Opportunities of digital twin in controlling and monitoring microbial processes in food fermentation
Krati Shukla , Sharon Nagpal , Ashish Vyas
Systems Microbiology and Biomanufacturing ›› 2026, Vol. 6 ›› Issue (3) : 56
Smart fermentation system / Internet of Things (IoT) / Industry 4.0 / Microbial process optimization / Modelling and prediction / Real-time data synchronization / Cloud-based bioprocessing
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
Appl C, Moser A, Baganz F, Hass VC. Digital twins for bioprocess control strategy development and realisation. In: Herwig C, Pörtner R, Möller J, editors. Digital Twins, vol. 177. Springer International Publishing; 2020. pp. 63–94. https://doi.org/10.1007/10_2020_151. |
| [6] |
Beri R, Sachdeva P. (2025). Integrating edge-cloud computing and IoT for Real-time food quality assessment. In T. Senjyu, C. So-In, & A. Joshi, editors, Smart Trends in Computing and Communications (Vol. 1469, pp. 69–78). Springer; Singapore. https://doi.org/10.1007/978-981-96-7807-5_7 |
| [7] |
|
| [8] |
Buonocore D, Ciavolino G, Caro DD, Liguori C. An IoT-based beer fermentation monitoring system. 2021 IEEE international workshop on metrology for agriculture and forestry (MetroAgriFor). 2021. 263–267. https://doi.org/10.1109/MetroAgriFor52389.2021.9628536 |
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
Food fermentations. NIR spectroscopy as a tool for process analytical technology. In Advances in Food and Nutrition Research. Elsevier; 2025. Vol. 115, pp. 391–430. https://doi.org/10.1016/bs.afnr.2025.06.002 |
| [18] |
|
| [19] |
|
| [20] |
Glaessgen, E., & Stargel, D. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference20th AIAA/ASME/AHS Adaptive Structures Conference14th AIAA. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference<BR>20th AIAA/ASME/AHS Adaptive Structures Conference<BR>14th AIAA, Honolulu, Hawaii; 2012. https://doi.org/10.2514/6.2012-1818 |
| [21] |
Goffi P-E, Tremblay R, Oakes B. Engineering a Digital Twin for the monitoring and control of beer fermentation sampling (version 1). arXiv. 2025. https://doi.org/10.48550/ARXIV.2508.18452. |
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
Grieves M, Vickers J. Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. In Kahlen F-J, Flumerfelt S, Alves A, editors, Transdisciplinary Perspectives on Complex Systems. Springer International Publishing; 2017. pp. 85–113. https://doi.org/10.1007/978-3-319-38756-7_4 |
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
INRAE. FermenTwin: Digital twin for food microbiota prediction in vegetable fermentation. 2024. https://fme.micalis.fr/projects/fermentwin/ |
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
Keskin E, Yıldırım IO. Cultivating precision: Comparative analysis of sensor-based yogurt fermentation monitoring techniques (version 1). arXiv. 2025. https://doi.org/10.48550/ARXIV.2501.08781. |
| [40] |
|
| [41] |
|
| [42] |
|
| [43] |
|
| [44] |
Lee A, Manrique Negrin DA, Cleophas L. Evaluating open-source tools for heterogeneous model-based digital twin development: A microbrewery case study. 2024 Annual Modeling and Simulation Conference (ANNSIM). 2024a. 1–13. https://doi.org/10.23919/ANNSIM61499.2024.10732658 |
| [45] |
|
| [46] |
|
| [47] |
|
| [48] |
|
| [49] |
Mendes I, Monteiro J, Barata J. A heritage Digital Twin for Serra Da Estrela Cheese production. 32nd International Conference on Information Systems Development, Gdańsk, Poland; 2024. https://doi.org/10.62036/ISD.2024.3 |
| [50] |
|
| [51] |
|
| [52] |
|
| [53] |
|
| [54] |
Neubauer P, Anane E, Junne S, Cruz Bournazou MN. Potential of integrating model-based design of experiments approaches and process analytical technologies for bioprocess scale-down. In: Herwig C, Pörtner R, Möller J, editors. Digital Twins. Volume 177. Springer International Publishing; 2020. pp. 1–28. https://doi.org/10.1007/10_2020_154. |
| [55] |
|
| [56] |
|
| [57] |
|
| [58] |
|
| [59] |
|
| [60] |
|
| [61] |
|
| [62] |
|
| [63] |
|
| [64] |
|
| [65] |
|
| [66] |
|
| [67] |
|
| [68] |
|
| [69] |
|
| [70] |
Sinner P, Daume S, Herwig C, Kager J. Usage of Digital Twins Along a Typical Process Development Cycle. In: Herwig C, Pörtner R, Möller J, editors. Digital Twins. Volume 176. Springer International Publishing; 2020. pp. 71–96. https://doi.org/10.1007/10_2020_149. |
| [71] |
Sivakumar M, Maranco M, Krishnaraj N, Reddy US. Data analytics and visualization in smart manufacturing using AI-based Digital Twins. In A. K. Tyagi, S. Tiwari, S. K. Arumugam, & A. K. Sharma, editors, Artificial Intelligence‐Enabled Digital Twin for Smart Manufacturing (1st ed., pp. 249–277). Wiley; 2024. https://doi.org/10.1002/9781394303601.ch12 |
| [72] |
|
| [73] |
|
| [74] |
|
| [75] |
|
| [76] |
The PAT pathway to scalable and sustainable precision fermentation, Hamilton company. (2024). https://processanalytics.hamiltoncompany.com/hubfs/00%20%20Process%20Analytics/Documents%20%28PA%29/PDFs/White-Papers/11100988500_Whitepaper_PAT_PrecisionFermentation_LR.pdf |
| [77] |
|
| [78] |
T SK, Saranyadevi S, Abdullahi A, Navina B. Microbial fermentation profiling: Tools and techniques for food analysis. In T. Sarkar, editor, Novel Food Analysis. Springer, US; 2025. pp. 295–320. https://doi.org/10.1007/978-1-0716-4787-5_14 |
| [79] |
|
| [80] |
|
| [81] |
|
| [82] |
|
| [83] |
|
| [84] |
|
| [85] |
|
| [86] |
WINE-PRO Project. Digital twin for wine fermentation process optimisation. 2023. https://ss4af.com/en/highfive/projects/wine-pro-digital-twin-wine-fermentation-process-optimisation |
| [87] |
Wu J, Wu C-C, Liao C-S. Novel Lactobacillus Fermentation Prediction Using Deep Learning. 2021 7th International Conference on Applied System Innovation (ICASI). 2021. pp. 54–57. https://doi.org/10.1109/ICASI52993.2021.9568412 |
| [88] |
|
| [89] |
|
| [90] |
|
| [91] |
|
| [92] |
|
| [93] |
|
| [94] |
|
Jiangnan University
/
| 〈 |
|
〉 |