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Vegetable fermentation as an overlooked source of greenhouse gases: from microbial mechanisms to global budget implications


Abstract

Vegetable fermentation represents a globally ubiquitous yet overlooked source of greenhouse gas (GHG) emissions. This study quantified GHG fluxes and integrated 16S rRNA sequencing to elucidate the potential microbial mechanisms using a 90-day cabbage fermentation model. High-salt conditions enhanced cumulative CO₂ emissions 2.1-fold relative to the low-salt treatment. This amplification was driven by salt-induced osmotic dehydration accelerating dissolved organic carbon release from vegetable tissues, which likely fueled heterofermentative guilds (e.g., Leuconostoc) and resulted in elevated CO₂ production. Conversely, low-to-medium salt concentrations favored N₂O generation via nitrification and denitrification by salt-sensitive Proteobacteria (e.g., Enterobacter), whereas high salinity shifted nitrogen flux toward dissimilatory nitrate reduction to ammonium (DNRA), thereby minimizing gaseous losses. Globally, vegetable fermentation is estimated to contribute between 16,483 and 56,872 tonnes of CO₂-equivalent annually. These findings establish vegetable fermentation as an important GHG source, offering new insights for mitigating the food industry’s environmental footprint.

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Data availability

The raw 16S rRNA gene sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under accession number SRP648168. The raw abundance data corresponding to Fig. 6 are provided in Table S8. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Torres, S., Verón, H., Contreras, L. & Isla, M. I. An overview of plant-autochthonous microorganisms and fermented vegetable foods. Food Sci. Hum. Well. 9, 112–123 (2020).

    Google Scholar 

  2. Tamang, J. P. et al. Fermented foods in a global age: East meets West. Compr. Rev. Food Sci. F. 19, 184–217 (2020).

    Google Scholar 

  3. Yu, Y. et al. Isolation of lactic acid bacteria from Chinese pickle and evaluation of fermentation characteristics. LWT 180, 114627 (2023).

    Google Scholar 

  4. Mi, T. et al. Effects of salt concentration on the quality and microbial diversity of spontaneously fermented radish paocai. Food Res. Int. 160, 111622 (2022).

    Google Scholar 

  5. Li, Y. et al. Fermentation modeling and machine learning for flavor prediction in low-sodium radish paocai with potassium chloride substitution. npj Sci. Food 9, 156 (2025).

    Google Scholar 

  6. Wang, G. & Wu, X. Research on the development of Qiandongnan-flavor pickles. Rural Pract. Technol. 9, 115–116 (2020).

    Google Scholar 

  7. Kim, S. H. et al. Lactic acid bacteria directly degrade N-nitrosodimethylamine and increase the nitrite-scavenging ability in kimchi. Food Control 71, 101–109 (2017).

    Google Scholar 

  8. Cole, J. J. et al. Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems 10, 172–185 (2007).

    Google Scholar 

  9. Dinsmore, K. J. et al. Role of the aquatic pathway in the carbon and greenhouse gas budgets of a peatland catchment. Glob. Chang. Biol. 16, 2750–2762 (2010).

    Google Scholar 

  10. Liu, L. et al. Residual nitrite and biogenic amines of traditional northeast sauerkraut in China. Int. J. Food Prop. 20, 2448–2455 (2017).

    Google Scholar 

  11. Song, Q. et al. Metagenomic insights into Chinese northeast suancai: Predominance and diversity of genes associated with nitrogen metabolism in traditional household suancai fermentation. Food Res. Int. 139, 109924 (2021).

    Google Scholar 

  12. Kuypers, M. M., Marchant, H. K. & Kartal, B. The microbial nitrogen-cycling network. Nat. Rev. Microbiol. 16, 263–276 (2018).

    Google Scholar 

  13. Tang, J. et al. Effect of salt concentration on the quality and microbial community during pickled peppers fermentation. Food Chem. X 23, 101594 (2024).

