lymph nodes showed only a relatively mild increase in FDG accumulation (Fig.  2 F).

CT and PET/CT findings. A – C CT image showing a marked bone destruction-like defect on the lateral side of the right maxillary alveolus (arrowhead, A ) contiguous with the right maxillary gingival mass lesion (arrows, A and B ), along with small calcifications (arrowhead, B ) anteriorly within the mass. Multiple enlarged lymph nodes, nearly 20 mm in length, were observed in the level I–II region of the right side of the neck (arrows, C ). D – F PET/CT scan demonstrating FDG hyperaccumulation (SUVmax = 14.81) in the right maxilla in an area consistent with the gingival lesion containing chronic periodontitis ( D and E ). Only mild FDG accumulation was observed in the cervical lymph nodes (arrows, F )

Initial biopsy was performed from the palatal and buccal sides of the surface of the mass, both of which showed “granulation tissue associated with marked inflammatory cell infiltration.” Because the imaging findings suggested a high probability of malignancy, a second biopsy was performed deeper into the lesion; however, the histology showed “severe chronic inflammatory cell infiltration and fibrous connective tissue hyperplasia with some bone tissue involvement,” again with no malignancy. Although pancytokeratin immunostaining was performed, no atypical epithelial cells were observed. At this stage, we additionally considered the possibility of reactive hyperplastic lesions [ 3 , 4 ] on the gingiva as a differential diagnosis; however, the possibility of malignancy could not be excluded as a pretreatment diagnosis in light of the above-mentioned findings.

Since surgical resection appeared indispensable regardless of the exact diagnosis, the patient underwent surgery under general anesthesia as a treatment that also served as a definitive diagnosis. Prior to surgery, the aforementioned inactive teeth with severe chronic periodontitis, except for the right maxillary molars contiguous with the lesion, were extracted by a dentist. During surgery, first of all, the two remaining right upper molars and one premolar surrounded by the gingival mass were extracted (Fig.  3 A). Then, several small specimens of the mass were excised from the tissue around the extraction socket corresponding to the deepest portion of the lesion and subjected to intraoperative frozen histological examination. Like the preoperative histological findings, all biopsied specimens showed “inflammatory granulation tissue with fibrosis and small calcification” without any malignancy, leading to a provisional diagnosis of ruling out the possibility of malignancy. Accordingly, we decided to perform a procedure similar to partial maxillectomy for benign lesions with minimal resection margins and omitted neck dissection.

Intraoperative findings. A Preoperative appearance of the right maxillary gingival mass lesion. B Intraoperative view after resection of the pedunculated gingival mass. The base of the mass was almost confined to the gingival mucosa. The remaining granulation tissues around the resection margin and surrounding alveolar bone were thoroughly curetted (arrow: preserved mucosa elevated from the alveolar bone). C The wound surface was covered by a polyglycolic acid sheet with fibrin glue. D Following additional covering with a sheet of chitin (poly- N -acetylglucosamine)-coated gauze (arrow), an immediate surgical obturator (ISO; arrowhead, transparent in color) was placed

As resection proceeded, the base of the pedunculated mass was found to be almost confined to the gingival mucosal surface, with the surrounding mucosa remaining normal. After removing the main mass, sufficient detachment and elevation of the surrounding normal mucosa from the periosteum were followed by thorough curettage of the remaining granulation tissues around the resection margin (Fig.  3 B). The alveolar bone was sufficiently shaved until a healthy bone margin was exposed, with additional scraping of the sharp edges. Although the bone defect in the maxillary sinus floor extended to approximately 10 mm, the sinus mucosa was preserved without perforation. After meticulous hemostasis, the wound surface was covered by a polyglycolic acid sheet (NEOVEIL Nano Ⓡ D10, Gunze Medical, Japan) with fibrin glue (Fig.  3 C) and then with a sheet of chitin (poly- N -acetylglucosamine)-coated gauze. An immediate surgical obturator (ISO), premade by the dentist, was placed immediately after surgery (Fig.  3 D). The excised mass was partially lobulated and measured approximately 60 × 36 × 17 mm (Fig.  4 A).

Histopathological findings. A The excised mass was partially lobulated and measured approximately 60 × 36 × 17 mm. B – D Hematoxylin and eosin staining. The histology consisted primarily of a fibrous component with myxoid degeneration and sparse proliferation of atypical fibroblast-like cells ( B ), partly comprising cementum-like ossification and calcification ( C ), without any atypia, even in the superficial squamous epithelium ( D ), leading to a final diagnosis of POF

The histology of the excised mass consisted primarily of a fibrous component with myxoid degeneration and sparse proliferation of atypical fibroblast-like spindle-shaped cells (Fig.  4 B), partly comprising cementum-like ossification and calcification (Fig.  4 C). No atypia was observed, even in the superficial squamous epithelium (Fig.  4 D). Immunostaining revealed mild positivity for SMA in the spindle-shaped cells, whereas S100, desmin, and CD34 were negative. Pancytokeratin staining, for which a positive is suggestive of odontogenic epithelium, was also negative. Based on these histological findings, a final diagnosis of POF was made.

The surgical wound healed uneventfully with granulation and reepithelialization, thereby maintaining the shape of the alveolar ridge. Three months after surgery, the patient regained the ability to consume a regular diet with the help of dentures remade by the dentist. No relapse or other complications were observed at the 10-month postoperative follow-up (Fig.  5 ).

Comparison between pre- and postoperative findings. A and B Right maxillary gingival lesion site preoperatively ( A ) and 3 months postoperatively ( B ). C and D Coronal CT images preoperatively ( C arrow: POF lesion) and 4 months postoperatively ( D a fistula due to the bone defect of the maxillary sinus floor closed spontaneously)

We reviewed the POF case series previously reported in various countries and summarized the epidemiological and clinical features (sex, age, site of occurrence, and size) of POF in Table  1 [ 2 , 4 , 6 , 7 , 8 , 9 , 14 , 15 , 21 ]. There were sex differences with consistent female dominance, except in one report [ 7 ], wherein the female-to-male ratio varied substantially, ranging from 1.3 to 3.5. The second to fourth decades of life were common susceptible ages, with 30s being the average age, and a gradual declining trend in the ratio with aging after 40 years was apparent in large-scale reports [ 4 , 14 ]. While the occurrence sites were distributed entirely across the upper and lower gingiva, the majority of studies indicated that the anterior maxilla (incisors and cuspids) was the most common site [ 2 , 4 , 6 , 9 , 14 , 21 ]. While the size of lesions ranged quite widely, most studies have reported an average size of 1–2 cm [ 2 , 6 , 8 , 14 , 15 ] and a maximum diameter of no more than 3 cm [ 2 , 9 , 15 , 21 ] or 5 cm [ 6 , 8 ] (except for a report with unknown data [ 4 ]).

The patient in this report was relatively “elderly” (68 years old) and male, with the lesion located on “the posterior maxilla”; although self-reported, the mass “had grown rapidly to over 6 cm in diameter within 6 months of its initial appearance,” all of which appeared unusual for a POF. In addition, because of the patient’s substantial history of smoking, alcohol consumption, and extremely poor oral hygiene, malignancy was strongly suspected. After treatment, when asked about the history of denture use in detail, the patient told us that, although he had quit using his upper denture due to ill-fitting, he continued to wear only his lower denture for more than 2 years to avoid eating difficulties. Accordingly, inappropriate denture use habits, in which the lower denture provided unnatural chronic mechanical stimulation to the maxillary gingiva during mastication, were suggested to be critical triggering factors for POF development. However, even if we had been aware of this episode from the beginning, there would not have been sufficient evidence to rule out malignancy before treatment.

Regarding the imaging findings of POF, the identification of radiopaque calcified foci via X-ray or CT is likely helpful in differential diagnosis; however, its sensitivity is not sufficient because the amount of calcified tissue varies depending on the patient [ 5 , 7 ]. Although the preexisting bone structure seldom changes except for compression-associated superficial concave defects and occasional tooth displacement, lesions that have increased in size over time may occasionally present with erosion or even destruction of the bone surface [ 6 , 7 , 9 ]. In the present case, the orthopantomogram showed no radiopaque calcified foci within the lesion, whereas CT displayed a very small number of calcified components in a limited portion of the lesion. However, its small size was not highly indicative of POF, even in hindsight. The marked bone destruction of the maxillary alveolus adjacent to the lesion shown on CT, together with the hyperaccumulation of FDG revealed on PET/CT, appeared to be rather more suggestive of malignancy. In contrast, the findings of preoperative tissue biopsies were, as it turns out, all consistent with POF. Considering that small bone fragments (cementum-like ossification) were contained within the lesion in the second biopsy obtained from a deeper location, it might have been possible to provisionally rule out malignancy at this stage, depending on the degree of experience. However, because of the many unusual features of POF, in terms of its size, clinical course, epidemiological background, and imaging findings suggestive of malignancy, it seemed practically difficult to exclude the possibility of malignancy on the basis of the preoperative examination alone.