    Google Scholar 

  14. Peng, X., Kelly, R. M. & Han, Y. Sequential processing with fermentative Caldicellulosiruptor kronotskyensis and chemolithoautotrophic Cupriavidus necator for converting rice straw and CO2 to polyhydroxybutyrate. Biotechnol. Bioeng. 115, 1624–1629 (2018).

    Google Scholar 

  15. Heyer, R. et al. Breakdown of hardly degradable carbohydrates (lignocellulose) in a two-stage anaerobic digestion plant is favored in the main fermenter. Water Res. 250, 121020 (2024).

    Google Scholar 

  16. Chun, B. H. et al. Pan-genomic and transcriptomic analyses of Leuconostoc mesenteroides provide insights into its genomic and metabolic features and roles in kimchi fermentation. Sci. Rep. 7, 11504 (2017).

    Google Scholar 

  17. Zhai, Y. & Pérez-Díaz, I. M. Contribution of Leuconostocaceae to CO2-mediated bloater defect in cucumber fermentation. Food Microbiol. 91, 103536 (2020).

    Google Scholar 

  18. Liang, H. et al. Bacterial profiles and volatile flavor compounds in commercial Suancai with varying salt concentration from Northeastern China. Food Res. Int. 137, 109384 (2020).

    Google Scholar 

  19. Lee, D. Y. et al. A comparative study of the physicochemical, microbial, and metabolic profiling of kimchi during long-term fermentation under varying salinity conditions. LWT 196, 115838 (2024).

    Google Scholar 

  20. Bautista-Gallego, J. et al. Salt reduction in vegetable fermentation: reality or desire? J. Food Sci. 78, R1095–R1100 (2013).

    Google Scholar 

  21. Zhao, C. C. et al. Kinetic study of mass transfer in different parts of Chinese cabbage during brining. J. Food Process Eng. 41, e12666 (2018).

    Google Scholar 

  22. Herman-Lara, E. et al. Mass transfer modeling of equilibrium and dynamic periods during osmotic dehydration of radish in NaCl solutions. Food Bioprod. Process 91, 216–224 (2013).

    Google Scholar 

  23. Chen, D. et al. Altering bacterial community: a possible way of lactic acid bacteria inoculants reducing CO2 production and nutrient loss during fermentation. Bioresour. Technol. 329, 124915 (2021).

    Google Scholar 

  24. Kandler, O. Carbohydrate metabolism in lactic acid bacteria. Anton. Leeuw. Int. J. G. 49, 209–224 (1983).

    Google Scholar 

  25. Bouwman, A. F. et al. Global trends and uncertainties in terrestrial denitrification and N2O emissions. Phil. Trans. R. Soc. 368, 20130112 (2013).

    Google Scholar 

  26. Lam, S. K., Suter, H., Mosier, A. R. & Chen, D. Using nitrification inhibitors to mitigate agricultural N2O emission: a double-edged sword?. Glob. Chang. Biol. 23, 485–489 (2017).

    Google Scholar 

  27. Ruser, R. & Schulz, R. The effect of nitrification inhibitors on the nitrous oxide (N2O) release from agricultural soils—a review. J. Plant Nutr. Soil Sci. 178, 171–188 (2015).

    Google Scholar 

  28. Zumft, W. G. Cell biology and molecular basis of denitrification. Microbiol. Mol. Biol. Rev. 61, 533–616 (1997).

    Google Scholar 

  29. Mpongwana, N. et al. Isolation of high-salinity-tolerant bacterial strains, Enterobacter sp., Serratia sp., and Yersinia sp., for nitrification and aerobic denitrification under cyanogenic conditions. Water Sci. Technol. 73, 2168–2175 (2016).

    Google Scholar 

  30. Zheng, H. Effects of salinity on nitrogen reduction pathways in estuarine wetland sediments. Mar. Pollut. Bull. 207, 116834 (2024).

    Google Scholar 

  31. Giblin, A. E. et al. The effects of salinity on nitrogen losses from an oligohaline estuarine sediment. Estuar. Coast. 33, 1054–1068 (2021).