In a review of reports of giant cases of POF (consisting of ten cases measuring 2.5 cm or larger) [ 22 ], although most required discrimination from malignancy, the proportion of cases with local bone resorption and that of cases with tooth displacement within the lesion were both at most half, suggesting that we should recognize the difficulty of pretreatment differential diagnosis in such giant POFs, as experienced in the present case. Regarding the differential diagnosis from other inflammatory proliferative lesions of the gingiva, peripheral giant cell granuloma (PGCG) is most similar to POF in that it is a reactive lesion that originates exclusively in the periodontal ligament or periosteum of the gingiva [ 4 ]. PGCG can be distinguished from POF by its common development in females between the fourth and sixth decades of life, its presentation as a relatively soft nodular mass, and its histological features consisting of a proliferation of mesenchymal cells and multinucleated giant cells associated with prominent vascular growth [ 4 , 9 , 23 ]. However, approximately one-third of PGCG also contains bone components [ 4 , 23 ], indicating that caution is still needed to distinguish them from each other.

Although conservative local resection is the standard treatment for POF, complete excision of the lesion, including the adjacent periodontal ligament or periosteum where the POF originates, as well as removal of the source of the irritating stimuli, are essential to eliminate the chances of recurrence [ 2 , 6 , 8 , 9 , 14 ]. In the present case, since no malignancy was reported even on intraoperative histological examination, the resection margin was determined to be as minimal as necessary in accordance with benign tumors. However, to eradicate the possible residual lesions, additional shaving and scraping of the alveolar portion of the maxilla were performed beyond the depth at which the healthy bone was exposed.

Through our experience with this case, we undeniably recognized three possible pitfalls associated with the terminology of POF that should be noted when correctly diagnosing POF and better understanding its pathogenesis. First, the disease conventionally referred to as “ossifying fibroma” means a benign tumor of bone origin whose pathogenesis is entirely different from that of POF. The origin of ossifying fibroma is the periodontal ligament (which is in common with POF) or endosteum (a very thin connective tissue layer covering the bone marrow cavity inside the bone cortex), which principally expands into the medullary space of the bone [ 3 , 6 , 7 , 12 ]. Since ossifying fibroma is sometimes referred to as “central ossifying fibroma” (COF) when it needs to be clearly distinguished from POF, it should be noted that the terms “central” versus “peripheral” in this context are employed simply in the sense of indicating their positional relationship in the bone structure [ 13 ]. Furthermore, the term “ossifying fibroma” can be referred to in multiple senses (in both broad and narrow senses); it is generally used in the narrow sense to refer to COF, whereas it is sometimes used in the broad sense as an umbrella term for both COF and POF, making the interpretation of this term quite confusing and ambiguous, which requires us to carefully distinguish the meaning indicated by the term depending on the situation [ 6 , 13 ].

Second, a multitude of synonyms have been used in the nomenclature of POF. Those seen in previous papers are as follows: “peripheral cemento-ossifying fibroma,” “ossifying fibro-epithelial polyp,” “peripheral fibroma with osteogenesis,” “peripheral fibroma with cementogenesis,” “peripheral fibroma with calcification,” “calcifying or ossifying fibroma epulis,” “calcifying fibroblastic granuloma,” “ossifying fibrous epulis,” “peripheral cementifying fibroma,” “calcifying fibroma,” “calcified peripheral fibroma,” and “calcified or ossified fibrous granuloma” [ 2 , 5 , 6 , 7 , 9 , 10 , 13 , 14 ]. Most appear to be a combination of terms meaning “ossification” or “calcification,” and “fibroma” or “fibrous.” However, numerous different names used for the identical pathological condition have led to a considerable degree of confusion in clinical practice [ 4 , 5 , 6 , 10 , 13 ], which appears to be the decisive factor in preventing the spread of accurate recognition of POF. Fortunately, in recent years, a consensus has emerged regarding the use of “peripheral ossifying fibroma (POF)” as the English term for this pathological condition, although a few exceptions remain. Furthermore, since the term “fibroma” literally refers to “benign tumor of fibrous connective tissue origin,” nomenclature-wise, the naming of POF (peripheral ossifying fibroma) itself is undoubtedly a misnomer for the inflammatory reactive proliferative lesion. However, revising its designation at this stage seems rather unwise, as it would have a much greater disadvantage of causing additional unnecessary confusion.