    Google Scholar 

  32. Jia, M., Winkler, M. K. & Volcke, E. I. Elucidating the competition between heterotrophic denitrification and DNRA using the resource-ratio theory. Environ. Sci. Technol. 54, 13953–13962 (2020).

    Google Scholar 

  33. Lin, B. & Lei, X. Carbon emissions reduction in China’s food industry. Energy Policy 86, 483–492 (2015).

    Google Scholar 

  34. Boehm, R. et al. A comprehensive life cycle assessment of greenhouse gas emissions from US household food choices. Food Policy 79, 67–76 (2018).

    Google Scholar 

  35. Naresh Kumar, S. & Chakabarti, B. Energy and carbon footprint of food industry. in Energy Footprints of the Food and Textile Sectors. Environmental Footprints and Eco-design of Products and Processes (eds Muthu, S.) Springer 19–44 (Springer, 2019).

  36. McGill, B. M., Hamilton, S. K., Millar, N. & Robertson, G. P. The greenhouse gas cost of agricultural intensification with groundwater irrigation in a Midwest US row cropping system. Glob. Chang. Biol. 24, 5948–5960 (2018).

    Google Scholar 

  37. Huo, P. & Gao, P. Degassing of greenhouse gases from groundwater under different irrigation methods: a neglected carbon source in agriculture. Agric. Water Manag. 301, 108941 (2024).

    Google Scholar 

  38. FAO. Agricultural Production Statistics 2010–2023 (FAO, 2024).

  39. Toensmeier, E., Ferguson, R. & Mehra, M. 2020. Perennial vegetables: a neglected resource for biodiversity, carbon sequestration, and nutrition. PLoS ONE 15, e0234611 (2020).

    Google Scholar 

  40. Sharma, S. et al. Appraisal of carbon capture, storage, and utilization through fruit crops. Front. Environ. Sci. 9, 700768 (2021).

    Google Scholar 

  41. Garrido, A. et al. Fruit photosynthesis: more to know about where, how and why. Plants 12, 2393 (2023).

    Google Scholar 

  42. Liang, H. et al. Synergistic effects of carbon cycle metabolism and photosynthesis in Chinese cabbage under salt stress. Hortic. Plant J. 10, 461–472 (2024).

    Google Scholar 

  43. Huisingh, D. et al. Recent advances in carbon emissions reduction: policies, technologies, monitoring, assessment, and modeling. J. Clean. Prod. 103, 1–12 (2015).

    Google Scholar 

  44. IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) 2391 https://doi.org/10.1017/9781009157896 (Cambridge University Press, 2021).

  45. Fowler, D. et al. The global nitrogen cycle in the twenty-first century. Philos. Trans. R. Soc. B Biol. Sci. 368, 20130164 (2013).

    Google Scholar 

  46. Xu, J. et al. A review on fermented vegetables: microbial community and potential upgrading strategy via inoculated fermentation. Compr. Rev. Food Sci. Food Saf. 23, e13362 (2024).

    Google Scholar 

  47. Blandino, A. et al. Cereal-based fermented foods and beverages. Food Res. Int. 36, 527–543 (2003).

    Google Scholar 

  48. Auchtung, J. M., Hallen-Adams, H. E. & Hutkins, R. Microbial interactions and ecology in fermented food ecosystems. Nat. Rev. Microbiol. 23, 622–634 (2025).

    Google Scholar 

  49. De Laurentiis, V., Corrado, S. & Sala, S. Quantifying household waste of fresh fruit and vegetables in the EU. Waste Manage 77, 238–251 (2018).

    Google Scholar 

  50. Pérez-Marroquín, X. A. et al. Agro-food waste as an ingredient in functional beverage processing: sources, functionality, market and regulation. Foods 12, 1583 (2023).

    Google Scholar 

  51. Park, S. E. et al. Effects of different fermentation temperatures on metabolites of Kimchi. Food Biosci. 23, 100–106 (2018).