Third, POF should also be distinguished from “peripheral odontogenic fibroma,” a different disease for which the same abbreviation “POF” has been applied [ 12 , 20 ]. Odontogenic fibroma is classified as one of benign mesenchymal odontogenic tumors in the World Health Organization (WHO) classification, which is further divided into endosteal “central odontogenic fibroma” and extraosseous “peripheral odontogenic fibroma” according to their position in the bone structure; both of these conditions are thus entirely different from POF [ 2 , 13 ]. The distinction between peripheral ossifying fibroma, an inflammatory reactive proliferative lesion, and peripheral odontogenic fibroma, a benign tumor, is quite misleading because they share the same abbreviation, “POF,” which requires caution to not confuse them.

Although POF is an inflammatory reactive proliferative lesion, its extreme enlargement can cause alveolar bone destruction and hyperaccumulation of FDG on PET/CT, making the differential diagnosis from gingival malignancy difficult. Proper diagnosis relies on the recognition of its characteristic histopathological findings and identification of possible underlying chronic mechanical stimuli, while successful treatment mandates complete resection of the lesion and improvement of problematic oral hygiene. Due to the numerous synonyms for POF and coexistence of very similar names for different neoplastic diseases, appropriate interpretation and sufficient awareness of these disease names are required to avoid diagnostic confusion and provide optimal management.

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The collected data and materials that can identify the patient are not publicly available because of the adequate protection of patient privacy. All other data collected and analyzed during this case study are included in this published article.

Abbreviations

Central ossifying fibroma

Computed tomography

Fluorodeoxyglucose

Immediate surgical obturator

Positron emission tomography with computed tomography

Peripheral giant cell granuloma

• Peripheral ossifying fibroma

Smooth muscle actin

Standardized uptake value

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We would like to thank Editage ( www.editage.com ) for English language editing.

This work was supported in part by a Grant-in-Aid for Scientific Research (C) from The Japan Society for the Promotion of Science (23K08918).

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Department of Otorhinolaryngology-Head and Neck Surgery, International University of Health and Welfare, School of Medicine, Narita Hospital, Narita, Japan

Ryo Takagi, Kosei Mori, Takashi Koike, Sayumi Tsuyuguchi, Kengo Kanai, Yoshihiro Watanabe, Mitsuhiro Okano, Yoshihiro Noguchi & Yorihisa Imanishi

Department of Oral Rehabilitation and Maxillofacial Surgery, International University of Health and Welfare, School of Medicine, Narita Hospital, Narita, Japan

Aya Tanaka, Kinue Kurihara, Kazumichi Sato & Ken Ishizaki

Department of Pathology, International University of Health and Welfare, School of Medicine, Narita Hospital, Narita, Japan

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RT treated the patient, collected and analyzed the materials and data, and drafted the manuscript. KM, TK, ST, KKa, and YW helped manage the patient and supported the data interpretation. AT, KKu, and KS treated and managed the patient in their capacity as dentists and oral surgeons. MO, YN, and KI provided helpful advice and administrative support. YH made the pathological diagnosis and provided critical suggestions. YI treated and managed the patient, organized the materials and data, and wrote and revised the manuscript. All the authors have read and approved the final manuscript.

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Takagi, R., Mori, K., Koike, T. et al. A giant peripheral ossifying fibroma of the maxilla with extreme difficulty in clinical differentiation from malignancy: a case report and review of the literature. J Med Case Reports 18 , 220 (2024). https://doi.org/10.1186/s13256-024-04529-9

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Received : 29 February 2024

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DOI : https://doi.org/10.1186/s13256-024-04529-9

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• Reactive proliferative lesion
• Ossification
• Periodontal ligament
• Differential diagnosis
• Terminology

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