    Google Scholar 

  52. Kim, J. et al. Controlled fermentation of kimchi using naturally occurring antimicrobial agents. Food Microbiol. 32, 20–31 (2012).

    Google Scholar 

  53. Lee, J. et al. Unravelling the key factors for the dominance of Leuconostoc starters during kimchi fermentation. npj Sci. Food 9, 61 (2025).

    Google Scholar 

  54. Kang, B. K. et al. The influence of red pepper powder on the density of Weissella koreensis during kimchi fermentation. Sci. Rep. 5, 15445 (2015).

    Google Scholar 

  55. Huang, T. T., Wu, Z. Y. & Zhang, W. X. 2020. Effects of garlic addition on bacterial communities and the conversions of nitrate and nitrite in a simulated pickle fermentation system. Food Control 113, 107215 (2020).

    Google Scholar 

  56. Xu, J. et al. Mining of characteristic microbes and qualities in pickled and salted chili peppers through integrated analysis. npj Sci. Food 9, 77 (2025).

    Google Scholar 

  57. Xia, Y., Zhu, W., Su, Y. & Chen, Y. Novel insights into the quality changes and metabolite transfer rules of pickles during fermentation: Pickle versus pickle solution. Food Chem. X 25, 102203 (2025).

    Google Scholar 

  58. Moon, E. W., Yang, J. S., Yoon, S. R. & Ha, J. H. Application of colorimetric indicators to predict the fermentation stage of kimchi. J. Food Sci. 85, 4170–4179 (2020).

    Google Scholar 

  59. Zhao, Z. et al. Metabolites changes of a low-temperature and low-salt fermented Chinese kohlrabi during fermentation based on non-targeted metabolomic analysis. Front. Sustain. Food Syst. 7, 1156173 (2023).

    Google Scholar 

  60. Johnson, K. M., Hughes, J. E., Donaghay, P. L. & Sieburth, J. M. Bottle-calibration static head space method for the determination of methane dissolved in seawater. Anal. Chem. 62, 2408–2412 (1990).

    Google Scholar 

  61. Weiss, R. F. & Price, B. A. Nitrous oxide solubility in water and seawater. Mar. Chem. 8, 347–359 (1980).

    Google Scholar 

  62. National Food Safety Standard: Determination of Nitrite and Nitrate in Foods (China Standards Press, 2016).

  63. Wood, W. W. & Hyndman, D. W. Groundwater depletion: a significant unreported source of atmospheric carbon dioxide. Earth Future 5, 1133–1135 (2017).

    Google Scholar 

  64. World Meteorological Organization. WMO Greenhouse Gas Bulletin (No. 21): The state of greenhouse gases in the atmosphere based on global observations through 2024. https://wmo.int/files/greenhouse-gas-bulletin-no-21 (2025).

  65. Chen, S., Zhou, Y., Chen, Y. & Gu, J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).

    Google Scholar 

  66. Magoč, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).

    Google Scholar 

  67. Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Google Scholar 

  68. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).

    Google Scholar 

  69. Louca, S., Parfrey, L. W. & Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 353, 1272–1277 (2016).

    Google Scholar 

  70. Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).

    Google Scholar 

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Acknowledgements

This study was supported by the Department of Agriculture and Rural Affairs of Shaanxi Province (Grant No. S202101010). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Pan Huo: Conceptualization, Data curation, Investigation, Visualization, Writing—original draft. Xinyu Zhang: Investigation, Data curation, Visualization. Chunyan Xu: Investigation, Data curation. Tianyi Han: Investigation. Pengcheng Gao: Conceptualization, Supervision, Writing – review & editing.

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Correspondence to
Pengcheng Gao.

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Huo, P., Zhang, X., Xu, C. et al. Vegetable fermentation as an overlooked source of greenhouse gases: from microbial mechanisms to global budget implications.
npj Sci Food (2026). https://doi.org/10.1038/s41538-026-00825-4

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